Physics-Based Computational Protein Design: An Update

J Phys Chem A. 2020 Dec 24;124(51):10637-10648. doi: 10.1021/acs.jpca.0c07605. Epub 2020 Nov 10.

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.

MeSH terms

  • Algorithms
  • Computational Chemistry
  • Data Interpretation, Statistical
  • Molecular Dynamics Simulation
  • Monte Carlo Method
  • Protein Conformation
  • Protein Folding
  • Proteins / chemistry*
  • Software
  • Thermodynamics

Substances

  • Proteins