Cited by 184Protein Structure and DynamicsComputational Drug Discovery MethodsMachine Learning in Bioinformatics

Computational prediction of protein–protein binding affinities

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Siebenmorgen, Till, Zacharias, Martin·2020·WIREs Computational Molecular Science

Abstract

Protein–protein interactions form central elements of almost all cellular processes. Knowledge of the structure of protein–protein complexes but also of the binding affinity is of major importance to understand the biological function of protein–protein interactions. Even weak transient protein–protein interactions can be of functional relevance for the cell during signal transduction or regulation of metabolism. The structure of a growing number of protein–protein complexes has been solved in recent years. Combined with docking approaches or template‐based methods, it is possible to generate structural models of many putative protein–protein complexes or to design new protein–protein interactions. In order to evaluate the functional relevance of putative or predicted protein–protein complexes, realistic binding affinity prediction is of increasing importance. Several computational tools ranging from simple force‐field or knowledge‐based scoring of single protein–protein complexes to ensemble‐based approaches and rigorous binding free energy simulations are available to predict relative and absolute binding affinities of complexes. With a focus on molecular mechanics force‐field approaches the present review aims at presenting an overview on available methods and discussing advantages, approximations, and limitations of the various methods. This article is categorized under: Molecular and Statistical Mechanics > Molecular Interactions Molecular and Statistical Mechanics > Free Energy Methods Software > Molecular Modeling

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Crossref · 10.1002/wcms.1448

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  • Alchemical decoupling of a complete protein molecule will usually result in poor convergence due to large free energy changes.

    “While in theory an alchemical pathway could be constructed via decoupling a binding partner in a protein–protein complex from its environment in the bound and unbound states, the alchemical decoupling of a complete protein molecule will usually result in poor convergence61 due to large free energy changes.62”

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Authors
Siebenmorgen, T., & Zacharias, M.
Affiliations
Technical University of Munich (DE)
Corresponding author
Zacharias, Martin
Venue
WIREs Computational Molecular Science
Publisher
Wiley
Published
2019-10-29
Volume
10
Issue
3
ISSN
  • 1759-0876 (ISSN-L)
  • 1759-0884
OpenAlex
W2982586377
Cited by
184
References
148
Citations by year
2026: 9 · 2025: 42 · 2024: 25 · 2023: 27 · 2022: 32 · 2021: 35 · 2020: 12 · 2019: 2
FWCI
6.70
Type
journal article
Language
en
Open access
Locations
  • Wiley Interdisciplinary Reviews Computational Molecular Science (publishedVersion, cc-by)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion, other-oa)
Funders
Deutsche Forschungsgemeinschaft (SFB863/A10)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
Keywords
protein-protein interaction, protein-protein complex, knowledge-based scoring, binding free energy, protein-protein docking, template-based modeling, protein-protein complex structure

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