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E. I. Shakhnovich

Publications and source records attributed to E. I. Shakhnovich.

18 recordsLinked to original sources

Identifying critical residues in protein folding: Insights from phi-value and Pfold analysis

We apply a simulational proxy of the phi-value analysis and perform extensive mutagenesis experiments to identify the nucleating residues in the folding reactions of two small lattice Go polymers with different native geometries. These results are compared with those obtained from an accurate analysis based on the reaction coordinate folding probability Pfold, and on structural clustering methods. For both protein models, the transition state ensemble is rather heterogeneous and splits-up into structurally different populations. For the more complex geometry the identified subpopulations are actually structurally disjoint. For the less complex native geometry we found a broad transition state with microscopic heterogeneity. For both geometries, the identification of the folding nucleus via the Pfold analysis agrees with the identification of the folding nucleus carried out with the phi-value analysis. For the most complex geometry, however, the apllied methodologies give more consistent results than for the more local geometry. The study of the transition state' structure reveals that the nucleus residues are not necessarily fully native in the transition state. Indeed, it is only for the more complex geometry that two of the five critical residues show a considerably high probability of having all its native bonds formed in the transition state. Therefore, one concludes that in general the phi-value correlates with the acceleration/deceleration of folding induced by mutation, rather than with the degree of nativeness of the transition state, and that the traditional interpretation of phi-values may provide a more realistic picture of the structure of the transition state only for more complex native geometries.

q-bio.BM↗

Structural similarity enhances interaction propensity of proteins

We study statistical properties of interacting protein-like surfaces and predict two strong, related effects: (i) statistically enhanced self-attraction of proteins; (ii) statistically enhanced attraction of proteins with similar structures. The effects originate in the fact that the probability to find a pattern self-match between two identical, even randomly organized interacting protein surfaces is always higher compared with the probability for a pattern match between two different, promiscuous protein surfaces. This theoretical finding explains statistical prevalence of homodimers in protein-protein interaction networks reported earlier. Further, our findings are confirmed by the analysis of curated database of protein complexes that showed highly statistically significant overrepresentation of dimers formed by structurally similar proteins with highly divergent sequences (superfamily heterodimers). We predict that significant fraction of heterodimers evolved from homodimers with the negative design evolutionary pressure applied against promiscuous homodimer formation. This is achieved through the formation of highly specific contacts formed by charged residues as demonstrated both in model and real superfamily heterodimers

q-bio.BM↗

Statistically enhanced self-attraction of random patterns

In this work we develop a theory of interaction of randomly patterned surfaces as a generic prototype model of protein-protein interactions. The theory predicts that pairs of randomly superimposed identical (homodimeric) random patterns have always twice as large magnitude of the energy fluctuations with respect to their mutual orientation, as compared with pairs of different (heterodimeric) random patterns. The amplitude of the energy fluctuations is proportional to the square of the average pattern density, to the square of the amplitude of the potential and its characteristic length, and scales linearly with the area of surfaces. The greater dispersion of interaction energies in the ensemble of homodimers implies that strongly attractive complexes of random surfaces are much more likely to be homodimers, rather than heterodimers. Our findings suggest a plausible physical reason for the anomalously high fraction of homodimers observed in real protein interaction networks.

q-bio.BM↗

Enhanced self-attraction of proteins and its evolutionary implications

Statistical analysis of protein-protein interactions shows anomalously high frequency of homodimers [Ispolatov, I., et al. (2005) Nucleic Acids Res 33, 3629-35]. Furthermore, recent findings [Wright, C.F., et al. (2005) Nature 438, 878-81] demonstrate that maintaining low sequence identity is a key evolutionary mechanism that inhibits protein aggregation. Here, we study statistical properties of interacting protein-like surfaces and predict the effect of universal, enhanced self-attraction of proteins. The effect originates in the fact that a pattern self-match between two identical, even randomly organized interacting protein surfaces is always stronger compared to the pattern match between two different, promiscuous protein surfaces. This finding implies an increased probability of homodimer selection in the course of early evolution. Our simple model of early evolutionary selection of interacting proteins accurately reproduces the experimental data on homodimer interface aminoacid compositions. In addition, we predict that heterodimers evolved from homodimers with the negative design evolutionary pressure applied against promiscuous homodimer formation. We predict that the anti-homodimer negative design evolutionary signal is conveyed through the enrichment of heterodimeric interfaces in polar residues, and most profoundly in glutamic acid and lysine, which is consistent with experimental findings. We predict therefore that the negative design against homodimers is the

q-bio.BM↗

Sidechain Dynamics and Protein Folding

The processes by which protein sidechains reach equilibrium during a folding reaction are investigated using both lattice and all-atom simulations. We find that rates of sidechain relaxation exhibit a distribution over the protein structure, with the fastest relaxing sidechains being involved in kinetically important positions. Traversal of the major folding transition state corresponds to the freezing of a small number of residues, while the rest of the chain proceeds towards equilibrium via backbone fluctuations around the native fold. The post-nucleation processes by which sidechains relax are characterized by very slow dynamics, and many barrier crossings, and thus resemble the behavior of a glass. At optimal temperature, however, the nucleated ensemble is energetically very close to equilibrium; slow relaxation is still observed. At lower temperatures, sidechain relaxation becomes a significant and very noticeable part of the folding reaction.

cond-mat.soft↗

The Folding Thermodynamics and Kinetics of Crambin Using an All-Atom Monte Carlo Simulation

We present a novel Monte Carlo simulation of protein folding, in which all heavy atoms are represented as interacting hard spheres. This model includes all degrees of freedom relevant to folding - all sidechain and backbone torsions - and uses a Go potential. In this study, we focus on the 46 residue alpha-beta protein crambin and two of its structural components, the helix and helix hairpin. For a wide range of temperatures, we have recorded multiple folding events of these three structures from random coils to native conformations that differ by less than 1 A dRMS from their crystal structure coordinates. The thermodynamics and kinetic mechanism of the helix-coil transition obtained from our simulation shows excellent agreement with currently available experimental and molecular dynamics data. Based on insights obtained from folding its smaller structural components, a possible folding mechanism for crambin is proposed. We observe that the folding occurs via a cooperative, first order-like process, and that many folding pathways to the native state exist. One particular sequence of events constitutes a ``fast-folding'' pathway where kinetic traps are avoided. At very low temperatures, a kinetic trap arising from the incorrect packing of sidechains was observed. These results demonstrate that folding to the native state can be observed in a reasonable amount of time on desktop computers even when an all-atom representation is used, provided the energetics sufficiently stabilize the native state.

cond-mat.soft↗

Hiking in the energy landscape in sequence space: a bumpy road to good folders

With the help of a simple 20 letters, lattice model of heteropolymers, we investigate the energy landscape in the space of designed good-folder sequences. Low-energy sequences form clusters, interconnected via neutral networks, in the space of sequences. Residues which play a key role in the foldability of the chain and in the stability of the native state are highly conserved, even among the chains belonging to different clusters. If, according to the interaction matrix, some strong attractive interactions are almost degenerate (i.e. they can be realized by more than one type of aminoacid contacts) sequence clusters group into a few super-clusters. Sequences belonging to different super-clusters are dissimilar, displaying very small ($\approx 10%$) similarity, and residues in key-sites are, as a rule, not conserved. Similar behavior is observed in the analysis of real protein sequences.

cond-mat.soft↗

Orientational Ordering in Sequence-Disordered Liquid Crystalline Polymers

Phase separation of sequence-disordered liquid crystalline polymers, a promising class of technological and biological relevance, is studied by field theory, and thermodynamic mechanisms responsible for orientational ordering observed in experiments, are discussed. The theory developed predicts that chemical disorder marginally affects the nematic/isotropic biphasic coexistence width, but strongly impacts ordering; above a critical chemical disorder threshold orientational ordering is precluded.

cond-mat.stat-mech↗

Stability of Designed Proteins Against Mutations

The stability of model proteins with designed sequences is assessed in terms of the number of sequences (obtained from the designed sequence through mutations), which fold into 5the ``native'' conformation. By a complete enumeration of the total number of sequences obtained by introducing up to 4 point mutations and up to 7 composition--conserving mutations (swapping of amino acids) in a 36mers chain, it is found that there are $10^8-10^9$ sequences which in the folding process target onto the ``native'' conformation. Consequently, proteins with designed sequences display a remarkable degree of stability and, to a large extent, of designability.

cond-mat.soft↗

Disordered Heteropolymers with Crosslinks - Phase Diagram and Conformational Transitions

We study the phase behavior of random heteropolymers (RHPs) with quenched cross-links, a novel polymer class of technological and biological relevance, and show the possible occurrence of freezing with few chain conformations sampled. The sensitivity of the frozen phase microstructure to the disorder components is elucidated at positive solubility parameter values; at low T's segregated microphases form, while at a finite T, a first order conformational transition occurs, and is attributed to statistical matching of large microphases bounded by cross-links. The end of the symmetry broken regime stabilization by cross-links occurs at a higher T by a second order conformational transition. \\icrophases form, while at a finite T, a first order conformational transition occurs, and is attributed to statistical matching of large microphases bounded by cross-links. The end of the symmetry broken regime stabilization by cross-links occurs at a higher T by a second order conformational transition.

cond-mat.stat-mech↗

Protein design: A perspective from simple tractable models

We review the recent progress in computational approaches to protein design which builds on advances in statistical-mechanical protein folding theory. In particular, we evaluate the degeneracy of the protein code (i.e. how many sequences fold into a given conformation) and outline a simple condition for ''designability`` in a protein model. From this point of view we discuss several popular protein models that were used for sequence design by several authors. We evaluate the strengths and weaknesses of popular approaches based on stochastic optimization in sequence space and discuss possible ways to improve them to bring them closer to experiment. We also discuss how sequence design affects folding and point out to some features of proteins that can be deigned ''in'' or designed ''out''}

cond-mat↗

How to derive a protein folding potential? A new approach to the old problem

In this paper we introduce a novel method of deriving a pairwise potential for protein folding. The potential is obtained by optimization procedure, which simultaneously maximizes the energy gap for {\it all} proteins in the database. To test our method and compare it with other knowledge-based approaches to derive potentials, we use simple lattice model. In the framework of the lattice model we build a database of model proteins by a) picking randomly 200 lattice chain conformations; b) designing sequences which fold into these structures with some arbitrary ``true'' potential; c) use this database for extracting a potential; d) fold model proteins using the extracted potential. This test on the model system showed that our procedure is able to recover the potential with correlation $r \approx 91\%$ with the ``true'' one and we were able to fold all model structures using the recovered potential. Other statistical knowledge-based approaches were tested using lattice models and the results indicate that they also can recover the ``true'' potential with high degree of accuracy. When applied to real protein structures with energy function taken in contact pairwise approximation, our potential scored somewhat better than existing ones. However, the discrimination of the native structure from decoys is still not strong enough to make the potential useful for {\em ab initio} folding. We argue that more detail of protein structure and energetics should be taken into account to achieve better energy gaps. The suggested method is general to allow to systematically derive parameters for more sophisticated energy function. The internal control of validity of the potential derived by our method, is converegency to a unique solution upon addition of new proteins to the database.

cond-mat↗

Theory of Kinetic Partitioning in Protein Folding (With Application to Prions)

In this paper we study the phenomenon of kinetic partitioning when a polypeptide chain has two ground state conformations one of which is more kinetically reachable than the other. This question is relevant to understand the phenomenology of prions, proteins which exist in the cell in non-pathogenic $α$-helical conformation but under certain circumstances may transform into pathogenic $PrP^{Sc}$ state featuring increased $β$-sheet content. We designed sequences for lattice model proteins having two different conformations of equal energy corresponding to the global energy minimum. Folding simulations revealed that one of these conformations was indeed much more kinetically accessible than the other. We found that the number and strength of local contacts in the ground state conformation is the major factor which determines which conformation is reached faster: The greater the number of local contacts the more kinetically reachable a conformation is. We present simple statistical-mechanical arguments to explain these findings. The presented results are in a clear agreement with experimental data on prions and other proteins exhibiting kinetic partitioning.

cond-mat↗

Chain length scaling of protein folding time

Folding of protein-like heteropolymers into unique 3D structures is investigated using Monte Carlo simulations on a cubic lattice. We found that folding time of chains of length $N$ scales as $N^λ$ at temperature of fastest folding. For chains with random sequences of monomers $λ\approx 6$, and for chains with sequences designed to provide a pronounced minimum of energy to their ground state conformation $λ\approx 4$. Folding at low temperatures exhibits an Arrhenius-like behavior with the energy barrier $E_b \approx ϕ|E_n|$, where $E_n$ is the energy of the native conformation. $ϕ\approx 0.18$ both for random and designed sequences.

cond-mat↗

Cooperativity of Protein Folding and the Random-Field Ising Model

The relation between cooperativity of protein folding and the Random-Field Ising Model (RFIM) is established. Generalization of the Imry-Ma argument predicts cooperative folding transition for small heterogeneity of the interactions stabilizing the native structure. Monte Carlo simulation of a lattice model shows that starting from some finite heterogeneity folding transition is not cooperative and involves formation of domains.

cond-mat↗

Dynamics of heteropolymers in dilute solution: effective equation of motion and relaxation spectrum

The dynamics of a heteropolymer chain in solution is studied in the limit of long chain length. Using functional integral representation we derive an effective equation of motion, in which the heterogeneity of the chain manifests itself as a time-dependent excluded volume effect. At the mean field level, the heteropolymer chain is therefore dynamically equivalent to a homopolymer chain with both time-independent and time-dependent excluded volume effects. The perturbed relaxation spectrum is also calculated. We find that heterogeneity also renormalizes the relaxation spectrum. However, we find, to the lowest order in heterogeneity, that the relaxation spectrum does not exhibit any dynamic freezing, at the point when static (equilibrium) ``freezing'' transition occurs in heteropolymer. Namely, the breaking of fluctuation-dissipation theorem (FDT) proposed for spin glass dynamics does not have dynamic effect in heteropolymer, as far as relaxation spectrum is concerned. The implication of this result is discussed.

cond-mat↗

Statistical mechanics of a cross-linked polymer blend

We study a blend of two kinds of homopolymers with tendency for segragation. Cross-links between the chains of different kinds do not allow macrophase separation. Instead microphase structure appears. Starting from a microscopic model we derive the effective Hamiltonian and calculate the form of the inverse scattering function and the domain size. The latter is found to be of the order of the mesh size. We show agreement of the results obtained by this microscopic statistical mechanical theory with experimental data and the existing scaling arguments.

cond-mat↗

Fluctuation Effects on Microphase Separation in Random Copolymers

We study random copolymers consisted of two kinds of monomers with attraction between similar kinds. The mean field analysis of this system indicates a continuous phase transition into a phase with periodic microdomain structure. It is shown that the inverse of the renormalized propagator has a minimum at non-zero wave-numbers. Consequently, there is an anomalously large contribution of fluctuations that make the disordered phase locally stable at every finite temperature. However, below a certain temperature, the ordered phase is shown to be locally stable and a weak first order transition is possible, similar to the weak crystallization theory developed by Brazovskii.

cond-mat↗