Adaptive Evolution as a Predictor of Species-Specific Innate Immune Response

It has been proposed that positive selection may be associated with protein functional change. For example, human and macaque have different outcomes to HIV infection and it has been shown that residues under positive selection in the macaque TRIM5α receptor locate to the region known to influence species-specific response to HIV. In general, however, the relationship between sequence and function has proven difficult to fully elucidate, and it is the role of large-scale studies to help bridge this gap in our understanding by revealing major patterns in the data that correlate genotype with function or phenotype. In this study, we investigate the level of species-specific positive selection in innate immune genes from human and mouse. In total, we analyzed 456 innate immune genes using codon-based models of evolution, comparing human, mouse, and 19 other vertebrate species to identify putative species-specific positive selection. Then we used population genomic data from the recently completed Neanderthal genome project, the 1000 human genomes project, and the 17 laboratory mouse genomes project to determine whether the residues that were putatively positively selected are fixed or variable in these populations. We find evidence of species-specific positive selection on both the human and the mouse branches and we show that the classes of genes under positive selection cluster by function and by interaction. Data from this study provide us with targets to test the relationship between positive selection and protein function and ultimately to test the relationship between positive selection and discordant phenotypes

Change in Allosteric Network Affects Binding Affinities of PDZ Domains: Analysis through Perturbation Response Scanning

The allosteric mechanism plays a key role in cellular functions of several PDZ domain proteins (PDZs) and is directly linked to pharmaceutical applications; however, it is a challenge to elaborate the nature and extent of these allosteric interactions. One solution to this problem is to explore the dynamics of PDZs, which may provide insights about how intramolecular communication occurs within a single domain. Here, we develop an advancement of perturbation response scanning (PRS) that couples elastic network models with linear response theory (LRT) to predict key residues in allosteric transitions of the two most studied PDZs (PSD-95 PDZ3 domain and hPTP1E PDZ2 domain). With PRS, we first identify the residues that give the highest mean square fluctuation response upon perturbing the binding sites. Strikingly, we observe that the residues with the highest mean square fluctuation response agree with experimentally determined residues involved in allosteric transitions. Second, we construct the allosteric pathways by linking the residues giving the same directional response upon perturbation of the binding sites. The predicted intramolecular communication pathways reveal that PSD-95 and hPTP1E have different pathways through the dynamic coupling of different residue pairs. Moreover, our analysis provides a molecular understanding of experimentally observed hidden allostery of PSD-95. We show that removing the distal third alpha helix from the binding site alters the allosteric pathway and decreases the binding affinity. Overall, these results indicate that (i) dynamics plays a key role in allosteric regulations of PDZs, (ii) the local changes in the residue interactions can lead to significant changes in the dynamics of allosteric regulations, and (iii) this might be the mechanism that each PDZ uses to tailor their binding specificities regulation

SH3 Domain-Peptide Binding Energy Calculations Based on Structural Ensemble and Multiple Peptide Templates

SH3 domains mediate signal transduction by recognizing short peptides. Understanding of the driving forces in peptide recognitions will help us to predict the binding specificity of the domain-peptide recognition and to understand the molecular interaction networks of cells. However, accurate calculation of the binding energy is a tough challenge. In this study, we propose three ideas for improving our ability to predict the binding energy between SH3 domains and peptides: (1) utilizing the structural ensembles sampled from a molecular dynamics simulation trajectory, (2) utilizing multiple peptide templates, and (3) optimizing the sequence-structure mapping. We tested these three ideas on ten previously studied SH3 domains for which SPOT analysis data were available. The results indicate that calculating binding energy using the structural ensemble was most effective, clearly increasing the prediction accuracy, while the second and third ideas tended to give better binding energy predictions. We applied our method to the five SH3 targets in DREAM4 Challenge and selected the best performing method

Detailed Regulatory Mechanism of the Interaction between ZO-1 PDZ2 and Connexin43 Revealed by MD Simulations

The gap junction protein connexin43 (Cx43) binds to the second PDZ domain of Zonula occludens-1 (ZO-1) through its C-terminal tail, mediating the regulation of gap junction plaque size and dynamics. Biochemical study demonstrated that the very C-terminal 12 residues of Cx43 are necessary and sufficient for ZO-1 PDZ2 binding and phosphorylation at residues Ser (-9) and Ser (-10) of the peptide can disrupt the association. However, only a crystal structure of ZO-1 PDZ2 in complex with a shorter 9 aa peptide of connexin43 was solved experimentally. Here, the interactions between ZO-1 PDZ2 and the short, long and phosphorylated Cx43 peptides were studied using molecular dynamics (MD) simulations and free energy calculation. The short peptide bound to PDZ2 exhibits large structural variations, while the extension of three upstream residues stabilizes the peptide conformation and enhanced the interaction. Phosphorylation at Ser(-9) significantly weakens the binding and results in conformational flexibility of the peptide. Glu210 of ZO-1 PDZ2 was found to be a key regulatory point in Cx43 binding and phosphorylation induced dissociation

Binding Free Energy Landscape of Domain-Peptide Interactions

Peptide recognition domains (PRDs) are ubiquitous protein domains which mediate large numbers of protein interactions in the cell. How these PRDs are able to recognize peptide sequences in a rapid and specific manner is incompletely understood. We explore the peptide binding process of PDZ domains, a large PRD family, from an equilibrium perspective using an all-atom Monte Carlo (MC) approach. Our focus is two different PDZ domains representing two major PDZ classes, I and II. For both domains, a binding free energy surface with a strong bias toward the native bound state is found. Moreover, both domains exhibit a binding process in which the peptides are mostly either bound at the PDZ binding pocket or else interact little with the domain surface. Consistent with this, various binding observables show a temperature dependence well described by a simple two-state model. We also find important differences in the details between the two domains. While both domains exhibit well-defined binding free energy barriers, the class I barrier is significantly weaker than the one for class II. To probe this issue further, we apply our method to a PDZ domain with dual specificity for class I and II peptides, and find an analogous difference in their binding free energy barriers. Lastly, we perform a large number of fixed-temperature MC kinetics trajectories under binding conditions. These trajectories reveal significantly slower binding dynamics for the class II domain relative to class I. Our combined results are consistent with a binding mechanism in which the peptide C terminal residue binds in an initial, rate-limiting step

Ancient thioredoxins evolved to modern-day stability–function requirement by altering native state ensemble

Thioredoxins (THRXs)—small globular proteins that reduce other proteins—are ubiquitous in all forms of life, from Archaea to mammals. Although ancestral thioredoxins share sequential and structural similarity with the modern-day (extant) homologues, they exhibit significantly different functional activity and stability. We investigate this puzzle by comparative studies of their (ancient and modern-day THRXs\u27) native state ensemble, as quantified by the dynamic flexibility index (DFI), a metric for the relative resilience of an amino acid to perturbations in the rest of the protein. Clustering proteins using DFI profiles strongly resemble an alternative classification scheme based on their activity and stability. The DFI profiles of the extant proteins are substantially different around the α3, α4 helices and catalytic regions. Likewise, allosteric coupling of the active site with the rest of the protein is different between ancient and extant THRXs, possibly explaining the decreased catalytic activity at low pH with evolution. At a global level, we note that the population of low-flexibility (called hinges) and high-flexibility sites increases with evolution. The heterogeneity (quantified by the variance) in DFI distribution increases with the decrease in the melting temperature typically associated with the evolution of ancient proteins to their modern-day counterparts

Plant-expressed cocaine hydrolase variants of butyrylcholinesterase exhibit altered allosteric effects of cholinesterase activity and increased inhibitor sensitivity

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Accurate prediction of the dynamical changes within the second PDZ domain of PTP1e.

Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods.Journal ArticleResearch Support, N.I.H. ExtramuralResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe