Cited by 2,008Protein Structure and DynamicsReceptor Mechanisms and SignalingProtein Interaction Studies and Fluorescence Analysis

The role of dynamic conformational ensembles in biomolecular recognition

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Boehr, David D, Nussinov, Ruth, Wright, Peter E·2009·Nature Chemical Biology

Abstract

Molecular recognition is central to all biological processes. For the past 50 years, Koshland's 'induced fit' hypothesis has been the textbook explanation for molecular recognition events. However, recent experimental evidence supports an alternative mechanism. 'Conformational selection' postulates that all protein conformations pre-exist, and the ligand selects the most favored conformation. Following binding the ensemble undergoes a population shift, redistributing the conformational states. Both conformational selection and induced fit appear to play roles. Following binding by a primary conformational selection event, optimization of side chain and backbone interactions is likely to proceed by an induced fit mechanism. Conformational selection has been observed for protein-ligand, protein-protein, protein-DNA, protein-RNA and RNA-ligand interactions. These data support a new molecular recognition paradigm for processes as diverse as signaling, catalysis, gene regulation and protein aggregation in disease, which has the potential to significantly impact our views and strategies in drug design, biomolecular engineering and molecular evolution.

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  • The conformational selection mechanism theorizes that the energy surface hosts a very large number of conformations, the best-fitting one is selected, with subsequent minor induced fit optimization largely by side chains.

    “In contrast, the conformational selection mechanism167−169,185 theorizes that the energy surface hosts a very large number of conformations, and the one that fits best is selected, with subsequent minor induced fit optimization, largely by side chains.”

    From AlphaFold, Artificial Intelligence (AI), and Allostery (2022) · cites this paper as [185]

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  1. [75]Zhang Q Stelzer A Fisher C Al-Hashimi H Visualizing spatially correlated dynamics that directs RNA conformational transitions Nature 450 1263 1267 2007 18097416

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Authors
Boehr, D. D., Nussinov, R., & Wright, P. E.
Affiliations
  • Pennsylvania State University (US)
  • Tel Aviv University (IL)
  • Scripps Research Institute (US)
Corresponding author
  • Boehr, David D
  • Wright, Peter E
Venue
Nature Chemical Biology
Published
2009-10-10
Volume
5
Issue
11
Pages
789-796
ISSN
  • 1552-4450 (ISSN-L)
  • 1552-4469
OpenAlex
W2066962978
Cited by
2,008
References
99
Citations by year
2026: 147 · 2025: 108 · 2024: 99 · 2023: 85 · 2022: 93 · 2021: 116 · 2020: 99 · 2019: 119 · 2018: 99 · 2017: 127 · 2016: 129 · 2015: 117 · 2014: 150 · 2013: 152 · 2012: 128
FWCI
9.10
Type
journal article
Language
en
Update notices
erratum (2009-12-01)
Open access
Locations
  • Nature Chemical Biology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • U.S. Department of Health and Human Services
  • National Institutes of Health (n01co12400-79-0-22)
  • National Cancer Institute (N01CO12400, N01-CO-012400, CA96865, R01CA096865)
  • National Institute of General Medical Sciences (R01GM075995, GM75995)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
Keywords
conformational selection, induced fit, molecular recognition, protein-ligand binding, protein-protein interaction, protein-DNA interactions, RNA-protein interactions, RNA-ligand interactions, conformational ensembles, binding free energy, drug design, biomolecular engineering, molecular evolution
MeSH terms
Binding Sites, Disease, DNA, Enzymes, Gene Expression Regulation, Genetic Engineering, Humans, Ligands, Models, Molecular, Molecular Conformation, Pattern Recognition, Visual, Protein Conformation, Proteins, Repressor Proteins, RNA, Thermodynamics, Drug Design, Evolution, Molecular, Databases, Protein

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