title: Structure-Based Statistical Mechanical Model Accounts for the Causality and Energetics of Allosteric Communication.
abstract: Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design.
authors.affiliation: Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.
authors.forename: Enrico
authors.initials: E
authors.lastname: Guarnera
authors.affiliation: Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.|Department of Biological Sciences (DBS), National University of Singapore (NUS), Singapore.
authors.forename: Igor N
authors.initials: IN
authors.lastname: Berezovsky
mesh_terms: D000494:Allosteric Regulation; D000495:Allosteric Site; D000595:Amino Acid Sequence; D003198:Computer Simulation; D004735:Energy Transfer; D004789:Enzyme Activation; D004798:Enzymes / Q000737:chemistry* / Q000648:ultrastructure*; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011485:Protein Binding; D011487:Protein Conformation; D013329:Structure-Activity Relationship; D013816:Thermodynamics
chemical_list: D004798:Enzymes