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Physics-Based Computational Protein Design: An Update

David Mignon, Karen Druart, Eleni Michael, Vaitea Opuu, Savvas Polydorides, Francesco Della Villa, Thomas Gaillard, Nicolas Panel, Georgios Archontis, Thomas Simonson

2020The Journal of Physical Chemistry A25 citationsDOI

Abstract

We describe methods for physics-based protein design and some recent applications from our work. We present the physical interpretation of a MC simulation in sequence space and show that sequences and conformations form a well-defined statistical ensemble, explored with Monte Carlo and Boltzmann sampling. The folded state energy combines molecular mechanics for solutes with continuum electrostatics for solvent. We usually assume one or a few fixed protein backbone structures and discrete side chain rotamers. Methods based on molecular dynamics, which introduce additional backbone and side chain flexibility, are under development. The redesign of a PDZ domain and an aminoacyl-tRNA synthetase enzyme were successful. We describe a versatile, adaptive, Wang-Landau MC method that can be used to design for substrate affinity, catalytic rate, catalytic efficiency, or the specificity of these properties. The methods are transferable to all biomolecules, can be systematically improved, and give physical insights.

Topics & Concepts

Protein designMolecular dynamicsStatistical mechanicsPhysicsMonte Carlo methodElectrostaticsStatistical physicsBiomoleculeChain (unit)Molecular mechanicsProtein structure predictionComputational chemistryProtein structureChemistryNanotechnologyMaterials scienceQuantum mechanicsMathematicsStatisticsNuclear magnetic resonanceProtein Structure and DynamicsRNA and protein synthesis mechanismsBacterial Genetics and Biotechnology
Physics-Based Computational Protein Design: An Update | Litcius