arXiv subjects

Eugene I. Shakhnovich

Publications and source records attributed to Eugene I. Shakhnovich.

At least 55 records · Page 3Linked to original sources

arXiv2006

Protein and DNA sequence determinants of thermophilic adaptation

Prokaryotes living at extreme environmental temperatures exhibit pronounced signatures in the amino acid composition of their proteins and nucleotide compositions of their genomes reflective of adaptation to their thermal environments. However, despite significant efforts, the definitive answer of what are the genomic and proteomic compositional determinants of Optimal Growth Temperature of prokaryotic organisms remained elusive. Here the authors performed a comprehensive analysis of amino acid and nucleotide compositional signatures of thermophylic adaptation by exhaustively evaluating all combinations of amino acids and nucleotides as possible determinants of Optimal Growth Temperature for all prokaryotic organisms with fully sequences genomes.. The authors discovered that total concentration of seven amino acids in proteomes, IVYWREL, serves as a universal proteomic predictor of Optimal Growth Temperature in prokaryotes. Resolving the old-standing controversy the authors determined that the variation in nucleotide composition (increase of purine load, or A+G content with temperature) is largely a consequence of thermal adaptation of proteins. However, the frequency with which A and G nucleotides appear as nearest neighbors in genome sequences is strongly and independently correlated with Optimal Growth Temperature. as a result of codon bias in corresponding genomes. Together these results provide a complete picture of proteomic and genomic determinants of thermophilic adaptation.

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arXiv2006

Information and Protein Interfaces

To confer high specificity and affinity in binding, contacts at interfaces between two interacting macromolecules are expected to exhibit pair preferences for types of atoms or residues. Here we quantify these preferences by measuring the mutual information of contacts for 895 protein-protein interfaces. The information content is significant and is highest at the atomic resolution. A simple phenomenological theory reveals a connection between information at interfaces and the free energy spectrum of association. The connection is presented in the form of a relation between mutual information and the energy gap of the native bound state to off-target bound states. Measurement of information content in designed lattice interfaces show the predicted scaling behavior to the energy gap. Our theory also suggests that mutual information in contacts emerges by a selection mechanism, and that strong selection, or high conservation, of residues should lead to correspondingly high mutual information. Amino acids which contribute more heavily to information content are then expected to be more conserved. We verify this by showing a statistically significant correlation between the conservation of each of the twenty amino acids and their individual contribution to the information content at protein-protein interfaces

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arXiv2006

A Structure-Centric View of Protein Evolution, Design and Adaptation

Proteins, by virtue of their central role in most biological processes, represent one of the key subjects of the study of molecular evolution. Inherent to the indispensability of proteins for living cells is the fact that a given protein can adopt a specific three-dimensional shape that is specified solely by the proteins sequence of amino acids. Over the past several decades, structural biologists have demonstrated that the array of structures that proteins may adopt is quite astounding, and this has lead to a strong interest in understanding how protein structures change and evolve over time. In this review we consider a large body of recent work that attempts to illuminate this structure-centric picture of protein evolution. Much of this work has focused on the question of how completely new protein structures (i.e. new folds or topologies) are discovered by protein sequences as they evolve. Pursuant to this question of structural innovation has been a desire to describe and understand the observation that certain types of protein structures are far more abundant than others and how this uneven distribution of proteins implicates on the process through which new shapes are discovered. We consider a number of theoretical models that have been successful at explaining this heterogeneity in protein populations and discuss the increasing amount of evidence that indicates that the process of structural evolution involves the divergence of protein sequences and structures from one another.

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arXiv2005

High resolution protein folding with a transferable potential

A generalized computational method for folding proteins with a fully transferable potential and geometrically realistic all-atom model is presented and tested on seven different helix bundle proteins. The protocol, which includes graph-theoretical analysis of the ensemble of resulting folded conformations, was systematically applied and consistently produced structure predictions of approximately 3 Angstroms without any knowledge of the native state. To measure and understand the significance of the results, extensive control simulations were conducted. Graph theoretic analysis provides a means for systematically identifying the native fold and provides physical insight, conceptually linking the results to modern theoretical views of protein folding. In addition to presenting a method for prediction of structure and folding mechanism, our model suggests that a accurate all-atom amino acid representation coupled with a physically reasonable atomic interaction potential (that does not require optimization to the test set) and hydrogen bonding are essential features for a realistic protein model.

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arXiv2005

A simple physical model for scaling in protein-protein interaction networks

It has recently been demonstrated that many biological networks exhibit a scale-free topology where the probability of observing a node with a certain number of edges (k) follows a power law: i.e. p(k) ~ k^-g. This observation has been reproduced by evolutionary models. Here we consider the network of protein-protein interactions and demonstrate that two published independent measurements of these interactions produce graphs that are only weakly correlated with one another despite their strikingly similar topology. We then propose a physical model based on the fundamental principle that (de)solvation is a major physical factor in protein-protein interactions. This model reproduces not only the scale-free nature of such graphs but also a number of higher-order correlations in these networks. A key support of the model is provided by the discovery of a significant correlation between number of interactions made by a protein and the fraction of hydrophobic residues on its surface. The model presented in this paper represents the first physical model for experimentally determined protein-protein interactions that comprehensively reproduces the topological features of interaction networks. These results have profound implications for understanding not only protein-protein interactions but also other types of scale-free networks.

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arXiv2005

Entropic stabilization of proteins and its proteomic consequences

We report here a new entropic mechanism of protein thermostability due to residual dynamics of rotamer isomerization in native state. All-atom simulations show that Lysines have much greater number of accessible rotamers than Arginines in folded states of proteins. This finding suggests that Lysines would preferentially entropically stabilize the native state. Indeed we show in computational experiments that Arginine-to-Lysine amino acid substitutions result in noticeable stabilization of proteins. We then hypothesize that if evolution uses this physical mechanisms in its strategies of thermophilic adaptation then hyperthermostable organisms would have much greater content of Lysines in their proteomes than of comparable in size and similarly charged Arginines.. Consistent with that, high-throughput comparative analysis of complete proteomes shows extremely strong bias towards Arginine-to-Lysine replacement in hyperthermophilic organisms and overall much greater content of Lysines than Arginines in hyperthermophiles. This finding cannot be explained by GC compositional biases. Our study provides an example of how analysis of a delicate physical mechanism of thermostability helps to resolve a puzzle in comparative genomics as to why aminoacid compositions of hyperthermophilic proteomes are significantly biased towards Lysines but not Arginines

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arXiv2005

Geometric and physical considerations for realistic protein models

Protein structure is generally conceptualized as the global arrangement or of smaller, local motifs of helices, sheets, and loops. These regular, recurring secondary structural elements have well-understood and standardized definitions in terms of amino acid backbone geometry and the manner in which hydrogen bonding requirements are satisfied. Recently, "tube" models have been proposed to explain protein secondary structure in terms of the geometrically optimal packing of a featureless cylinder. However, atomically detailed simulations demonstrate that such packing considerations alone are insufficient for defining secondary structure; both excluded volume and hydrogen bonding must be explicitly modeled for helix formation. These results have fundamental implications for the construction and interpretation of realistic and meaningful biomacromolecular models.

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arXiv2005

Nucleation and the transition state of the SH3 domain

We present a verified computational model of the SH3 domain transition state (TS) ensemble. This model was built for three separate SH3 domains using experimental s in all-atom protein folding simulations. While averaging over all conformations incorrectly considers non-TS conformations as transition states, quantifying structures as pre-TS, TS, and post-TS by measurement of their transmission coefficient (pfold, or probability to fold) allows for rigorous conclusions regarding the structure of the folding nucleus and a full mechanistic analysis of the folding process. Through analysis of the TS, we observe a highly polarized nucleus in which many residues are solvent-exposed. Mechanistic analysis suggests the hydrophobic core forms largely after an early nucleation step. SH3 presents an ideal system for studying the nucleation-condensation mechanism and highlights the synergistic relationship between experiment and simulation in the study of protein folding.

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arXiv2004

Of sequence and structure: Strategies of protein thermostability in evolutionary perspective

In this work we employ various methods of analysis (unfolding simulations and comparative analysis of structures and sequences of proteomes of thermophilic organisms) to show that organisms can follow two major strategies of thermophilic adaptation: (i) General, non-specific, structure-based, when proteomes of certain thermophilic organisms show significant structural bias toward proteins of higher compactness. In this case thermostability is achieved by greater overall number of stabilizing contacts, none of which may be especially strong, and (ii) Specific, sequence-based, whereby sequence variations aimed at strengthening specific types of interactions (e.g. electrostatics) are applied without significantly changing structures of proteins. The choice of a certain strategy is a direct consequence of evolutionary history and environmental conditions of particular (hyper) thermophilic species: ancient hyperthermophilic organisms that directly evolved in hot environment, pursued mostly structure-based strategy, while later evolved organisms whose thermophilic adaptation was a consequence of their recolonization of hot environment, pursued specific, sequence-based strategy of thermophilic adaptation.

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arXiv2004

Evolutionary dynamics of adult stem cells: Comparison of random and immortal strand segregation mechanisms

This paper develops a point-mutation model describing the evolutionary dynamics of a population of adult stem cells. Such a model may prove useful for quantitative studies of tissue aging and the emergence of cancer. We consider two modes of chromosome segregation: (1) Random segregation, where the daughter chromosomes of a given parent chromosome segregate randomly into the stem cell and its differentiating sister cell. (2) ``Immortal DNA strand'' co-segregation, for which the stem cell retains the daughter chromosomes with the oldest parent strands. Immortal strand co-segregation is a mechanism, originally proposed by Cairns (J. Cairns, {\it Nature} {\bf 255}, 197 (1975)), by which stem cells preserve the integrity of their genomes. For random segregation, we develop an ordered strand pair formulation of the dynamics, analogous to the ordered strand pair formalism developed for quasispecies dynamics involving semiconservative replication with imperfect lesion repair (in this context, lesion repair is taken to mean repair of postreplication base-pair mismatches). Interestingly, a similar formulation is possible with immortal strand co-segregation, despite the fact that this segregation mechanism is age-dependent. From our model we are able to mathematically show that, when lesion repair is imperfect, then immortal strand co-segregation leads to better preservation of the stem cell lineage than random chromosome segregation. Furthermore, our model allows us to estimate the optimal lesion repair efficiency for preserving an adult stem cell population for a given period of time. For human stem cells, we obtain that mispaired bases still present after replication and cell division should be left untouched, to avoid potentially fixing a mutation in both DNA strands.

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arXiv2004

The Emergence of Scaling in Sequence-based Physical Models of Protein Evolution

It has recently been discovered that many biological systems, when represented as graphs, exhibit a scale-free topology. One such system is the set of structural relationships among protein domains. The scale-free nature of this and other systems has previously been explained using network growth models that, while motivated by biological processes, do not explicitly consider the underlying physics or biology. In the present work we explore a sequence-based model for the evolution protein structures and demonstrate that this model is able to recapitulate the scale-free nature observed in graphs of real protein structures. We find that this model also reproduces other statistical feature of the protein domain graph. This represents, to our knowledge, the first such microscopic, physics-based evolutionary model for a scale-free network of biological importance and as such has strong implications for our understanding of the evolution of protein structures and of other biological networks.

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arXiv2004

Semiconservative replication in the quasispecies model II: Generalization to arbitrary lesion repair probabilities

This paper extends the semiconservative quasispecies equations to account for arbitrary post-replication lesion repair efficiency. Such an extension could be an important tool for understanding processes such as cancer development and stem cell growth. Starting from the quasispecies dynamics over the space of genomes, we derive an equivalent dynamics over the space of ordered sequence pairs. From this set of equations, we are able to derive the infinite sequence length form of the dynamics for a class of ``master-genome''-based fitness landscapes. We use these equations to solve for a ``generalized'' single-fitness-peak landscape, where the master genome can sustain a maximum number of lesions and remain viable. The central pattern that emerges from our studies is that imperfect lesion repair often leads to increased mutational robustness over semiconservative replication with completely efficient lesion repair. The reason for this is that imperfect lesion repair breaks some of the correlation between the parent and daughter strands, thereby preventing replication errors from destroying the information in the original genome. The result is a delayed error catastrophe over that expected from the original semiconservative quasispecies model. In particular, we show that when only of the strands is necessary for conferring viability, then, when lesion repair is turned off, a semiconservatively replicating system becomes an effectively conservatively replicating one.

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arXiv2004

Imperfect DNA Repair and the Error Catastrophe

In this Letter, we extend the semiconservative quasispecies equations to incorporate imperfect DNA lesion repair. We study the equilibrium behavior of this model in the limit of infinite sequence length and population size, using a single-fitness-peak landscape for which the master genome can sustain a finite number of lesions and remain viable. We provide a full analytical treatment of the problem, providing a general mathematical framework as well as the full solution for a particular class of fitness landscapes. Stochastic simulations using finite sequence lengths and populations agree well with the analytical results. Applications to biological systems are briefly discussed.

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arXiv2004

The Importance of DNA Repair in Tumor Suppression

The transition from a normal to cancerous cell requires a number of highly specific mutations that affect cell cycle regulation, apoptosis, differentiation, and many other cell functions. One hallmark of cancerous genomes is genomic instability, with mutation rates far greater than those of normal cells. In microsatellite instability (MIN tumors), these are often caused by damage to mismatch repair genes, allowing further mutation of the genome and tumor progression. These mutation rates may lie near the error catastrophe found in the quasispecies model of adaptive RNA genomes, suggesting that further increasing mutation rates will destroy cancerous genomes. However, recent results have demonstrated that DNA genomes exhibit an error threshold at mutation rates far lower than their conservative counterparts. Furthermore, while the maximum viable mutation rate in conservative systems increases indefinitely with increasing master sequence fitness, the semiconservative threshold plateaus at a relatively low value. This implies a paradox, wherein inaccessible mutation rates are found in viable tumor cells. In this paper, we address this paradox, demonstrating an isomorphism between the conservatively replicating (RNA) quasispecies model and the semiconservative (DNA) model with post-methylation DNA repair mechanisms impaired. Thus, as DNA repair becomes inactivated, the maximum viable mutation rate increases smoothly to that of a conservatively replicating system on a transformed landscape, with an upper bound that is dependent on replication rates. We postulate that inactivation of post-methylation repair mechanisms are fundamental to the progression of a tumor cell and hence these mechanisms act as a method for prevention and destruction of cancerous genomes.

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arXiv2004

Solution of the Quasispecies Model for an Arbitrary Gene Network

In this paper, we study the equilibrium behavior of Eigen's quasispecies equations for an arbitrary gene network. We consider a genome consisting of $ N $ genes, so that each gene sequence $ σ$ may be written as $ σ= σ_1 σ_2 ... σ_N $. We assume a single fitness peak (SFP) model for each gene, so that gene $ i $ has some ``master'' sequence $ σ_{i, 0} $ for which it is functioning. The fitness landscape is then determined by which genes in the genome are functioning, and which are not. The equilibrium behavior of this model may be solved in the limit of infinite sequence length. The central result is that, instead of a single error catastrophe, the model exhibits a series of localization to delocalization transitions, which we term an ``error cascade.'' As the mutation rate is increased, the selective advantage for maintaining functional copies of certain genes in the network disappears, and the population distribution delocalizes over the corresponding sequence spaces. The network goes through a series of such transitions, as more and more genes become inactivated, until eventually delocalization occurs over the entire genome space, resulting in a final error catastrophe. This model provides a criterion for determining the conditions under which certain genes in a genome will lose functionality due to genetic drift. It also provides insight into the response of gene networks to mutagens. In particular, it suggests an approach for determining the relative importance of various genes to the fitness of an organism, in a more accurate manner than the standard ``deletion set'' method. The results in this paper also have implications for mutational robustness and what C.O. Wilke termed ``survival of the flattest.''

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arXiv2004

An Exact Model of Fluctuations in Gene Expression

Fluctuations in the measured mRNA levels of unperturbed cells under fixed conditions have often been viewed as an impediment to the extraction of information from expression profiles. Here, we argue that such expression fluctuations should themselves be studied as a source of valuable information about the underlying dynamics of genetic networks. By analyzing microarray data taken from Saccharomyces cerevisiae, we demonstrate that correlations in expression fluctuations have a highly statistically significant dependence on gene function, and furthermore exhibit a remarkable scale-free network structure. We therefore present what we view to be the simplest phenomenological model of a genetic network which can account for the presence of biological information in transcript level fluctuations. We proceed to exactly solve this model using a path integral technique and derive several quantitative predictions. Finally, we propose several experiments by which these predictions might be rigorously tested.

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arXiv2004

Host-Parasite Co-evolution and Optimal Mutation Rates for Semi-conservative Quasispecies

In this paper, we extend a model of host-parasite co-evolution to incorporate the semi-conservative nature of DNA replication for both the host and the parasite. We find that the optimal mutation rate for the semi-conservative and conservative hosts converge for realistic genome lengths, thus maintaining the admirable agreement between theory and experiment found previously for the conservative model and justifying the conservative approximation in some cases. We demonstrate that, while the optimal mutation rate for a conservative and semi-conservative parasite interacting with a given immune system is similar to that of a conservative parasite, the properties away from this optimum differ significantly. We suspect that this difference, coupled with the requirement that a parasite optimize survival in a range of viable hosts, may help explain why semi-conservative viruses are known to have significantly lower mutation rates than their conservative counterparts.

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arXiv2004

A Selective Advantage for Conservative Viruses

In this letter we study the full semi-conservative treatment of a model for the co-evolution of a virus and an adaptive immune system. Regions of viability are calculated for both conservatively and semi-conservatively replicating viruses interacting with a realistic semi-conservatively replicating immune system. The conservative virus is found to have a selective advantage in the form of an ability to survive in regions with a wider range of mutation rates than its semi-conservative counterpart. This may help explain the existence of a rich range of viruses with conservatively replicating genomes, a trait which is found nowhere else in nature.

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