The DOI matches its Crossref record.
Natural Selection and the Concept of a Protein Space
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Adaptation on Rugged Landscapes
Levinthal, D. A. (1997) · Management Science · doi:10.1287/mnsc.43.7.934 · Cited by 2,254
Enzyme promiscuity: A mechanistic and evolutionary perspective
Tawfik, O. K. A. D. S. (2010) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-030409-143718 · Cited by 1,355
Machine-learning-guided directed evolution for protein engineering
Yang, K. K., Wu, Z., & Arnold, F. H. (2019) · Nature Methods · doi:10.1038/s41592-019-0496-6 · Cited by 1,130
Greaney, A. J., Starr, T. N., Gilchuk, P., Zost, S. J., Binshtein, E., Loes, A. N., Hilton, S. K., Huddleston, J., Eguia, R., Crawford, K. H. D., et al. (2021) · Cell Host & Microbe · doi:10.1016/j.chom.2020.11.007 · Cited by 1,016
Domingo, E., Sheldon, J., & Perales, C. (2012) · Microbiology and Molecular Biology Reviews · doi:10.1128/mmbr.05023-11 · Cited by 1,009
Simulating 500 million years of evolution with a language model
Hayes, T., Rao, R., Akin, H., Sofroniew, N. J., Oktay, D., Lin, Z., Verkuil, R., Tran, V. Q., Deaton, J., Wiggert, M., et al. (2025) · Science · doi:10.1126/science.ads0018 · Cited by 937
Autocatalytic sets of proteins
Kauffman, S. A. (1986) · Journal of Theoretical Biology · doi:10.1016/s0022-5193(86)80047-9 · Cited by 741
Empirical fitness landscapes and the predictability of evolution
de Visser, J. A. G. M., & Krug, J. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3744 · Cited by 715
Enzyme promiscuity: evolutionary and mechanistic aspects
Khersonsky, O., Roodveldt, C., & Tawfik, D. S. (2006) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2006.08.011 · Cited by 641
Illuminating protein space with a programmable generative model
Ingraham, J. B., Baranov, M., Costello, Z., Barber, K. W., Wang, W., Ismail, A., Frappier, V., Lord, D. M., Ng-Thow-Hing, C., Van Vlack, E. R., et al. (2023) · Nature · doi:10.1038/s41586-023-06728-8 · Cited by 444
One sequence, two ribozymes: implications for the emergence of new ribozyme folds
Schultes, E. A., & Bartel, D. P. (2000) · Science · doi:10.1126/science.289.5478.448 · Cited by 364
The molecular basis of phenotypic convergence
Rosenblum, E. B., Parent, C. E., & Brandt, E. E. (2014) · Annual Review of Ecology, Evolution, and Systematics · doi:10.1146/annurev-ecolsys-120213-091851 · Cited by 256
Nowak, M. A. (1992) · Trends in Ecology & Evolution · doi:10.1016/0169-5347(92)90145-2 · Cited by 192
Comprehensive experimental fitness landscape and evolutionary network for small RNA
Jiménez, J. I., Xulvi-Brunet, R., Campbell, G. W., Turk-MacLeod, R., & Chen, I. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1307604110 · Cited by 140
Real ribozymes suggest a relaxed error threshold
Kun, Á., Santos, M., & Szathmáry, E. (2005) · Nature Genetics · doi:10.1038/ng1621 · Cited by 151
Evolution of sodium channels predates the origin of nervous systems in animals
Liebeskind, B. J., Hillis, D. M., & Zakon, H. H. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1106363108 · Cited by 149
Historical contingency and its biophysical basis in glucocorticoid receptor evolution
Harms, M. J., & Thornton, J. W. (2014) · Nature · doi:10.1038/nature13410 · Cited by 147
Katsonis, P., & Lichtarge, O. (2014) · Genome Research · doi:10.1101/gr.176214.114 · Cited by 137
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
Evolution of DNA specificity in a transcription factor family produced a new gene regulatory module
McKeown, A. N., Bridgham, J. T., Anderson, D. W., Murphy, M. N., Ortlund, E. A., & Thornton, J. W. (2014) · Cell · doi:10.1016/j.cell.2014.09.003 · Cited by 107
Computational scoring and experimental evaluation of enzymes generated by neural networks
Johnson, S. R., Fu, X., Viknander, S., Goldin, C., Monaco, S., Zelezniak, A., & Yang, K. K. (2025) · Nature Biotechnology · doi:10.1038/s41587-024-02214-2 · Cited by 99
Protein codes promote selective subcellular compartmentalization
Kilgore, H. R., Chinn, I., Mikhael, P. G., Mitnikov, I., Van Dongen, C., Zylberberg, G., Afeyan, L., Banani, S. F., Wilson-Hawken, S., Lee, T. I., et al. (2025) · Science · doi:10.1126/science.adq2634 · Cited by 99
Manrubia, S., Cuesta, J. A., Aguirre, J., Ahnert, S. E., Altenberg, L., Cano, A. V., Catalán, P., Diaz-Uriarte, R., Elena, S. F., García-Martín, J. A., et al. (2021) · Physics of Life Reviews · doi:10.1016/j.plrev.2021.03.004 · Cited by 88
How much of protein sequence space has been explored by life on Earth?
Dryden, D. T. F., Thomson, A. R., & White, J. H. (2008) · Journal of The Royal Society Interface · doi:10.1098/rsif.2008.0085 · Cited by 85
“Finally, we conclude that the number 20100 and similar large numbers (e.g. Salisbury 1969; Maynard Smith 1970; Mandecki 1998; Luisi 2003; Carrier 2004; de Duve 2005) are simply ‘straw men’ advanced to initiate discussion in the same spirit as the ‘Levinthal paradox’ of protein folding rates (Levinthal 1969; Zwanzig et…”
BackgroundInfluentialIlluminating protein space with a programmable generative model
Ingraham, J., Baranov, M., Costello, Z., Frappier, V., Ismail, A., Tie, S., Wang, W., Xue, V., Obermeyer, F., Beam, A., et al. (2022) · doi:10.1101/2022.12.01.518682 · Cited by 83
Error Thresholds in Genetic Algorithms
Ochoa, G. (2006) · Evolutionary Computation · doi:10.1162/evco.2006.14.2.157 · Cited by 71
Invariance and Meaningfulness in Phenotype spaces
Huttegger, S. M., & Mitteroecker, P. (2011) · Evolutionary Biology · doi:10.1007/s11692-011-9123-x · Cited by 64
Molecular Crowding and Early Evolution
Saha, R., Pohorille, A., & Chen, I. A. (2014) · Origins of Life and Evolution of Biospheres · doi:10.1007/s11084-014-9392-3 · Cited by 52
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
Li, F.-Z., Amini, A. P., Yue, Y., Yang, K. K., & Lu, A. X. (2024) · doi:10.1101/2024.02.05.578959 · Cited by 51
Evolutionary innovations and the organization of protein functions in genotype space
Ferrada, E., & Wagner, A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0014172 · Cited by 51
The standard genetic code enhances adaptive evolution of proteins
Zhu, W., & Freeland, S. (2006) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2005.07.012 · Cited by 44
On the networked architecture of genotype spaces and its critical effects on molecular evolution
Aguirre, J., Catalán, P., Cuesta, J. A., & Manrubia, S. (2018) · Open Biology · doi:10.1098/rsob.180069 · Cited by 44
Massey, S. (2015) · Life · doi:10.3390/life5021301 · Cited by 38
Brown, B. P., Stein, R. A., Meiler, J., & Mchaourab, H. S. (2024) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c01081 · Cited by 41
The genetic code constrains yet facilitates Darwinian evolution
Firnberg, E., & Ostermeier, M. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt536 · Cited by 36
Adaptive multiscapes: an up-to-date metaphor to visualize molecular adaptation
Catalán, P., Arias, C. F., Cuesta, J. A., & Manrubia, S. (2017) · Biology Direct · doi:10.1186/s13062-017-0178-1 · Cited by 36
Experimental fitness landscapes to understand the molecular evolution of RNA-based life
Athavale, S. S., Spicer, B., & Chen, I. A. (2014) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2014.09.008 · Cited by 25
Ramasamy, P., Zuallaert, J., Martens, L., & Vranken, W. F. (2026) · Protein Science · doi:10.1002/pro.70376 · Cited by 15
The simple emergence of complex molecular function
Manrubia, S. (2022) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2020.0422 · Cited by 13
Investigating the determinants of performance in machine learning for protein fitness prediction
Sandhu, M., Mater, A. C., Matthews, D. S., Spence, M. A., Lenskiy, A. A., & Jackson, C. (2020) · doi:10.1101/2020.09.30.319780 · Cited by 8
Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters
Crandall, J. G., Zhou, X., Rokas, A., & Hittinger, C. T. (2024) · Molecular Biology and Evolution · doi:10.1093/molbev/msae228 · Cited by 7
Investigating the determinants of performance in machine learning for protein fitness prediction
(2025) · doi:10.1002/pro.70235 · Cited by 6
Metadata
- Authors
- MAYNARD SMITH, J.
- Venue
- Nature
- Published
- 1970-02
- Volume
- 225
- Issue
- 5232
- Pages
- 563-564
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1992613346
- Cited by
- 922
- References
- 0
- FWCI
- 2.38
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.