The role of dynamic conformational ensembles in biomolecular recognition
Open accessAbstract
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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Self-citationAllostery without a conformational change? Revisiting the paradigm
Nussinov, R., & Tsai, C.-J. (2015) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.11.005 · Cited by 202 · see citing works
Self-citationImpact of protein conformational diversity on AlphaFold predictions
Saldaño, T., Escobedo, N., Marchetti, J., Zea, D. J., Mac Donagh, J., Velez Rueda, A. J., Gonik, E., García Melani, A., Novomisky Nechcoff, J., Salas, M. N., et al. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac202 · Cited by 196 · see citing works
AlphaFold, Artificial Intelligence (AI), and Allostery
Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190 · see citing works
Self-citationRas activation by SOS: Allosteric regulation by altered fluctuation dynamics
Iversen, L., Tu, H.-L., Lin, W.-C., Christensen, S. M., Abel, S. M., Iwig, J., Wu, H.-J., Gureasko, J., Rhodes, C., Petit, R. S., et al. (2014) · Science · doi:10.1126/science.1250373 · Cited by 154 · see citing works
Metabolite recognition principles and molecular mechanisms underlying riboswitch function
Serganov, A., & Patel, D. J. (2012) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-101211-113224 · Cited by 160 · see citing works
Principles of Allosteric Interactions in Cell Signaling
Nussinov, R., Tsai, C.-J., & Liu, J. (2014) · Journal of the American Chemical Society · doi:10.1021/ja510028c · Cited by 154 · see citing works
Self-citationExploring the role of receptor flexibility in structure-based drug discovery
Feixas, F., Lindert, S., Sinko, W., & McCammon, J. A. (2014) · Biophysical Chemistry · doi:10.1016/j.bpc.2013.10.007 · Cited by 156 · see citing works
The Design of Covalent Allosteric Drugs
Nussinov, R., & Tsai, C.-J. (2015) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010814-124401 · Cited by 112 · see citing works
Self-citationProtein Conformational Populations and Functionally Relevant Substates
Ramanathan, A., Savol, A., Burger, V., Chennubhotla, C. S., & Agarwal, P. K. (2014) · Accounts of Chemical Research · doi:10.1021/ar400084s · Cited by 110 · see citing works
Cooperative Unfolding of Compact Conformations of the Intrinsically Disordered Protein Osteopontin
Kurzbach, D., Platzer, G., Schwarz, T. C., Henen, M. A., Konrat, R., & Hinderberger, D. (2013) · Biochemistry · doi:10.1021/bi400502c · Cited by 105 · see citing works
Structure-based prediction of protein allostery
Greener, J. G., & Sternberg, M. J. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.10.002 · Cited by 91 · see citing works
Information transfer by leaky, heterogeneous, protein kinase signaling systems
Voliotis, M., Perrett, R. M., McWilliams, C., McArdle, C. A., & Bowsher, C. G. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314446111 · Cited by 98 · see citing works
RNA-guided assembly of Rev-RRE nuclear export complexes
Bai, Y., Tambe, A., Zhou, K., & Doudna, J. A. (2014) · eLife · doi:10.7554/elife.03656 · Cited by 86 · see citing works
Greives, N., & Zhou, H.-X. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1407545111 · Cited by 82 · see citing works
Biased cytochrome P450-mediated metabolism via small-molecule ligands binding P450 oxidoreductase
Jensen, S. B., Thodberg, S., Parween, S., Moses, M. E., Hansen, C. C., Thomsen, J., Sletfjerding, M. B., Knudsen, C., Del Giudice, R., Lund, P. M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22562-w · Cited by 64 · see citing works
Protein flexibility in drug discovery: from theory to computation.
Buonfiglio, R., Recanatini, M., & Masetti, M. (2015) · ChemMedChem · doi:10.1002/cmdc.201500086 · Cited by 73 · see citing works
Di Cera, E. (2020) · Biophysics Reviews · doi:10.1063/5.0020997 · Cited by 73 · see citing works
“Pathway drug cocktail”: targeting Ras signaling based on structural pathways
Nussinov, R., Tsai, C.-J., & Mattos, C. (2013) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2013.07.009 · Cited by 62 · see citing works
Self-citationCritical Scaffolding Regions of the Tumor Suppressor Axin1 Are Natively Unfolded
Noutsou, M., Duarte, A. M. S., Anvarian, Z., Didenko, T., Minde, D. P., Kuper, I., de Ridder, I., Oikonomou, C., Friedler, A., Boelens, R., et al. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.11.013 · Cited by 58 · see citing works
Allosteric Conformational Barcodes Direct Signaling in the Cell
Nussinov, R., Ma, B., Tsai, C.-J., & Csermely, P. (2013) · Structure · doi:10.1016/j.str.2013.06.002 · Cited by 55 · see citing works
Self-citationConformational Recognition of an Intrinsically Disordered Protein
Krieger, J. M., Fusco, G., Lewitzky, M., Simister, P. C., Marchant, J., Camilloni, C., Feller, S. M., & De Simone, A. (2014) · Biophysical Journal · doi:10.1016/j.bpj.2014.03.004 · Cited by 56 · see citing works
Bush, M., Alhanshali, B. M., Qian, S., Stanley, C. B., Heller, W. T., Matsui, T., Weiss, T. M., Nicholl, I. D., Walz, T., Callaway, D. J. E., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911489116 · Cited by 42 · see citing works
Kurkcuoglu, Z., & Bonvin, A. M. J. J. (2020) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25802 · Cited by 37 · see citing works
Xia, J., Deng, N.-J., & Levy, R. M. (2013) · The Journal of Physical Chemistry B · doi:10.1021/jp400797y · Cited by 29 · see citing works
Protein multiple conformations prediction using multi-objective evolution algorithm
Hou, M.-H., Jin, S.-R., Cui, X.-Y., Peng, C.-X., Zhao, K.-L., Song, L., & Zhang, G.-J. (2023) · doi:10.1101/2023.04.21.537776 · Cited by 29 · see citing works
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“However, a protein may have two or more viable conformations that correspond to different functional or physical states responding to various conditions, such as interactions with other molecules and environmental conditions 24,25 .”
Quantitatively accounting for protein reorganization in computer-aided drug design
Fajer, M., Borrelli, K., Abel, R., & Wang, L. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00009 · Cited by 18 · see citing works
Dynamic Protein Allosteric Regulation and Disease
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Self-citationImpact of protein conformational diversity on AlphaFold predictions
Saldaño, T., Escobedo, N., Marchetti, J., Zea, D. J., Mac Donagh, J., Velez Rueda, A. J., Gonik, E., Melani, A. G., Novomisky Nechcoff, J., Salas, M. N., et al. (2021) · doi:10.1101/2021.10.27.466189 · Cited by 196 · see citing works
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Ensemble-based characterization of unbound and bound states on protein energy landscape
Ruvinsky, A. M., Kirys, T., Tuzikov, A. V., & Vakser, I. A. (2013) · Protein Science · doi:10.1002/pro.2256 · Cited by 9 · see citing works
Lesovoy, D., Roshchin, K., Sala, B. M., Sandalova, T., Achour, A., Agback, T., Orekhov, V., & Agback, P. (2025) · doi:10.1101/2025.02.07.637034 · Cited by 6 · see citing works
- 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
- PMC
- PMC2916928
- 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
- green
- www.ncbi.nlm.nih.gov
- 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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