Literature DB >> 33170681

Physics-Based Computational Protein Design: An Update.

David Mignon1, Karen Druart1, Eleni Michael2, Vaitea Opuu1, Savvas Polydorides2, Francesco Villa1, Thomas Gaillard1, Nicolas Panel1, Georgios Archontis2, Thomas Simonson1.   

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.

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Year:  2020        PMID: 33170681     DOI: 10.1021/acs.jpca.0c07605

Source DB:  PubMed          Journal:  J Phys Chem A        ISSN: 1089-5639            Impact factor:   2.781


  4 in total

1.  A computational protein design protocol for optimization of the SARS-CoV-2 receptor-binding-motif affinity for human ACE2.

Authors:  Savvas Polydorides; Georgios Archontis
Journal:  STAR Protoc       Date:  2022-03-03

2.  Knowledge-Based Unfolded State Model for Protein Design.

Authors:  Vaitea Opuu; David Mignon; Thomas Simonson
Journal:  Methods Mol Biol       Date:  2022

3.  Computational Design of Miniprotein Binders.

Authors:  Younes Bouchiba; Manon Ruffini; Thomas Schiex; Sophie Barbe
Journal:  Methods Mol Biol       Date:  2022

4.  Propagation of seminal toxins through binary expression gene drives could suppress populations.

Authors:  Juan Hurtado; Santiago Revale; Luciano M Matzkin
Journal:  Sci Rep       Date:  2022-04-15       Impact factor: 4.996

  4 in total

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