Biology subjects

Thirumalai, D.

Publications and source records attributed to Thirumalai, D..

22 records · Page 2Linked to original sources

bioRxiv2017

Molecular chaperones maximize the native state yield per unit time by driving substrates out of equilibrium

Molecular chaperones have evolved to facilitate folding of proteins and RNA in vivo where spontaneous self-assembly is sometimes prohibited. Folding of Tetrahymena ribozyme, assisted by the RNA chaperone CYT-19, surprisingly shows that at physiological Mg2+ ion concentrations, increasing the chaperone concentration reduces the yield of native ribozymes. In contrast, the more extensively investigated protein chaperone GroEL works in exactly the opposite manner--the yield of native substrate increases with the increase in chaperone concentration. Thus, the puzzling observation on the assisted-ribozyme folding seems to contradict the expectation that a molecular chaperone acts as an efficient annealing machine. We suggest a resolution to this apparently paradoxical behavior by developing a minimal stochastic model that captures the essence of the Iterative Annealing Mechanism (IAM), providing a unified description of chaperone mediated-folding of proteins and RNA. Our theory provides a general relation involving the kinetic rates of the system, which quantitatively predicts how the yield of native state depends on chaperone concentration. By carefully analyzing a host of experimental data on Tetrahymena (and its mutants) as well as the protein Rubisco and Malate Dehydrogenase, we show that although the absolute yield of native states decreases in the ribozyme, the rate of native state production increases in both the cases. By utilizing energy from ATP hydrolysis, both CYT-19 and GroEL drive their substrate concentrations far out of equilibrium, in an endeavor to maximize the native yield in a short time. Our findings are consistent with the general expectation that proteins or RNA need to be folded by the cellular machinery on biologically relevant timescales, even if the final yield is lower than what equilibrium thermodynamics would dictate. Besides establishing the IAM as the basis for functions of RNA and protein chaperones, our work shows that cellular copy numbers have been adjusted to optimize the rate of native state production of the folded states of RNA and proteins under physiological conditions.\n\nSignificance statementMolecular chaperones have evolved to assist the folding of proteins and RNA, thus avoiding the deleterious consequences of misfolding. Thus, it is expected that increasing chaperone concentration should lead to an enhancement in native yield. While this has been observed in GroEL-mediated protein folding, experiments on Tetrahymena ribozyme folding assisted by CYT-19, surprisingly show the opposite trend. Here, we reconcile these divergent experimental observations by developing a unified stochastic model of chaperone assisted protein and RNA folding. We show that chaperones drive their substrates out of equilibrium, and in the process maximize the rate of native substrate production rather than the absolute yield or the folding rate. In vivo the number of chaperones is regulated to optimize their functions.

biophysics↗

bioRxiv2017

Optimal Information Transfer In Enzymatic Networks: A Field Theoretic Formulation

Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach in order to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus (Phys. Rev. X., 4, 041017 (2014)). We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudo intermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudo intermediate. Surprisingly, in these examples the minimum error computed using simulations that take non-linearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in networks of arbitrary complexity.

biophysics↗

bioRxiv2016

Interplay of Driver, Mini-Driver, and Deleterious Passenger Mutations on Cancer Progression

Cancer is caused by the accumulation of a critical number of somatic mutations (drivers) that offer fitness advantage to tumor cells. Moderately deleterious passengers, suppressing cancer progression, and mini-drivers, mildly beneficial to tumors, can profoundly alter the cancer evolutionary landscape. This observation prompted us to develop a stochastic evolutionary model intended to probe the interplay of drivers, mini-drivers and deleterious passengers in tumor growth over a broad range of fitness values and mutation rates. Below a (small) threshold number of drivers tumor growth exhibits a plateau (dormancy) with large burst occurring when a driver achieves fixation, reminiscent of intermittency in dissipative dynamical systems. The predictions of the model, in particular the relationship between the average number of passenger mutations versus drivers in a tumor, is in accord with clinical data on several cancers. When deleterious drivers are included, we predict a non-monotonic growth of tumors as the mutation rate is varied with shrinkage and even reversal occurring at very large mutation rates. This surprising finding explains the paradoxical observation that high chromosomal instability (CIN) correlates with improved prognosis in a number of cancers compared with intermediate CIN.

cancer biology↗

bioRxiv2016

Collapse Precedes Folding in Denaturant-Dependent Assembly of Ubiquitin

Despite the small size the folding of Ubiquitin (Ub), which plays an indispensable role in targeting proteins for degradation and DNA damage response, is complex. A number of experiments on Ub folding have reached differing conclusions regarding the relation between collapse and folding, and whether intermediates are populated. In order to resolve these vexing issues, we elucidate the denaturant-dependent thermodynamics and kinetics of Ub folding in low and neutral pH as a function of Guanidinium chloride and Urea using coarse-grained molecular simulations. The changes in the fraction of the folded Ub, and the radius of gyration (Rg) as a function of the denaturant concentration, [C], are in quantitative agreement with experiments. Under conditions used in experiments, Rg of the unfolded state at neutral pH changes only by {approx} 17% as the [GdmCl] decreases from 6 M to 0 M. We predict that the extent of compaction of the unfolded state increases as temperature decreases. A two-dimensional folding landscape as a function of Rg and a measure of similarity to the folded state reveals unambiguously that the native state assembly is preceded by collapse, as discovered in fast mixing experiments on several proteins. Analyses of the folding trajectories, under mildly denaturing conditions ([GdmCl]=1.0M or [Urea]=1.0M), shows that Ub folds by collision between preformed secondary structural elements involving kinetic intermediates that are primarily stabilized by long-range contacts. Our work explains the results of Small Angle X-Ray Scattering (SAXS) experiments on Ub quantitatively, and establishes that evolved globular proteins are poised to collapse. In the process, we explain the discrepancy between SAXS and single molecule fluorescent resonant energy transfer (smFRET) experiments, which have arrived at a contradicting conclusion concerning the collapse of polypeptide chains.

biophysics↗