Source author record

D. Thirumalai

D. Thirumalai appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record

cond-mat.soft Biomolecules Biological Physics cond-mat.stat-mech physics.chem-ph Molecular Networks Subcellular Processes Cell Behavior Tissues and Organs cond-mat.dis-nn Genomics physics.comp-ph Populations and Evolution q-bio Quantitative Methods

Catalog footprint

What is connected

64works

15topics

4close collaborators

Actions

Connect this record

Open graph Browse works

Inspect adjacent papers, topics, institutions and collaborators without losing the researcher page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

preprint2026arXiv

Loop Extrusion Reversal by Condensin Motor is Mediated by Catch Bonds

Structural Maintenance Complexes (SMC) are energy consuming motors that are important in folding the genome by loop extrusion (LE) in all stages of the cell cycle. Single molecule magnetic tweezer pulling experiments have revealed that condensin, a member of the SMC family involved in mitosis, takes occasional backward steps, thus coughing up the gains in the length of the extruded loop. To reveal the mechanism of the forward and backward steps simultaneously, we developed a theory using the stochastic kinetic model and the scrunching mechanism for LE. The calculations quantitatively account for the measured force-dependent step size and dwell time distributions in both the directions. By postulating the existence of an intermediate state in the ATP-driven cycle that is poised to take a forward or a backward step, we predict that its lifetime increases as the external mechanical force increases till a critical value and subsequently decreases at higher forces. The surprising finding of lifetime increase in an active motor, at sub-piconewton forces, is the characteristic of catch bonds, known in force-induced rupture of several passive protein complexes. The identification of catch bond-like states in condensin not only expands our understanding of LE but also highlights the significance of mechanical forces in regulating genome organization.

preprint2022arXiv

Mechanical feedback controls the emergence of dynamical memory in growing tissue monolayers

The growth of a tissue, which depends on cell-cell interactions and biologically relevant process such as cell division and apoptosis, is regulated by a mechanical feedback mechanism. We account for these effects in a minimal two-dimensional model in order to investigate the consequences of mechanical feedback, which is controlled by a critical pressure, $p_c$. A cell can only grow and divide if the pressure it experiences, due to interaction with its neighbors, is less than $p_c$. Because temperature is an irrelevant variable in the model, the cell dynamics is driven by self-generated active forces (SGAFs) that are created by cell division. It is shown that even in the absence of intercellular interactions, cells undergo diffusive behavior. The SGAF driven diffusion is indistinguishable from the well-known dynamics of a free Brownian particle at a fixed finite temperature. When intercellular interactions are taken into account, we find persistent temporal correlations in the force-force autocorrelation function ($FAF$) that extends over timescale of several cell division times. The time-dependence of the $FAF$ reveals memory effects, which increases as pc increases. The observed non-Markovian effects emerge due to the interplay of cell division and mechanical feedback, and is inherently a non-equilibrium phenomenon.

preprint2021arXiv

On the emergence of orientational order in folded proteins with implications for allostery

The beautiful structures of single and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instances that require a combination of softness and rigidity within the same molecule. By analyzing the solved protein structures, we show that orientational symmetry is broken in the aperiodic arrangement of the secondary structural elements (SSEs), which we deduce by calculating the nematic order parameter, $P_{2}$. We find that the folded structures are nematic droplets with a broad distribution of $P_{2}$. We argue that non-zero values of $P_{2}$, leads to an arrangement of the SSEs that can resist mechanical forces, which is a requirement for allosteric proteins. Such proteins, which resist mechanical forces in some regions while being flexible in others, transmit signals from one region of the protein to another (action at a distance) in response to binding of ligands (oxygen, ATP or other small molecules).

preprint2020arXiv

Cooperation among tumor cell subpopulations leads to intratumor heterogeneity

Heterogeneity is a hallmark of all cancers. Tumor heterogeneity is found at different levels -- interpatient, intrapatient, and intratumor heterogeneity. All of them pose challenges for clinical treatments. The latter two scenarios can also increase the risk of developing drug resistance. Although the existence of tumor heterogeneity has been known for two centuries, a clear understanding of its origin is still elusive, especially at the level of intratumor heterogeneity (ITH). The coexistence of different subpopulations within a single tumor has been shown to play crucial roles during all stages of carcinogenesis. Here, using concepts from evolutionary game theory and public goods game, often invoked in the context of the tragedy of commons, we explore how the interactions among subclone populations influence the establishment of ITH. By using an evolutionary model, which unifies several experimental results in distinct cancer types, we develop quantitative theoretical models for explaining data from {\it in vitro} experiments involving pancreatic cancer as well as {\it vivo} data in glioblastoma multiforme. Such physical and mathematical models complement experimental studies, and could optimistically also provide new ideas for the design of efficacious therapies for cancer patients.

preprint2020arXiv

Dual Role of Cell-Cell Adhesion In Tumor Suppression and Proliferation Due to Collective Mechanosensing

It is known that mechanical interactions couple a cell to its neighbors, enabling a feedback loop to regulate tissue growth. However, the interplay between cell-cell adhesion strength, local cell density and force fluctuations in regulating cell proliferation is poorly understood. Here, we show that spatial variations in the tumor growth rates, which depend on the location of cells within tissue spheroids, are strongly influenced by cell-cell adhesion. As the strength of the cell-cell adhesion increases, intercellular pressure initially decreases, enabling dormant cells to more readily enter into a proliferative state. We identify an optimal cell-cell adhesion regime where pressure on a cell is a minimum, allowing for maximum proliferation. We use a theoretical model to validate this novel collective feedback mechanism coupling adhesion strength, local stress fluctuations and proliferation.Our results, predicting the existence of a non-monotonic proliferation behavior as a function of adhesion strength, are consistent with experimental results. Several experimental implications of the proposed role of cell-cell adhesion in proliferation are quantified, making our model predictions amenable to further experimental scrutiny. We show that the mechanism of contact inhibition of proliferation, based on a pressure-adhesion feedback loop, serves as a unifying mechanism to understand the role of cell-cell adhesion in proliferation.

preprint2020arXiv

Spatially Heterogeneous Dynamics of Cells in a Growing Tumor Spheroid: Comparison Between Theory and Experiments

Collective cell movement, characterized by multiple cells that are in contact for substantial periods of time and undergo correlated motion, plays a central role in cancer and embryogenesis. Recent imaging experiments have provided time-dependent traces of individual cells, thus providing an unprecedented picture of tumor spheroid growth. By using simulations of a minimal cell model, we analyze the experimental data that map the movement of cells in fibrosarcoma tumor spheroid embedded in a collagen matrix. Both simulations and experiments show that cells in the core of the spheroid exhibit subdiffusive glassy dynamics (mean square displacement, $Δ(t) \approx t^α$ with $α< 1$), whereas cells in the periphery exhibit superdiffusive motion, $Δ(t) \approx t^α$ with $α>1)$. The motion of most of the cells near the periphery undergo highly persistent and correlated directional motion, thus explaining the observed superdiffusive behavior. The $α$ values for cells in the core and periphery, extracted from simulations and experiments are in near quantitative agreement with each other, which is surprising given that no parameter in the model was used to fit the measurements. The qualitatively different dynamics of cells in the core and periphery is captured by the fourth order susceptibility, introduced to characterize metastable states in glass forming systems. Analyses of the velocity autocorrelation of individual cells show remarkable spatial heterogeneity with no two cells exhibiting similar behavior. The prediction that $α$ should depend on the location of the cells in the tumor is amenable to experimental test. The highly heterogeneous dynamics of cells in the tumor spheroid provides a plausible mechanism for the origin of intratumor heterogeneity.

preprint2019arXiv

Conformational Heterogeneity in Human Interphase Chromosome Organization Reconciles the FISH and Hi-C Paradox

Hi-C experiments are used to infer the contact probabilities between loci separated by varying genome lengths. Contact probability should decrease as the spatial distance between two loci increases. However, studies comparing Hi-C and FISH data show that in some cases the distance between one pair of loci, with larger Hi-C readout, is paradoxically larger compared to another pair with a smaller value of the contact probability. Here, we show that the FISH-Hi-C paradox can be resolved using a theory based on a Generalized Rouse Model for Chromosomes (GRMC). The FISH-Hi-C paradox arises because the cell population is highly heterogeneous, which means that a given contact is present in only a fraction of cells. Insights from the GRMC is used to construct a theory, without any adjustable parameters, to extract the distribution of subpopulations from the FISH data, which quantitatively reproduces the Hi-C data. Our results show that heterogeneity is pervasive in genome organization at all length scales, reflecting large cell-to-cell variations.

preprint2019arXiv

Fragile-to-Strong Crossover, growing length scales, and dynamic heterogeneity in Wigner Glasses

Colloidal particles, which are ubiquitous, have become ideal testing grounds for the structural glass transition (SGT) theories. In these systems glassy behavior is manifested as the density of the particles is increased. Thus, soft colloidal particles with varying degree of softness capture diverse glass forming properties, observed normally in molecular glasses. By performing Brownian dynamics simulations for a binary mixture of micron-sized charged colloidal suspensions, known to form Wigner glasses, we show that by tuning the softness of the potential, achievable by changing the monovalent salt concentration, there is a continuous transition between fragile to strong behavior. Remarkably, this is found in a system where the well characterized potential between the colloidal particles is isotropic. We also show that the predictions of the random first order transition (RFOT) theory quantitatively describes the universal features such as the growing correlation length, $ξ\sim (ϕ_K/ϕ- 1)^{-ν}$ with $ν= 2/3$ where $ϕ_K$, the analogue of the Kauzmann temperature, depends on the salt concentration. As anticipated by the RFOT predictions, we establish a causal relationship between the growing correlation length and a steep increase in the relaxation time and dynamic heterogeneity. The broad range of fragility observed in Wigner glasses is used to draw analogies with molecular glasses. The large variations in the fragility is found only when the temperature dependence of the viscosity is examined for a large class of diverse glass forming materials. In sharp contrast, this is vividly illustrated in a single system that can be experimentally probed. Our work also shows that the RFOT predictions are accurate in describing the dynamics over the entire density range, regardless of the fragility of the glasses, implying that the physics describing the SGT is universal.

preprint2019arXiv

How kinesin waits for ATP affects the nucleotide and load dependence of the stepping kinetics

Dimeric molecular motors walk on polar tracks by binding and hydrolyzing one ATP per step. Despite tremendous progress, the waiting state for ATP binding in the well-studied kinesin that walks on microtubule (MT), remains controversial. One experiment suggests that in the waiting state both heads are bound to the MT, while the other shows that ATP binds to the leading head after the partner head detaches. To discriminate between these two scenarios, we developed a theory to calculate accurately several experimentally measurable quantities as a function of ATP concentration and resistive force. In particular, we predict that measurement of the randomness parameter could discriminate between the two scenarios for the waiting state of kinesin, thereby resolving this standing controversy.

preprint2019arXiv

Theoretical Perspectives on Biological Machines

Many biological functions are executed by molecular machines, which consume energy and convert it into mechanical work. Biological machines have evolved to transport cargo, facilitate folding of proteins and RNA, remodel chromatin and replicate DNA. A common aspect of these machines is that their functions are driven out of equilibrium. It is a challenge to provide a general framework for understanding the functions of biological machines, such as molecular motors, molecular chaperones, and helicases. Using these machines as prototypical examples, we describe a few general theoretical methods providing insights into their functions. Although the theories rely on coarse-graining of these complex systems they have proven useful in not only accounting for many in vitro experiments but also addressing questions such as how the trade-off between precision, energetic costs and optimal performances are balanced. However, many complexities associated with biological machines will require one to go beyond current theoretical methods. Simple point mutations in the enzyme could drastically alter functions, making the motors bi-directional or result in unexpected diseases or dramatically restrict the capacity of molecular chaperones to help proteins fold. These examples are reminders that while the search for principles of generality in biology is intellectually stimulating, one also ought to keep in mind that molecular details must be accounted for to develop a deeper understanding of processes driven by biological machines. Going beyond generic descriptions of in vitro behavior to making genuine understanding of in vivo functions will likely remain a major challenge for some time to come. The combination of careful experiments and the use of physical principles will be useful in elucidating the rules governing the workings of biological machines.

preprint2018arXiv

Symmetry, Rigidity, and Allosteric Signaling: From Monomeric Proteins to Molecular Machines

Allosteric signaling in biological molecules, which may be viewed as specific action at a distance due to localized perturbation upon binding of ligands or changes in environmental cues, is pervasive in biology. Phenomenological MWC and KNF models galvanized research for over five decades, and these models continue to be the basis for describing the allostery in an array of systems. However, understanding allosteric signaling and the associated dynamics between distinct allosteric states is challenging. In this review, we first describe symmetry and rigidity as essential requirements for allosteric proteins. The general features, with MWC and KNF as two extreme scenarios, emerge when allosteric signaling is viewed from an energy landscape perspective. To go beyond the general theories, we describe computational tools to predict the network of residues that carry allosteric signals. Methods to obtain molecular insights into the dynamics of allosteric transitions are briefly mentioned. The utility of the methods is illustrated by applications to systems ranging from monomeric proteins to multisubunit proteins. Finally, the role allostery plays in the functions of ATP-consuming molecular machines, bacterial chaperonin GroEL and molecular motors, is described. Although universal molecular principles governing allosteric signaling do not exist, we can draw the following general conclusions. (1) Multiple pathways connecting allosteric states are highly heterogeneous. (2) Allosteric signaling is exquisitely sensitive to the architecture of the system, which implies that the capacity for allostery is encoded in the structure itself. (3) The mechanical modes that connect distinct allosteric states are robust to sequence variations. (4) Extensive investigations of allostery in Hemoglobin and more recently GroEL, show that a network of salt-bridge rearrangements serves as allosteric switches.

preprint2016arXiv

Discrete step sizes of molecular motors lead to bimodal non-Gaussian velocity distributions under force

Fluctuations in the physical properties of biological machines are inextricably linked to their functions. Distributions of run-lengths and velocities of processive molecular motors, like kinesin-1, are accessible through single molecule techniques, yet there is lack a rigorous theoretical model for these probabilities up to now. We derive exact analytic results for a kinetic model to predict the resistive force ($F$) dependent velocity ($P(v)$) and run-length ($P(n)$) distribution functions of generic finitely processive molecular motors that take forward and backward steps on a track. Our theory quantitatively explains the zero force kinesin-1 data for both $P(n)$ and $P(v)$ using the detachment rate as the only parameter, thus allowing us to obtain the variations of these quantities under load. At non-zero $F$, $P(v)$ is non-Gaussian, and is bimodal with peaks at positive and negative values of $v$. The prediction that $P(v)$ is bimodal is a consequence of the discrete step-size of kinesin-1, and remains even when the step-size distribution is taken into account. Although the predictions are based on analyses of kinesin-1 data, our results are general and should hold for any processive motor, which walks on a track by taking discrete steps.

preprint2016arXiv

Folding PDZ2 domain using the Molecular Transfer Model

A major challenge in molecular simulations is to describe denaturant-dependent folding of proteins order to make direct comparisons with {\it in vitro} experiments. We use the molecular transfer model, which is currently the only method that accomplishes this goal albeit phenomenologically, to quantitatively describe urea-dependent folding of PDZ domain, which plays a significant role in molecular recognition and signaling. Experiments show that urea-dependent unfolding rates of the PDZ2 domain exhibit a downward curvature at high urea concentrations, which has been interpreted by invoking the presence of a sparsely populated high energy intermediate. Simulations using the MTM and a coarse-grained model of PDZ2 are used to show that the intermediate, which has some native-like character, is present in equilibrium both in the presence and absence of urea. The free energy profiles show that there are two barriers separating the folded and unfolded states. Structures of the transition state ensembles, ($TSE1$ separating the unfolded and $I_{EQ}$ and $TSE2$ separating $I_{EQ}$ and the native state), determined using the $P_{fold}$ method, show that $TSE1$ is expanded; $TSE2$ and native-like. Folding trajectories reveal that PDZ2 folds by parallel routes. In one pathway folding occurs exclusively through $I_1$, which resembles $I_{EQ}$. In a fraction of trajectories, constituting the second pathway, folding occurs through a combination of $I_{1}$ and a kinetic intermediate. The radius of gyration ($R_g^{U}$) of the unfolded state is more compact (by $\sim$ 9\%) under native conditions. Decrease in $R_g^{U}$ occurs on the time scale on the order of utmost $\sim$ 20 $μs$. The modest decrease in $R_g^{U}$ and the rapid collapse suggest that high spatial and temporal resolution are needed to detect compaction in finite-sized proteins.

preprint2016arXiv

Noise control in gene regulatory networks with negative feedback

Genes and proteins regulate cellular functions through complex circuits of biochemical reactions. Fluctuations in the components of these regulatory networks result in noise that invariably corrupts the signal, possibly compromising function. Here, we create a practical formalism based on ideas introduced by Wiener and Kolmogorov (WK) for filtering noise in engineered communications systems to quantitatively assess the extent to which noise can be controlled in biological processes involving negative feedback. Application of the theory, which reproduces the previously proven scaling of the lower bound for noise suppression in terms of the number of signaling events, shows that a tetracycline repressor-based negative-regulatory gene circuit behaves as a WK filter. For the class of Hill-like nonlinear regulatory functions, this type of filter provides the optimal reduction in noise. Our theoretical approach can be readily combined with experimental measurements of response functions in a wide variety of genetic circuits, to elucidate the general principles by which biological networks minimize noise.

preprint2016arXiv

Phenomenological and microscopic theories for catch bonds

Lifetimes of bound states of protein complexes or biomolecule folded states typically decrease when subject to mechanical force. However, a plethora of biological systems exhibit the counter-intuitive phenomenon of catch bonding, where non-covalent bonds become stronger under externally applied forces. The quest to understand the origin of catch-bond behavior has lead to the development of phenomenological and microscopic theories that can quantitatively recapitulate experimental data. Here, we assess the successes and limitations of such theories in explaining experimental data. The most widely applied approach is a phenomenological two-state model, which fits all of the available data on a variety of complexes: actomyosin, kinetochore-microtubule, selectin-ligand, and cadherin-catenin binding to filamentous actin. With a primary focus on the selectin family of cell-adhesion complexes, we discuss the positives and negatives of phenomenological models and the importance of evaluating the physical relevance of fitting parameters. We describe a microscopic theory for selectins, which provides a structural basis for catch bonds and predicts a crucial allosteric role for residues Asn82--Glu88. We emphasize the need for new theories and simulations that can mimic experimental conditions, given the complex response of cell adhesion complexes to force and their potential role in a variety of biological contexts.

preprint2016arXiv

Protein Collapse is Encoded in the Folded State Architecture

Natural protein sequences that self-assemble to form globular structures are compact with high packing densities in the folded states. It is known that proteins unfold upon addition of denaturants, adopting random coil structures. The dependence of the radii of gyration on protein size in the folded and unfolded states obeys the same scaling laws as synthetic polymers. Thus, one might surmise that the mechanism of collapse in proteins and polymers ought to be similar. However, because the number of amino acids in single domain proteins is not significantly greater than about two hundred, it has not been resolved if the unfolded states of proteins are compact under conditions that favor the folded states - a problem at the heart of how proteins fold. By adopting a theory used to derive polymer-scaling laws, we find that the propensity for the unfolded state of a protein to be compact is universal and is encoded in the contact map of the folded state. Remarkably, analysis of over 2000 proteins shows that proteins rich in $β$-sheets have greater tendency to be compact than $α$-helical proteins. The theory provides insights into the reasons for the small size of single domain proteins and the physical basis for the origin of multi-domain proteins. Application to non-coding RNA molecules show that they have evolved to collapse sharing similarities to $β$-sheet proteins. An implication of our theory is that the evolution of natural foldable sequences is guided by the requirement that for efficient folding they should populate minimum energy compact states under folding conditions. This concept also supports the compaction selection hypothesis used to rationalize the unusually condensed states of viral RNA molecules.

preprint2016arXiv

Salt Effects on the Thermodynamics of a Frameshifting RNA Pseudoknot under Tension

Because of the potential link between -1 programmed ribosomal frameshifting and response of a pseudoknot (PK) RNA to force, a number of single molecule pulling experiments have been performed on PKs to decipher the mechanism of programmed ribosomal frameshifting. Motivated in part by these experiments, we performed simulations using a coarse-grained model of RNA to describe the response of a PK over a range of mechanical forces ($f$s) and monovalent salt concentrations ($C$s). The coarse-grained simulations quantitatively reproduce the multistep thermal melting observed in experiments, thus validating our model. The free energy changes obtained in simulations are in excellent agreement with experiments. By varying $f$ and $C$, we calculated the phase diagram that shows a sequence of structural transitions, populating distinct intermediate states. As $f$ and $C$ are changed, the stem-loop tertiary interactions rupture first, followed by unfolding of the $3^{\prime}$-end hairpin ($\textrm{I}\rightleftharpoons\textrm{F}$). Finally, the $5^{\prime}$-end hairpin unravels, producing an extended state ($\textrm{E}\rightleftharpoons\textrm{I}$). A theoretical analysis of the phase boundaries shows that the critical force for rupture scales as $\left(\log C_{\textrm{m}}\right)^α$ with $α=1\,(0.5)$ for $\textrm{E}\rightleftharpoons\textrm{I}$ ($\textrm{I}\rightleftharpoons\textrm{F}$) transition. This relation is used to obtain the preferential ion-RNA interaction coefficient, which can be quantitatively measured in single-molecule experiments, as done previously for DNA hairpins. A by-product of our work is the suggestion that the frameshift efficiency is likely determined by the stability of the $5^{\prime}$-end hairpin that the ribosome first encounters during translation.

preprint2015arXiv

Confinement-induced glassy dynamics in a model for chromosome organization

Recent experiments showing scaling of the intrachromosomal contact probability, $P(s)\sim s^{-1}$ with the genomic distance $s$, are interpreted to mean a self-similar fractal-like chromosome organization. However, scaling of $P(s)$ varies across organisms, requiring an explanation. We illustrate dynamical arrest in a highly confined space as a discriminating marker for genome organization, by modeling chromosome inside a nucleus as a homopolymer confined to a sphere of varying sizes. Brownian dynamics simulations show that the chain dynamics slows down as the polymer volume fraction ($ϕ$) inside the confinement approaches a critical value $ϕ_c$. The universal value of $ϕ_c^{\infty}\approx 0.44$ for a sufficiently long polymer ($N\gg 1$) allows us to discuss genome dynamics using $ϕ$ as a single parameter. Our study shows that the onset of glassy dynamics is the reason for the segregated chromosome organization in human ($N\approx 3\times 10^9$, $ϕ\gtrsimϕ_c^{\infty}$), whereas chromosomes of budding yeast ($N\approx 10^8$, $ϕ<ϕ_c^{\infty}$) are equilibrated with no clear signature of such organization.

preprint2015arXiv

Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model

Folding of Ubiquitin (Ub) is investigated at low and neutral pH at different temperatures using simulations of the coarse-grained Self-Organized-Polymer model with side chains. The calculated radius of gyration, showing dramatic variations with pH, is in excellent agreement with scattering experiments. At $T_m$ Ub folds in a two-state manner at low and neutral pH. Clustering analysis of the conformations sampled in equilibrium folding trajectories at $T_m$, with multiple transitions between the folded and unfolded states, show a network of metastable states connecting the native and unfolded states. At low and neutral pH, Ub folds with high probability through a preferred set of conformations resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal that Ub assembly at low pH occurs by multiple pathways involving a combination of nucleation-collapse and diffusion collision mechanism. The mechanism by which Ub folds is dictated by the stability of the key secondary structural elements responsible for establishing long range contacts and collapse of Ub. Nucleation collapse mechanism holds if the stability of these elements are marginal, as would be the case at elevated temperatures. If the lifetimes associated with these structured microdomains are on the order of hundreds of $μsec$ then Ub folding follows the diffusion-collision mechanism with intermediates many of which coincide with those found in equilibrium. Folding at neutral pH is a sequential process with a populated intermediate resembling that sampled at equilibrium. The transition state structures, obtained using a $P_{fold}$ analysis, are homogeneous and globular with most of the secondary and tertiary structures being native-like. Many of our findings are not only in agreement with experiments but also provide missing details not resolvable in standard experiments.

preprint2015arXiv

Effects of macromolecular crowding on the collapse of biopolymers

Experiments show that macromolecular crowding modestly reduces the size of intrinsically disordered proteins (IDPs) even at volume fraction ($ϕ$) similar to that in the cytosol whereas DNA undergoes a coil-to-globule transition at very small $ϕ$. We show using a combination of scaling arguments and simulations that the polymer size $\overline{R}_g(ϕ)$ depends on $x = \overline{R}_g(0)/D$ where $D$ is the $ϕ$-dependent distance between the crowders. If $x\lesssim \mathcal{O}(1)$, there is only a small decrease in $\overline{R}_g(ϕ)$ as $ϕ$ increases. When $x\gg \mathcal{O}(1)$, a cooperative coil-to-globule transition is induced. Our theory quantitatively explains a number of experiments.

preprint2015arXiv

Extracting folding landscape characteristics of biomolecules using mechanical forces

In recent years single molecule force spectroscopy has opened a new avenue to provide profiles of the complex energy landscape of biomolecules. In this field, quantitative analyses of the data employing sound theoretical models, have played a major role in interpreting data and anticipating outcomes of experiments. Here, we explain how by using temperature as a variable in mechanical unfolding of biomolecules in force spectroscopy, the roughness of the energy landscape can be measured without making any assumptions about the underlying reaction coordinate. Estimates of other aspects of the energy landscape such as free energy barriers or the transition state (TS) locations could depend on the precise model used to analyze the experimental data. We illustrate the inherent difficulties in obtaining the transition state location from loading rate or force-dependent unfolding rates. Because the transition state moves as the force or the loading rate is varied, which is reminiscent of the Hammond effect, it is in general difficult to invert the experimental data. The independence of the TS location on force holds good only for brittle or hard biomolecules whereas the TS location changes considerably if the molecule is soft or plastic. Finally, we discuss the goodness of the end-to-end distance (or pulling) coordinate of the molecule as a surrogate reaction coordinate in a situation like force-induced ligand-unbinding from a gated molecular receptor as well as force-quench refolding of an RNA hairpin.

preprint2015arXiv

Force-dependent switch in protein unfolding pathways and transition state movements

Although known that single domain proteins fold and unfold by parallel pathways, demonstration of this expectation has been difficult to establish in experiments. Unfolding rate, $k_\mathrm{u}(f)$, as a function of force $f$, obtained in single molecule pulling experiments on src SH3 domain, exhibits upward curvature on a $\log k_\mathrm{u}(f)$ plot. Similar observations were reported for other proteins for the unfolding rate $k_\mathrm{u}([C])$. These findings imply unfolding in these single domain proteins involves a switch in the pathway as $f$ or $[C]$ is increased from a low to a high value. We provide a unified theory demonstrating that if $\log k_\mathrm{u}$ as a function of a perturbation ($f$ or $[C]$) exhibits upward curvature then the underlying energy landscape must be strongly multidimensional. Using molecular simulations we provide a structural basis for the switch in the pathways and dramatic shifts in the transition state ensemble (TSE) in src SH3 domain as $f$ is increased. We show that a single point mutation shifts the upward curvature in $\log k_\mathrm{u}(f)$ to a lower force, thus establishing the malleability of the underlying folding landscape. Our theory, applicable to any perturbation that affects the free energy of the protein linearly, readily explains movement in the TSE in a $β$-sandwich (I27) protein and single chain monellin as the denaturant concentration is varied. We predict that in the force range accessible in laser optical tweezer experiments there should be a switch in the unfolding pathways in I27 or its mutants.

preprint2015arXiv

On the importance of hydrodynamic interactions in the stepping kinetics of kinesin

Conventional kinesin walks by a hand-over-hand mechanism on the microtubule (MT) by taking $\sim$ 8$nm$ discrete steps, and consumes one ATP molecule per step. The time needed to complete a single step is on the order of twenty microseconds. We show, using simulations of a coarse-grained model of the complex containing the two motor heads, the MT, and the coiled coil that in order to obtain quantitative agreement with experiments for the stepping kinetics hydrodynamic interactions (HI) have to be included. In simulations without hydrodynamic interactions spanning nearly twenty $μ$s not a single step was completed in hundred trajectories. In sharp contrast, nearly 14\% of the steps reached the target binding site within 6$μ$s when HI were included. Somewhat surprisingly, there are qualitative differences in the diffusion pathways in simulations with and without HI. The extent of movement of the trailing head of kinesin on the MT during the diffusion stage of stepping is considerably greater in simulations with HI than in those without HI. Our results suggest that inclusion of HI is crucial in the accurate description of motility of other motors as well.

preprint2015arXiv

Unexpected swelling of stiff DNA in a polydisperse crowded environment

We investigate the conformations of DNA-like stiff chains, characterized by contour length ($L$) and persistence length ($l_p$), in a variety of crowded environments containing mono disperse soft spherical (SS) and spherocylindrical (SC) particles, mixture of SS and SC, and a milieu mimicking the composition of proteins in $E. coli.$ cytoplasm. The stiff chain, whose size modestly increases in SS crowders up to $ϕ\approx 0.1$, is considerably more compact at low volume fractions ($ϕ\leq 0.2$) in monodisperse SC particles than in a medium containing SS particles. A 1:1 mixture of SS and SC crowders induces greater chain compaction than the pure SS or SC crowders at the same $ϕ$ with the effect being highly non-additive. We also discover a counter-intuitive result that polydisperse crowding environment, mimicking the composition of a cell lysate, swells the DNA-like polymer, which is in stark contrast to the size reduction of flexible polymer in the same milieu. Trapping of the stiff chain in a fluctuating tube-like environment created by large-sized crowders explains the dramatic increase in size and persistence length of the stiff chain. In the polydisperse medium, mimicking the cellular environment, the size of the DNA (or related RNA) is determined by $L/l_p$. At low $L/l_p$ the size of the polymer is unaffected whereas there is a dramatic swelling at intermediate value of $L/l_p$. We use these results to provide insights into recent experiments on crowding effects on RNA, and also make testable predictions.

preprint2014arXiv

Cellular signaling networks function as generalized Wiener-Kolmogorov filters to suppress noise

Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov (WK) optimal noise filter. Using concepts from umbral calculus, we generalize the linear WK theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function---like ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways, and the manipulation of pathways through experimental probes like oscillatory input.

preprint2014arXiv

Development and applications of Coarse Grained models for RNA

In contrast to proteins much less attention has been focused on development of computational models for describing RNA molecules, which are being recognized as playing key roles in many cellular functions. Current atomically detailed force fields are not accurate enough to capture the properties of even simple nucleic acid constructs. In this article, we review our efforts to develop coarse-grained (CG) models that capture the underlying physics for the particular length scale of interest. Two models are discussed. One of them is the Three Interaction Site (TIS) model in which each nucleotide is represented by three beads corresponding to sugar, phosphate, and base. The other is the Self-Organized Polymer (SOP) model in which each nucleotide is represented as a single interaction center. Applications of the TIS model to study the complexity of hairpin formation and the effects of crowding in shifting equilibrium between two conformations in human telomerase pseudoknot are described. The work on crowding illustrates a direct link to the activity of telomerase. We use the SOP model to describe the response of {\it Tetrahymena} ribozyme to force. The simulated unfolding pathways agree well with single molecule pulling experiments. We also review predictions for the unfolding pathways for {\it Azoarcus} ribozyme. The success of the CG applications to describe dynamics in RNA gives hope that more complex processes involving RNA-protein interactions can be tackled using variants of the proposed models.

preprint2014arXiv

Dynamical Transition and Heterogeneous Hydration Dynamics in RNA

Enhanced dynamical fluctuations of RNAs, facilitated by a network of water molecules with strong interactions with RNA, are suspected to be critical in their ability to respond to a variety of cellular signals. Using atomically detailed molecular dynamics simulations at various temperatures of purine (adenine)- and preQ$_1$ sensing riboswitch aptamers, we show that water molecules in the vicinity of RNAs undergo complex dynamics depending on the local structures of the RNAs. The overall lifetimes of hydrogen bonds (HBs) of surface bound waters are more than at least 1-2 orders of magnitude longer than bulk water. Slow hydration dynamics, revealed in non-Arrhenius behavior of the relaxation time, arises from high activation barriers to break water hydrogen bonds with a nucleotide and by reduced diffusion of water. The relaxation kinetics at specific locations in the two RNAs show a broad spectrum of time scales reminiscent of glass-like behavior, suggesting that the hydration dynamics is highly heterogeneous. Both RNAs undergo dynamic transition at $T = T_D \gtrsim 200$ K as assessed by the mean square fluctuation of hydrogen atoms $\langle x^2\rangle$, which undergoes an abrupt harmonic-to-anharmonic transition at $T_D$. The near universal value of $T_D$ found for these RNAs and previously for tRNA is strongly correlated with changes in hydration dynamics as $T$ is altered. Hierarchical dynamics of waters associated with the RNA surface, revealed in the motions of distinct classes of water with well-separated time scales, reflects the heterogeneous local environment on the molecular surface of RNA. At low temperatures slow water dynamics predominates over structural transitions. Our study demonstrates that the complex interplay of dynamics between water and local environment in the RNA structures could be a key determinant of the functional activities of RNA.

preprint2014arXiv

Entropy and enthalpy of interaction between amino acid side chains in nanopores

Understanding the stabilities of proteins in nanopores requires a quantitative description of confinement induced interactions between amino acid side chains. We use molecular dynamics simulations to study the nature of interactions between the side chain pairs ALA-PHE, SER-ASN and LYS-GLU in bulk water and in water-filled nanopores. The temperature dependence of the bulk solvent potentials of mean force and the interaction free energies in cylindrical and spherical nanopores is used to identify the corresponding entropic and enthalpic components. The entropically stabilized hydrophobic interaction between ALA and PHE in bulk water is enthalpically dominated upon confinement depending on the relative orientations between the side chains. In the case of SER-ASN, hydrogen bonded configurations that are similar in bulk water are thermodynamically distinct in a cylindrical pore, thus making rotamer distributions different from those in the bulk. Remarkably, salt bridge formation between LYS-GLU is stabilized by entropy in contrast to the bulk. Implications of our findings for confinement-induced alterations in protein stability are briefly outlined.

preprint2014arXiv

Membrane-protein interactions hold the key to understanding amyloid formation

In this perspective we describe the critical role membranes play in modulating the structures of the Amyloid Precursor Proteins to produce the peptides involved in the Alzheimer's disease. Some of the key concepts related to protein aggregation including the potential role of the excited states of monomers in initiating protein aggregation are described.

preprint2014arXiv

Plasticity of hydrogen bond networks regulates mechanochemistry of cell adhesion complexes

Mechanical forces acting on cell adhesion receptor proteins regulate a range of cellular functions by formation and rupture of non-covalent interactions with ligands. Typically, force decreases the lifetimes of intact complexes (slip-bonds), making the discovery that these lifetimes can also be prolonged ("catch-bonds"), a surprise. We created a microscopic analytic theory by incorporating the structures of selectin and integrin receptors into a conceptual framework based on the theory of stochastic equations, which quantitatively explains a wide range of experimental data (including catch-bonds at low forces and slip-bonds at high forces). Catch-bonds arise due to force-induced remodeling of hydrogen bond networks, a finding that also accounts for unbinding in structurally unrelated integrin-fibronectin and actomyosin complexes. For the selectin family, remodeling of hydrogen bond networks drives an allosteric transition resulting in the formation of maximum number of hydrogen bonds determined only by the structure of the receptor and is independent of the ligand. A similar transition allows us to predict the increase in number of hydrogen bonds in a particular allosteric state of $α_5 β_1$ integrin-fibronectin complex, a conformation which is yet to be crystallized. We also make a testable prediction that a single point mutation (Tyr51Phe) in the ligand associated with selectin should dramatically alter the nature of the catch-bond compared to the wild type. Our work suggests that nature utilizes a ductile network of hydrogen bonds to engineer function over a broad range of forces.

preprint2014arXiv

Propensity to form amyloid fibrils is encoded as excitations in the free energy landscape of monomeric proteins

Protein aggregation, linked to many of diseases, is initiated when monomers access rogue conformations that are poised to form amyloid fibrils. We show, using simulations of src SH3 domain, that mechanical force enhances the population of the aggregation prone ($N^*$) states, which are rarely populated under force free native conditions, but are encoded in the spectrum of native fluctuations. The folding phase diagrams of SH3 as a function of denaturant concentration ($[C]$), mechanical force ($f$), and temperature exhibit an apparent two-state behavior, without revealing the presence of the elusive $N^*$ states. Interestingly, the phase boundaries separating the folded and unfolded states at all [C] and $f$ fall on a master curve, which can can be quantitatively described using an analogy to superconductors in a magnetic field. The free energy profiles as a function of the molecular extension ($R$), which are accessible in pulling experiments, ($R$), reveal the presence of a native-like $N^*$ with a disordered solvent-exposed amino terminal $β$-strand. The structure of the $N^*$ state is identical to that found in Fyn SH3 by NMR dispersion experiments. We show that the time scale for fibril formation can be estimated from the population of the $N^*$ state, determined by the free energy gap separating the native structure and the $N^*$ state, a finding that can be used to assess fibril forming tendencies of proteins. The structures of the $N^*$ state are used to show that oligomer formation and likely route to fibrils occur by a domain-swap mechanism in SH3 domain.

preprint2014arXiv

Random First Order Theory concepts in Biology and Condensed Matter physics

The routine transformation of a liquid, as it is cooled rapidly, resulting in glass formation, is remarkably complex. A theoretical explanation of the dynamics associated with this process has remained one of the major unsolved problems in condensed matter physics. The Random First Order Transition (RFOT) theory, which was proposed over twenty five years ago, provides a theoretical basis for explaining much of the phenomena associated with glass forming materials. It links or relates multiple metastable states, slow or glassy dynamics, dynamic heterogeneity, and both a dynamical and an ideal glass transition. Remarkably, the major concepts in the RFOT theory can also be profitably used to understand many spectacular phenomena in biology and condensed matter physics, as we illustrate here. The presence of a large number of metastable states and the dynamics in such complex landscapes in biological systems from molecular to cellular scale and beyond leads to behavior, which is amenable to descriptions based on the RFOT theory. Somewhat surprisingly even intratumor heterogeneity arising from variations in cancer metastasis in different cells is hauntingly similar to glassy systems. There are also deep connections between glass physics and electronically disordered systems undergoing a metal-insulator transition, aging effects in which quantum effects play a role, and the physics of super glasses (a phase that is simultaneously a super fluid and a frozen amorphous structure). We argue that the common aspect in all these diverse phenomena is that multiple symmetry unrelated states governing both the equilibrium and dynamical behavior - a lynchpin in the RFOT theory - controls the behavior observed in these unrelated systems.

preprint2014arXiv

Universal relations in the self-assembly of proteins and RNA

Concepts rooted in physics are becoming increasingly important in biology as we transition to an era in which quantitative descriptions of all processes from molecular to cellular level are needed. In this essay I discuss two unexpected findings of universal behavior, uncommon in biology, in the self-assembly of proteins and RNA. These findings, which are surprising, reveal that physics ideas applied to biological problems ranging from folding to gene expression to cellular movement and communication between cells might lead to discovery of universal principles operating in adoptable living systems.

preprint2013arXiv

A Coarse-Grained Model for Predicting RNA Folding Thermodynamics

We present a thermodynamically robust coarse-grained model to simulate folding of RNA in monovalent salt solutions. The model includes stacking, hydrogen bond and electrostatic interactions as fundamental components in describing the stability of RNA structures. The stacking interactions are parametrized using a set of nucleotide-specific parameters, which were calibrated against the thermodynamic measurements for single-base stacks and base-pair stacks. All hydrogen bonds are assumed to have the same strength, regardless of their context in the RNA structure. The ionic buffer is modeled implicitly, using the concept of counterion condensation and the Debye-Hückel theory. The three adjustable parameters in the model were determined by fitting the experimental data for two RNA hairpins and a pseudoknot. A single set of parameters provides good agreement with thermodynamic data for the three RNA molecules over a wide range of temperatures and salt concentrations. In the process of calibrating the model, we establish the extent of counterion condensation onto the single-stranded RNA backbone. The reduced backbone charge is independent of the ionic strength and is 60% of the RNA bare charge at 37 degrees Celsius. Our model can be used to predict the folding thermodynamics for any RNA molecule in the presence of monovalent ions.

preprint2013arXiv

Design principles governing the motility of myosin V

The molecular motor myosin V exhibits a wide repertoire of pathways during the stepping process, which is intimately connected to its biological function. The best understood of these is hand-over-hand stepping by a swinging lever arm movement toward the plus-end of actin filaments, essential to its role as a cellular transporter. However, single-molecule experiments have also shown that the motor "foot stomps", with one hand detaching and rebinding to the same site, and backsteps under sufficient load. Explaining the complete taxonomy of myosin V's load-dependent stepping pathways, and the extent to which these are constrained by motor structure and mechanochemistry, are still open questions. Starting from a polymer model, we develop an analytical theory to understand the minimal physical properties that govern motor dynamics. In particular, we solve the first-passage problem of the head reaching the target binding site, investigating the competing effects of load pulling back at the motor, strain in the leading head that biases the diffusion in the direction of the target, and the possibility of preferential binding to the forward site due to the recovery stroke. The theory reproduces a variety of experimental data, including the power stroke and slow diffusive search regimes in the mean trajectory of the detached head, and the force dependence of the forward-to-backward step ratio, run length, and velocity. The analytical approach yields a formula for the stall force, identifying the relative contributions of the chemical cycle rates and mechanical features like the bending rigidities of the lever arms. Most importantly, by fully exploring the design space of the motor, we predict that myosin V is a robust motor whose dynamical behavior is not compromised by reasonable perturbations to the reaction cycle, and changes in the architecture of the lever arm.

preprint2013arXiv

Entropic stabilization of the folded states of RNA due to macromolecular crowding

We review the effects of macromolecular crowding on the folding of RNA by considering the simplest scenario when excluded volume interactions between crowding particles and RNA dominate. Using human telomerase enzyme as an example, we discuss how crowding can alter the equilibrium between pseudoknot and hairpin states of the same RNA molecule - a key aspect of crowder-RNA interactions. We summarize data showing that the crowding effect is significant only if the size of the spherical crowding particle is smaller than the radius of gyration of the RNA in the absence of crowding particles. The implication for function of the wild type and mutants of human telomerase is outlined by using a relationship between enzyme activity and its conformational equilibrium. In addition, we discuss the interplay between macromolecular crowding and ionic strength of the RNA buffer. Finally, we briefly review recent experiments which illustrate the connection between excluded volume due to macromolecular crowding and the thermodynamics of RNA folding.

preprint2013arXiv

Force-Induced Unzipping Transitions in an Athermal Crowded Environment

Using theoretical arguments and extensive Monte Carlo (MC) simulations of a coarse-grained three-dimensional off-lattice model of a β-hairpin, we demonstrate that the equilibrium critical force, $F_c$, needed to unfold the biopolymer increases non-linearly with increasing volume fraction occupied by the spherical macromolecular crowding agent. Both scaling arguments and MC simulations show that the critical force increases as $F_c \approx φ_c^α$. The exponent $α$ is linked to the Flory exponent relating the size of the unfolded state of the biopolymer and the number of amino acids. The predicted power law dependence is confirmed in simulations of the dependence of the isothermal extensibility and the fraction of native contacts on $φ_c$. We also show using MC simulations that $F_c$ is linearly dependent on the average osmotic pressure ($\mathrm{P}$) exerted by the crowding agents on the β-hairpin. The highly significant linear correlation coefficient of 0.99657 between $F_c$ and $\mathrm{P}$ makes it straightforward to predict the dependence of the critical force on the density of crowders. Our predictions are amenable to experimental verification using Laser Optical Tweezers.

preprint2013arXiv

From mechanical folding trajectories to intrinsic energy landscapes of biopolymers

In single molecule laser optical tweezer (LOT) pulling experiments a protein or RNA is juxtaposed between DNA handles that are attached to beads in optical traps. The LOT generates folding trajectories under force in terms of time-dependent changes in the distance between the beads. How to construct the full intrinsic folding landscape (without the handles and the beads) from the measured time series is a major unsolved problem. By using rigorous theoretical methods---which account for fluctuations of the DNA handles, rotation of the optical beads, variations in applied tension due to finite trap stiffness, as well as environmental noise and the limited bandwidth of the apparatus---we provide a tractable method to derive intrinsic free energy profiles. We validate the method by showing that the exactly calculable intrinsic free energy profile for a Generalized Rouse Model, which mimics the two-state behavior in nucleic acid hairpins, can be accurately extracted from simulated time series in a LOT setup regardless of the stiffness of the handles. We next apply the approach to trajectories from coarse grained LOT molecular simulations of a coiled-coil protein based on the GCN4 leucine zipper, and obtain a free energy landscape that is in quantitative agreement with simulations performed without the beads and handles. Finally, we extract the intrinsic free energy landscape from experimental LOT measurements for the leucine zipper, which is independent of the trap parameters.

preprint2013arXiv

Manifestation of Random First Order Transition theory in Wigner glasses

We use Brownian dynamics simulations of a binary mixture of highly charged spherical colloidal particles to illustrate many of the implications of the Random First Order Transition (RFOT) theory (PRA 40 1045 (1989)), which is the only theory that provides a unified description of both the statics and dynamics of the liquid to glass transition. In accord with the RFOT, we find that as the volume fraction of the colloidal particles \f, the natural variable that controls glass formation in colloidal systems, approaches \f_A there is an effective ergodic to non-ergodic dynamical transition, which is signalled by a dramatic slowing down of diffusion. In addition, using the energy metric we show that the system becomes non-ergodic as \f_A is approached. The time t^*, at which the four-point dynamical susceptibility achieves a maximum, also diverges near \f_A. Remarkably, three independent measures(translational diffusion coefficients, ergodic diffusion coefficients,as well t^*) all signal that at \f_A=0.1 ergodicity is effectively broken. The translation diffusion constant, the ergodic diffusion constant, and (t^*)^-1 all vanish as (\f_A-\f)^g with both \f_A and g being the roughly the same for all three quantities. Below \f_A transport involves crossing suitable free energy barriers. In this regime, the density-density correlation function decays as a stretched exponential exp(-t/tau_a)^b with b=0.45. The \f-dependence of the relaxation time τ_a is well fit using the VFT law with the ideal glass transition occurring at \f_K=0.47. By using an approximate measure of the local entropy (s_3) we show that below \f_A the law of large numbers, which states that the distribution of s_3 for a large subsample should be identical to the whole sample, is not obeyed. The comprehensive analyses provided here for Wigner glass forming charged colloidal suspensions fully validate the concepts of the RFOT.

preprint2012arXiv

Chain Length Determines the Folding Rates of RNA

We show that the folding rates (k_F) of RNA are determined by N, the number of nucleotides. By assuming that the distribution of free energy barriers separating the folded and the unfolded states is Gaussian, which follows from central limit theorem arguments and polymer physics concepts, we show that k_F ~ k_0 exp(-alpha N^0.5). Remarkably, the theory fits the experimental rates spanning over seven orders of magnitude with k_0 ~ 1.0 (microsec)^{-1}. An immediate consequence of our finding is that the speed limit of RNA folding is about one microsecond just as it is in the folding of globular proteins.

preprint2012arXiv

Exact solution of the Zwanzig-Lauritzen model of Polymer Crystallization under Tension

We solve a two dimensional model for polymer chain folding in the presence of mechanical pulling force ($f$) exactly using equilibrium statistical mechanics. Using analytically derived expression for the partition function we determine the phase diagram for the model in the $f$-temperature ($T$) plane. A square root singularity in the susceptibility indicates a second order phase transition from a folded to an unfolded state at a critical force ($f_c$) in the thermodynamic limit of infinitely long polymer chain. Surprisingly, the temperature dependence of $f_c$ shows a reentrant phase transition, which is reflected in an increase in $f_c$ as $T$ increases below a threshold value. For a range of $f$ values, the unfolded state is stable at both low and high temperatures. The high temperature unfolded state is stabilized by entropy whereas the low temperature unfolded state is dominated by favorable energy. The exact calculation could serve as a bench mark for testing approximate theories that are used in analyzing single molecule pulling experiments.

preprint2012arXiv

Gene Regulation by Riboswitches with and without Negative Feedback Loop

Riboswitches, structured elements in the untranslated regions of messenger RNAs, regulate gene expression by binding specific metabolites. We introduce a kinetic network model that describes the functions of riboswitches at the systems level. Using experimental data for flavin mono nucleotide riboswitch as a guide we show that efficient function, implying a large dynamic range without compromising the requirement to suppress transcription, is determined by a balance between the transcription speed, the folding and unfolding rates of the aptamer, and the binding rates of the metabolite. We also investigated the effect of negative feedback accounting for binding to metabolites, which are themselves the products of genes that are being regulated. For a range of transcription rates negative feedback suppresses gene expression by nearly 10 fold. Negative feedback speeds the gene expression response time, and suppresses the change of steady state protein concentration by half relative to that without feedback, when there is a modest spike in DNA concentration. A dynamic phase diagram expressed in terms of transcription speed, folding rates, and metabolite binding rates predicts different scenarios in riboswitch-mediated transcription regulation.

preprint2012arXiv

Hidden Complexity in the Isomerization Dynamics of Holliday Junctions

A plausible consequence of rugged energy landscapes of biomolecules is that functionally competent folded states may not be unique, as is generally assumed. Indeed, molecule-to-molecule variations in the dynamics of enzymes and ribozymes under folding conditions have recently been identified in single molecule experiments. However, systematic quantification and the structural origin of the observed complex behavior remain elusive. Even for a relatively simple case of isomerization dynamics in Holliday Junctions (HJs), molecular heterogeneities persist over a long observation time (Tobs ~ 40 sec). Here, using concepts in glass physics and complementary clustering analysis, we provide a quantitative method to analyze the smFRET data probing the isomerization in HJ dynamics. We show that ergodicity of HJ dynamics is effectively broken; as a result, the conformational space of HJs is partitioned into a folding network of kinetically disconnected clusters. While isomerization dynamics in each cluster occurs rapidly as if the associated conformational space is fully sampled, distinct patterns of time series belonging to different clusters do not interconvert on Tobs. Theory suggests that persistent heterogeneity of HJ dynamics is a consequence of internal multiloops with varying sizes and flexibilities frozen by Mg2+ ions. An annealing experiment using Mg2+ pulse that changes the Mg2+ cocentration from high to low to high values lends support to this idea by explicitly showing that interconversions can be driven among trajectories with different patterns.

preprint2012arXiv

Multiple barriers in forced rupture of protein complexes

Curvatures in the most probable rupture force ($f^*$) versus log-loading rate ($\log{r_f}$) observed in dynamic force spectroscopy (DFS) on biomolecular complexes are interpreted using a one-dimensional free energy profile with multiple barriers or a single barrier with force-dependent transition state. Here, we provide a criterion to select one scenario over another. If the rupture dynamics occurs by crossing a single barrier in a physical free energy profile describing unbinding, the exponent $ν$, from $(1- f^*/f_c)^{1/ν}\sim(\log r_f)$ with $f_c$ being a critical force in the absence of force, is restricted to $0.5 \leq ν\leq 1$. For biotin-ligand complexes and leukocyte-associated antigen-1 bound to intercellular adhesion molecules, which display large curvature in the DFS data, fits to experimental data yield $ν<0.5$, suggesting that ligand unbinding is associated with multiple-barrier crossing.

preprint2012arXiv

On the origin of the unusual behavior in the stretching of single-stranded DNA

Force extension curves (FECs), which quantify the response of a variety of biomolecules subject to mechanical force ($f$), are often quantitatively fit using worm-like chain (WLC) or freely-jointed chain (FJC) models. These models predict that the chain extension, $x$, normalized by the contour length increases linearly at small $f$ and at high forces scale as $x \sim (1 - f^{-α})$ where $α$= 0.5 for WLC and unity for FJC. In contrast, experiments on ssDNA show that over a range of $f$ and ionic concentration, $x$ scales as $x\sim\ln f$, which cannot be explained using WLC or FJC models. Using theory and simulations we show that this unusual behavior in FEC in ssDNA is due to sequence-independent polyelectrolyte effects. We show that the $x\sim \ln f$ arises because in the absence of force the tangent correlation function, quantifying chain persistence, decays algebraically on length scales on the order of the Debye length. Our theory, which is most appropriate for monovalent salts, quantitatively fits the experimental data and further predicts that such a regime is not discernible in double stranded DNA.

preprint2012arXiv

RNA under Tension: Folding Landscapes, Kinetic Partitioning Mechanism, and Molecular Tensegrity

Non-coding RNA sequences play a great role in controlling a number of cellular functions, thus raising the need to understand their complex conformational dynamics in quantitative detail. In this perspective, we first show that single molecule pulling experiments when combined with with theory and simulations can be used to quantitatively explore the folding landscape of nucleic acid hairpins, and riboswitches with tertiary interactions. Applications to riboswitches, which are non-coding RNA elements that control gene expression by undergoing dynamical conformational changes in response to binding of metabolites, lead to an organization principle that assembly of RNA is determined by the stability of isolated helices. We also point out the limitations of single molecule pulling experiments, with molecular extension as the only accessible parameter, in extracting key parameters of the folding landscapes of RNA molecules.

preprint2011arXiv

Capturing the essence of folding and functions of biomolecules using Coarse-Grained Models

The distances over which biological molecules and their complexes can function range from a few nanometres, in the case of folded structures, to millimetres, for example during chromosome organization. Describing phenomena that cover such diverse length, and also time scales, requires models that capture the underlying physics for the particular length scale of interest. Theoretical ideas, in particular, concepts from polymer physics, have guided the development of coarse-grained models to study folding of DNA, RNA, and proteins. More recently, such models and their variants have been applied to the functions of biological nanomachines. Simulations using coarse-grained models are now poised to address a wide range of problems in biology.

preprint2011arXiv

Compaction and tensile forces determine the accuracy of folding landscape parameters from single molecule pulling experiments

We establish a framework for assessing whether the transition state location of a biopolymer, which can be inferred from single molecule pulling experiments, corresponds to the ensemble of structures that have equal probability of reaching either the folded or unfolded states (Pfold = 0.5). Using results for the forced-unfolding of a RNA hairpin, an exactly soluble model and an analytic theory, we show that Pfold is solely determined by s, an experimentally measurable molecular tensegrity parameter, which is a ratio of the tensile force and a compaction force that stabilizes the folded state. Applications to folding landscapes of DNA hairpins and leucine zipper with two barriers provide a structural interpretation of single molecule experimental data. Our theory can be used to assess whether molecular extension is a good reaction coordinate using measured free energy profiles.

preprint2011arXiv

Crowding Promotes the Switch from Hairpin to Pseudoknot Conformation in Human Telomerase RNA

Formation of a pseudoknot in the conserved RNA core domain in the ribonucleoprotein human telomerase is required for function. In vitro experiments show that the pseudoknot (PK) is in equilibrium with an extended hairpin (HP) structure. We use molecular simulations of a coarse-grained model, which reproduces most of the salient features of the experimental melting profiles of PK and HP, to show that crowding enhances the stability of PK relative to HP in the wild type and in a mutant associated with dyskeratosis congenita. In monodisperse suspensions, small crowding particles increase the stability of compact structures to a greater extent than larger crowders. If the sizes of crowders in a binary mixture are smaller than the unfolded RNA, the increase in melting temperature due to the two components is additive. In a ternary mixture of crowders that are larger than the unfolded RNA, which mimics the composition of ribosome, large enzyme complexes and proteins in E. coli, the marginal increase in stability is entirely determined by the smallest component. We predict that crowding can restore partially telomerase activity in mutants, which dramatically decrease the PK stability.

preprint2011arXiv

Entropic Stabilization of Proteins by TMAO

To understand the mechanism of trimethylamine N-oxide (TMAO) induced stabilization of folded protein states, we systematically investigated the action of TMAO on several model dipeptides (Leucine, L2, Serine, S2, Glutamine, Q2, Lysine, K2, and Glycine, G2) in order to elucidate the effect of residue-specific TMAO interactions on small fragments of solvent-exposed conformations of the denatured states of proteins. We find that TMAO preferentially hydrogen bonds with the exposed dipeptide backbone, but generally not with nonpolar or polar side chains. However, interactions with the positively charged Lys are substantially greater than with the backbone. The dipeptide G2, is a useful model of pure amide backbone, interacts with TMAO by forming a hydrogen bond between the amide nitrogen and the oxygen in TMAO. In contrast, TMAO is depleted from the protein backbone in the hexapeptide G6, which shows that the length of the polypeptide chain is relevant in aqueous TMAO solutions. These simulations lead to the hypothesis that TMAO-induced stabilization of proteins and peptides is a consequence of depletion of the solute from the protein surface provided intramolecular interactions are more favorable than those between TMAO and the backbone. To test our hypothesis we performed additional simulations of the action of TMAO on an intrinsically disordered Aβ16-22 (KLVFFAE) monomer. In the absence of TMAO Aβ16-22 is a disordered random coil. However, in aqueous TMAO solution Aβ16-22 monomer samples compact conformations. A transition from random coil to α-helical secondary structure is observed at high TMAO concentrations. Our work highlights the potential similarities between the action of TMAO on long polypeptide chains and entropic stabilization of proteins in a crowded environment due to excluded volume interactions. In this sense TMAO is a nano-crowding particle.

preprint2011arXiv

Hydrophobic and ionic-interactions in bulk and confined water with implications for collapse and folding of proteins

Water and water-mediated interactions determine thermodynamic and kinetics of protein folding, protein aggregation and self-assembly in confined spaces. To obtain insights into the role of water in the context of folding problems, we describe computer simulations of a few related model systems. The dynamics of collapse of eicosane shows that upon expulsion of water the linear hydrocarbon chain adopts an ordered helical hairpin structure with 1.5 turns. The structure of dimer of eicosane molecules has two well ordered helical hairpins that are stacked perpendicular to each other. As a prelude to studying folding in confined spaces we used simulations to understand changes in hydrophobic and ionic interactions in nano droplets. Solvation of hydrophobic and charged species change drastically in nano water droplets. Hydrophobic species are localized at the boundary. The tendency of ions to be at the boundary where water density is low increases as the charge density decreases. Interaction between hydrophobic, polar, and charged residue are also profoundly altered in confined spaces. Using the results of computer simulations and accounting for loss of chain entropy upon confinement we argue and then demonstrate, using simulations in explicit water, that ordered states of generic amphiphilic peptide sequences should be stabilized in cylindrical nanopores.

preprint2011arXiv

Influence of Nanoparticle Size and Shape on Oligomer Formation of an Amyloidogenic Peptide

Understanding the influence of macromolecular crowding and nanoparticles on the formation of in-register $β$-sheets, the primary structural component of amyloid fibrils, is a first step towards describing \emph{in vivo} protein aggregation and interactions between synthetic materials and proteins. Using all atom molecular simulations in implicit solvent we illustrate the effects of nanoparticle size, shape, and volume fraction on oligomer formation of an amyloidogenic peptide from the transthyretin protein. Surprisingly, we find that inert spherical crowding particles destabilize in-register $β$-sheets formed by dimers while stabilizing $β$-sheets comprised of trimers and tetramers. As the radius of the nanoparticle increases crowding effects decrease, implying smaller crowding particles have the largest influence on the earliest amyloid species. We explain these results using a theory based on the depletion effect. Finally, we show that spherocylindrical crowders destabilize the ordered $β$-sheet dimer to a greater extent than spherical crowders, which underscores the influence of nanoparticle shape on protein aggregation.

preprint2011arXiv

Polyelectrolyte and polyampholyte effects in synthetic and biological macromolecules

The nature of electrostatic interactions involving polyanions modulate the properties of both synthetic and biological macromolecules. Although intensely studied for decades the interplay of many length scales has prevented a complete resolution of some of the basic questions such as how the electrostatic persistence length ($l_e$) varies with ionic strength ($I$). In this review we describe certain characteristics of polyelectrolytes (PAs) and polyampholytes (PAs), which are polymers whose monomers have a random distribution of opposite charges. After reviewing the current theoretical understanding of the dependence of $l_e$ on $I$ we present experimental data that conform to two distinct behavior. For RNA and DNA it is found that that $l_e \sim I^{-1}$ whereas for some proteins and other polyelectrolytes $l_e \sim i^{-1/2}$. A scaling type theory, which delineates charge correlation and pure polyelectrolyte effects for the shape of PAs that is valid over a wide range of salt concentration is described. We also use theory and simulations to argue that the distinct stages in the kinetics of collapse of PAs (with a net charge that is small enough to induce globule formation) and PEs (relevant for RNA folding) are similar. In both cases the major initial conformation change involves formation of metastable pearl-necklace structures. In the coarsening process large clusters (pearls) grow at the expense of smaller ones by a process that is reminiscent of Lifshitz-Slyozov mechanism. Finally, recent theories and single molecule experiments on stretching of single stranded DNA and PEs further sheds insights into the complex behavior of charged macromolecules. The survey, which is limited to very few topics, shows the importance of polyelectrolyte effects in a wide range of disciplines.

preprint2011arXiv

Role of water in Protein Aggregation and Amyloid Polymorphism

A variety of neurodegenerative diseases are associated with the formation of amyloid plaques. Our incomplete understanding of this process underscores the need to decipher the principles governing protein aggregation. Most experimental and simulation studies have been interpreted largely from the perspective of proteins: the role of solvent has been relatively overlooked. In this Account, we provide a perspective on how interactions with water affect folding landscapes of A$β$ monomers, A$β_{16-22}$ oligomer formation, and protofilament formation in a Sup35 peptide. Simulations show that the formation of aggregation-prone structures (N$^*$) similar to the structure in the fibril requires overcoming high desolvation barrier. The mechanism of protofilament formation in a polar Sup35 peptide fragment illustrates that water dramatically slows down self-assembly. Release of water trapped in the pores as water wires creates protofilament with a dry interface. Similarly, one of the main driving force for addition of a solvated monomer to a preformed fibril is the entropy gain of released water. We conclude by postulating that two-step model for protein crystallization must also hold for higher order amyloid structure formation starting from N$^*$. Multiple N$^*$ structures with varying water content results in a number of distinct water-laden polymorphic structures. In predominantly hydrophobic sequences, water accelerates fibril formation. In contrast, water-stabilized metastable intermediates dramatically slow down fibril growth rates in hydrophilic sequences.

preprint2010arXiv

Determination of factors governing fibrillogenesis of polypeptide chains using lattice models

Using lattice models we explore the factors that determine the tendencies of polypeptide chains to aggregate by exhaustively sampling the sequence and conformational space. The morphologies of the fibril-like structures and the time scales ($τ_{fib}$) for their formation depend on a subtle balance between hydrophobic and coulomb interactions. The extent of population of a fibril-prone structure in the spectrum of monomer conformations is the major determinant of $τ_{fib}$. This observation is used to determine the aggregation-prone consensus sequences by exhaustively exploring the sequence space. Our results provide a basis for genome wide search of fragments that are aggregation prone.

preprint2010arXiv

Factors governing fibrillogenesis of polypeptide chains

Using lattice models we explore the factors that determine the tendencies of polypeptide chains to aggregate by exhaustively sampling the sequence and conformational space. The morphologies of the fibril-like structures and the time scales ($τ_{fib}$) for their formation depend on a balance between hydrophobic and coulomb interactions. The extent of population of an ensemble of \textbf{N$^*$} structures, which are fibril-prone structures in the spectrum of conformations of an isolated protein, is the major determinant of $τ_{fib}$. This observation is used to determine the aggregating sequences by exhaustively exploring the sequence space, thus providing a basis for genome wide search of fragments that are aggregation prone.

preprint2010arXiv

Theoretical Perspectives on Protein Folding

Understanding how monomeric proteins fold under in vitro conditions is crucial to describing their functions in the cellular context. Significant advances both in theory and experiments have resulted in a conceptual framework for describing the folding mechanisms of globular proteins. The experimental data and theoretical methods have revealed the multifaceted character of proteins. Proteins exhibit universal features that can be determined using only the number of amino acid residues (N) and polymer concepts. The sizes of proteins in the denatured and folded states, cooperativity of the folding transition, dispersions in the melting temperatures at the residue level, and time scales of folding are to a large extent determined by N. The consequences of finite N especially on how individual residues order upon folding depends on the topology of the folded states. Such intricate details can be predicted using the Molecular Transfer Model that combines simulations with measured transfer free energies of protein building blocks from water to the desired concentration of the denaturant. By watching one molecule fold at a time, using single molecule methods, the validity of the theoretically anticipated heterogeneity in the folding routes, and the N-dependent time scales for the three stages in the approach to the native state have been established. Despite the successes of theory, of which only a few examples are documented here, we conclude that much remains to be done to solve the "protein folding problem" in the broadest sense.

preprint2009arXiv

Refolding dynamics of stretched biopolymers upon force quench

Single molecule force spectroscopy methods can be used to generate folding trajectories of biopolymers from arbitrary regions of the folding landscape. We illustrate the complexity of the folding kinetics and generic aspects of the collapse of RNA and proteins upon force quench, using simulations of an RNA hairpin and theory based on the de Gennes model for homopolymer collapse. The folding time, $τ_F$, depends asymmetrically on $δf_S = f_S - f_m$ and $δf_Q = f_m - f_Q$ where $f_S$ ($f_Q$) is the stretch (quench) force, and $f_m$ is the transition mid-force of the RNA hairpin. In accord with experiments, the relaxation kinetics of the molecular extension, $R(t)$, occurs in three stages: a rapid initial decrease in the extension is followed by a plateau, and finally an abrupt reduction in $R(t)$ that occurs as the native state is approached. The duration of the plateau increases as $λ=τ_Q/τ_F$ decreases (where $τ_Q$ is the time in which the force is reduced from $f_S$ to $f_Q$). Variations in the mechanisms of force quench relaxation as $λ$ is altered are reflected in the experimentally measurable time-dependent entropy, which is computed directly from the folding trajectories. An analytical solution of the de Gennes model under tension reproduces the multistage stage kinetics in $R(t)$. The prediction that the initial stages of collapse should also be a generic feature of polymers is validated by simulation of the kinetics of toroid (globule) formation in semiflexible (flexible) homopolymers in poor solvents upon quenching the force from a fully stretched state. Our findings give a unified explanation for multiple disparate experimental observations of protein folding.

preprint2009arXiv

Theory of biopolymer stretching at high forces

We provide a unified theory for the high force elasticity of biopolymers solely in terms of the persistence length, $ξ_p$, and the monomer spacing, $a$. When the force $f>\fh \sim k_BTξ_p/a^2$ the biopolymers behave as Freely Jointed Chains (FJCs) while in the range $\fl \sim k_BT/ξ_p < f < \fh$ the Worm-like Chain (WLC) is a better model. We show that $ξ_p$ can be estimated from the force extension curve (FEC) at the extension $x\approx 1/2$ (normalized by the contour length of the biopolymer). After validating the theory using simulations, we provide a quantitative analysis of the FECs for a diverse set of biopolymers (dsDNA, ssRNA, ssDNA, polysaccharides, and unstructured PEVK domain of titin) for $x \ge 1/2$. The success of a specific polymer model (FJC or WLC) to describe the FEC of a given biopolymer is naturally explained by the theory. Only by probing the response of biopolymers over a wide range of forces can the $f$-dependent elasticity be fully described.

preprint2006arXiv

Effect of finite size on cooperativity and rates of protein folding

We analyze the dependence of cooperativity of the thermal denaturation transition and folding rates of globular proteins on the number of amino acid residues, $N$, using lattice models with side chains,off-lattice Go models and the available experimental data. A dimensionless measure of cooperativity, $Ω_c$ ($0 < Ω_c < \infty$), scales as $Ω_c \sim N^ζ$. The results of simulations and the analysis of experimental data further confirm the earlier prediction that $ζ$ is universal with $ζ= 1 +γ$, where exponent $γ$ characterizes the susceptibility of a self-avoiding walk. This finding suggests that the structural characteristics in the denaturated state are manifested in the folding cooperativity at the transition temperature. The folding rates $k_F$ for the Go models and a dataset of 69 proteins can be fit using $k_F = k_F^0 \exp(-cN^β)$. Both $β= 1/2$ and 2/3 provide a good fit of the data. We find that $k_F = k_F^0 \exp(-cN^{1/2})$, with the average (over the dataset of proteins) $k_F^0 \approx (0.2μs)^{-1}$ and $c \approx 1.1$, can be used to estimate folding rates to within an order of magnitude in most cases. The minimal models give identical $N$ dependence with $c \approx 1$. The prefactor for off-lattice Go models is nearly four orders of magnitude larger than the experimental value.

preprint2005arXiv

The shape of a flexible polymer in a cylindrical pore

We calculate the mean end-to-end distance ($R$) of a self-avoiding polymer encapsulated in an infinitely long cylinder with radius $D$. A self-consistent perturbation theory is used to calculate $R$ as a function of $D$ for impenetrable hard walls and soft walls. In both cases, $R$ obeys the predicted scaling behavior in the limit of large and small $D$. The crossover from the three dimensional behavior ($D\to\infty$) to the fully stretched one dimensional case ($D\to 0$) is non-monotonic. The minimum value of $R$ is found at $D\sim 0.46 R_F$, where $R_F$ is the Flory radius of $R$ at $D \to \infty$. The results for soft walls map onto the hard wall case with a larger cylinder radius.

preprint2003arXiv

Anisotropic coarse-grained statistical potentials improve the ability to identify native-like protein structures

We present a new method to extract distance and orientation dependent potentials between amino acid side chains using a database of protein structures and the standard Boltzmann device. The importance of orientation dependent interactions is first established by computing orientational order parameters for proteins with alpha-helical and beta-sheet architecture. Extraction of the anisotropic interactions requires defining local reference frames for each amino acid that uniquely determine the coordinates of the neighboring residues. Using the local reference frames and histograms of the radial and angular correlation functions for a standard set of non-homologue protein structures, we construct the anisotropic pair potentials. The performance of the orientation dependent potentials was studied using a large database of decoy proteins. The results demonstrate that the new distance and orientation dependent residue-residue potentials present a significantly improved ability to recognize native folds from a set of native and decoy protein structures.

preprint1998arXiv

Fractal Analysis of Protein Potential Energy Landscapes

The fractal properties of the total potential energy V as a function of time t are studied for a number of systems, including realistic models of proteins (PPT, BPTI and myoglobin). The fractal dimension of V(t), characterized by the exponent γ, is almost independent of temperature and increases with time, more slowly the larger the protein. Perhaps the most striking observation of this study is the apparent universality of the fractal dimension, which depends only weakly on the type of molecular system. We explain this behavior by assuming that fractality is caused by a self-generated dynamical noise, a consequence of intermode coupling due to anharmonicity. Global topological features of the potential energy landscape are found to have little effect on the observed fractal behavior.

preprint1997arXiv

Distribution Function of the End-to-End Distance of Semiflexible Polymers

The distribution function of the end-to-end distance of a semiflexible polymer, G(R;L) (where R denotes the end-to-end distance and L the contour length), is calculated using a meanfield-like approach. The theory yields an extremely simple expression for G(R;L) which is in excellent agreement with Monte Carlo simulations. The second and fourth moments of G(R;L) agree with exact results for a semiflexible polymer in both the random coil and the rod limit.

D. Thirumalai

What is connected

Connect this record

See the researcher in context

Building this map preview

64 published item(s)

Loop Extrusion Reversal by Condensin Motor is Mediated by Catch Bonds

Mechanical feedback controls the emergence of dynamical memory in growing tissue monolayers

On the emergence of orientational order in folded proteins with implications for allostery

Cooperation among tumor cell subpopulations leads to intratumor heterogeneity

Dual Role of Cell-Cell Adhesion In Tumor Suppression and Proliferation Due to Collective Mechanosensing

Spatially Heterogeneous Dynamics of Cells in a Growing Tumor Spheroid: Comparison Between Theory and Experiments

Conformational Heterogeneity in Human Interphase Chromosome Organization Reconciles the FISH and Hi-C Paradox

Fragile-to-Strong Crossover, growing length scales, and dynamic heterogeneity in Wigner Glasses

How kinesin waits for ATP affects the nucleotide and load dependence of the stepping kinetics

Theoretical Perspectives on Biological Machines

Symmetry, Rigidity, and Allosteric Signaling: From Monomeric Proteins to Molecular Machines

Discrete step sizes of molecular motors lead to bimodal non-Gaussian velocity distributions under force

Folding PDZ2 domain using the Molecular Transfer Model

Noise control in gene regulatory networks with negative feedback

Phenomenological and microscopic theories for catch bonds

Protein Collapse is Encoded in the Folded State Architecture

Salt Effects on the Thermodynamics of a Frameshifting RNA Pseudoknot under Tension

Confinement-induced glassy dynamics in a model for chromosome organization

Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model

Effects of macromolecular crowding on the collapse of biopolymers

Extracting folding landscape characteristics of biomolecules using mechanical forces

Force-dependent switch in protein unfolding pathways and transition state movements

On the importance of hydrodynamic interactions in the stepping kinetics of kinesin

Unexpected swelling of stiff DNA in a polydisperse crowded environment

Cellular signaling networks function as generalized Wiener-Kolmogorov filters to suppress noise

Development and applications of Coarse Grained models for RNA

Dynamical Transition and Heterogeneous Hydration Dynamics in RNA

Entropy and enthalpy of interaction between amino acid side chains in nanopores

Membrane-protein interactions hold the key to understanding amyloid formation

Plasticity of hydrogen bond networks regulates mechanochemistry of cell adhesion complexes

Propensity to form amyloid fibrils is encoded as excitations in the free energy landscape of monomeric proteins

Random First Order Theory concepts in Biology and Condensed Matter physics

Universal relations in the self-assembly of proteins and RNA

A Coarse-Grained Model for Predicting RNA Folding Thermodynamics

Design principles governing the motility of myosin V

Entropic stabilization of the folded states of RNA due to macromolecular crowding

Force-Induced Unzipping Transitions in an Athermal Crowded Environment

From mechanical folding trajectories to intrinsic energy landscapes of biopolymers

Manifestation of Random First Order Transition theory in Wigner glasses

Chain Length Determines the Folding Rates of RNA

Exact solution of the Zwanzig-Lauritzen model of Polymer Crystallization under Tension

Gene Regulation by Riboswitches with and without Negative Feedback Loop

Hidden Complexity in the Isomerization Dynamics of Holliday Junctions

Multiple barriers in forced rupture of protein complexes

On the origin of the unusual behavior in the stretching of single-stranded DNA

RNA under Tension: Folding Landscapes, Kinetic Partitioning Mechanism, and Molecular Tensegrity

Capturing the essence of folding and functions of biomolecules using Coarse-Grained Models

Compaction and tensile forces determine the accuracy of folding landscape parameters from single molecule pulling experiments

Crowding Promotes the Switch from Hairpin to Pseudoknot Conformation in Human Telomerase RNA

Entropic Stabilization of Proteins by TMAO

Hydrophobic and ionic-interactions in bulk and confined water with implications for collapse and folding of proteins

Influence of Nanoparticle Size and Shape on Oligomer Formation of an Amyloidogenic Peptide

Polyelectrolyte and polyampholyte effects in synthetic and biological macromolecules

Role of water in Protein Aggregation and Amyloid Polymorphism

Determination of factors governing fibrillogenesis of polypeptide chains using lattice models

Factors governing fibrillogenesis of polypeptide chains

Theoretical Perspectives on Protein Folding

Refolding dynamics of stretched biopolymers upon force quench

Theory of biopolymer stretching at high forces

Effect of finite size on cooperativity and rates of protein folding

The shape of a flexible polymer in a cylindrical pore

Anisotropic coarse-grained statistical potentials improve the ability to identify native-like protein structures

Fractal Analysis of Protein Potential Energy Landscapes

Distribution Function of the End-to-End Distance of Semiflexible Polymers