 Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein AllosteryRobert Kalescky, Hongyu Zhou, Jin Liu and Peng Tao PLOS Computational Biology, 2016, vol. 12, issue 4, 1-21 Abstract: Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier’s principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery.Author Summary: Allostery is a fundamental dynamics property of many proteins, and plays a critical role in protein functions. Despite extensive experimental and theoretical studies of protein allosteric mechanisms, the current understanding and predicting power of protein allostery are still limited. One of the main challenges in studying protein allostery is effectively narrowing down residues for further site-directed mutagenesis study. Our goal is to develop effective computational tools to systematically evaluate significance of individual residue in protein dynamics and allostery without any a priori knowledge about protein allosteric mechanism. In this study, we significantly enhanced a simulation protocol developed in our lab, rigid residue scan (RRS), through combination of configurational entropy calculation, principal component analysis (PCA), and projection of ensembles onto coherent allosteric modes. Detailed analysis of the impact of removing individual residue internal motions on overall protein dynamics led to identification of key allosteric residues. Our prediction of key allosteric residues has good agreement with experimental studies of an allosteric protein as a model system, which displays allostery through binding events. Interestingly, the entropy calculations suggest that the La Châtelier’s principle in chemical equilibrium may also govern the rigidity/flexibility equilibrium in protein structure, which is related to protein allostery. Our study has demonstrated these methods to be very valuable tools to effectively identify initial key residues for proteins with crystallographic structures and limited information of their allosteric mechanisms. Date: 2016 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1004893 DOI: 10.1371/journal.pcbi.1004893 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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