Volume 11, Issue 3 e1502
Advanced Review

The challenge of predicting distal active site mutations in computational enzyme design

Sílvia Osuna

Corresponding Author

Sílvia Osuna

CompBioLab group, Institut de Química Computacional i Catàlisi (IQCC) and Departament de Química, Universitat de Girona, Girona, Spain

ICREA, Barcelona, Spain


Sílvia Osuna, CompBioLab group, Institut de Química Computacional i Catàlisi (IQCC) and Departament de Química, Universitat de Girona, c/Maria Aurèlia Capmany 69, Girona 17003, Spain.

Email: [email protected]

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First published: 25 August 2020
Citations: 56

Funding information: Agència de Gestió d'Ajuts Universitaris i de Recerca, Grant/Award Number: 2017 SGR-1707; H2020 European Research Council, Grant/Award Number: ERC-2015-StG-679001; Secretaría de Estado de Investigación, Desarrollo e Innovación, Grant/Award Number: PGC2018-102192-B-I00


Many computational enzyme design approaches have been developed in recent years that focus on a reduced set of key enzymatic features. Initial protocols mostly focused on the chemical steps(s) through transition state stabilization, whereas most recent approaches exploit the enzyme conformational dynamics often crucial for substrate binding, product release, and allosteric regulation. The detailed evaluation of the conformational landscape of many laboratory-evolved enzymes has revealed dramatic changes on the relative stabilities of the conformational states after mutation, favoring those conformational states key for the novel functionality. Of note is that these mutations are often located all around the enzyme structure, which contrasts with most of the computational design strategies that reduce the problem into active site alterations. Recent computational strategies have been developed that consider enzyme design as a population shift problem, that is, redistribution of the relative stabilities of the conformational states induced by mutations. These strategies focus on reconstructing the conformational landscape of the enzyme, applying correlation-based tools to elucidate the underlying allosteric network of interactions and identify potential mutation hotspots located at the active site, but most importantly at distal positions for the first time.

This article is categorized under:

  • Structure and Mechanism > Computational Biochemistry and Biophysics
  • Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
  • Software > Molecular Modeling

Graphical Abstract

Computational enzyme redesign as a population shift problem: the challenge lies in the computational prediction of distal and active site mutations for altering the relative stabilities of the conformational ensemble of the enzyme and favoring those conformational states of importance for the novel function.


The author has declared no conflict of interest for this article.