Frustration, specific sequence dependence, and nonlinearity in large-amplitude fluctuations of allosteric proteins
Open accessAbstract
Proteins have often evolved sequences so as to acquire the ability for regulation via allosteric conformational change. Here we investigate how allosteric dynamics is designed through sequences with nonlinear interaction features. First, for 71 allosteric proteins of which two, open and closed, structures are available, a statistical survey of interactions using an all-atom model with effective solvation shows that those residue contact interactions specific to one of the two states are significantly weaker than are the contact interactions shared by the two states. This interaction feature indicates there is underlying sequence design to facilitate conformational change. Second, based on the energy landscape theory, we implement these interaction features into a new atomic-interaction-based coarse-grained model via a multiscale simulation protocol (AICG). The AICG model outperforms standard coarse-grained models for predictions of the native-state mean fluctuations and of the conformational change direction. Third, using the new model for adenylate kinase, we show that intrinsic fluctuations in one state contain rare and large-amplitude motions nearly reaching the other state. Such large-amplitude motions are realized partly by sequence specificity and partly by the nonlinear nature of contact interactions, leading to cracking. Both features enhance conformational transition rates.
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In allosteric proteins, hinges sit near high-frustration regions, allowing rare large-amplitude fluctuations that approach the opposite state basin.
“Their work confirmed that hinge regions are located near regions of high frustration, which enables allosteric proteins to exhibit rare and large-amplitude fluctuations nearly up to the opposite state basin.143”
From Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell (2016) · cites this paper as [143]
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- Authors
- Li, W., Wolynes, P. G., & Takada, S.
- Affiliations
- Kyoto University (JP)
- University of California San Diego (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-02-09
- Volume
- 108
- Issue
- 9
- Pages
- 3504-3509
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3048140
- OpenAlex
- W2085928981
- Cited by
- 159
- References
- 38
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 10 · 2023: 4 · 2022: 5 · 2021: 10 · 2020: 7 · 2019: 17 · 2018: 7 · 2017: 12 · 2016: 8 · 2015: 14 · 2014: 16 · 2013: 15 · 2012: 13
- FWCI
- 6.76
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- American Institute for Contemporary German Studies
- Ministry of Education, Culture, Sports, Science and Technology
- Ministerio de Educación, Cultura y Deporte
- Center for Theoretical Biological Physics
- Japan Society for the Promotion of Science (22370057)
- National Institute of General Medical Sciences (R01 GM44 557, R01GM044557)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Keywords
- allosteric proteins, allosteric conformational change, sequence design, frustration, nonlinear interactions, energy landscape theory, coarse-grained models, multiscale modeling, adenylate kinase
- MeSH terms
- Adenylate Kinase, Allosteric Regulation, Amino Acid Sequence, Amino Acids, Protein Conformation, Proteins, Thermodynamics, Nonlinear Dynamics, Databases, Protein, Molecular Dynamics Simulation
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