The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Why are proteins marginally stable?
Open accessAbstract
Most globular proteins are marginally stable regardless of size or activity. The most common interpretation is that proteins must be marginally stable in order to function, and so marginal stability represents the results of positive selection. We consider the issue of marginal stability directly using model proteins and the dynamical aspects of protein evolution in populations. We find that the marginal stability of proteins is an inherent property of proteins due to the high dimensionality of the sequence space, without regard to protein function. In this way, marginal stability can result from neutral, non‐adaptive evolution. By allowing evolving protein sub‐populations with different stability requirements for functionality to complete, we find that marginally stable populations of proteins tend to dominate. Our results show that functionalities consistent with marginal stability have a strong evolutionary advantage, and might arise because of the natural tendency of proteins towards marginal stability. Proteins 2002;46:105–109. © 2001 Wiley‐Liss, Inc.
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Cites
The genetical theory of natural selection
Fisher, R. A. (1930) · doi:10.5962/bhl.title.27468 · Cited by 17,617
The spandrels of San Marco and the Panglossian paradigm: a critique of the adaptationist programme
Gould, S. J., & Lewontin, R. C. (1979) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1979.0086 · Cited by 7,770 · cited 1×
“as an obvious adaptation to our need for spectacles and our legs as an adaptation for wearing trousers.(12) There has”
BackgroundContinuity in evolution: on the nature of transitions.
Fontana, W., & Schuster, P. (1998) · Science · doi:10.1126/science.280.5368.1451 · Cited by 456
Heteropolymer freezing and design: Towards physical models of protein folding
Pande, V. S., Grosberg, A. Y., & Tanaka, T. (2000) · Reviews of Modern Physics · doi:10.1103/revmodphys.72.259 · Cited by 284
Cited by
De novo design of potent and selective mimics of IL-2 and IL-15
Silva, D.-A., Yu, S., Ulge, U. Y., Spangler, J. B., Jude, K. M., Labão-Almeida, C., Ali, L. R., Quijano-Rubio, A., Ruterbusch, M., Leung, I., et al. (2019) · Nature · doi:10.1038/s41586-018-0830-7 · Cited by 531
Expanding functional protein sequence spaces using generative adversarial networks
Repecka, D., Jauniskis, V., Karpus, L., Rembeza, E., Rokaitis, I., Zrimec, J., Poviloniene, S., Laurynenas, A., Viknander, S., Abuajwa, W., et al. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00310-5 · Cited by 388
Navigating the protein fitness landscape with Gaussian processes
Romero, P. A., Krause, A., & Arnold, F. H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1215251110 · Cited by 360
Araya, C. L., Fowler, D. M., Chen, W., Muniez, I., Kelly, J. W., & Fields, S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1209751109 · Cited by 230
Evolution favors protein mutational robustness in sufficiently large populations
Bloom, J. D., Lu, Z., Chen, D., Raval, A., Venturelli, O. S., & Arnold, F. H. (2007) · BMC Biology · doi:10.1186/1741-7007-5-29 · Cited by 119
Metadata
- Authors
- Taverna, D. M., & Goldstein, R. A.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2001-11-27
- Volume
- 46
- Issue
- 1
- Pages
- 105-109
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W1992579032
- Cited by
- 373
- References
- 4
- FWCI
- 3.62
- Type
- journal article
- Language
- en
- Open access
- bronze
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