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Cited by 503

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On Some Principles Governing Molecular Evolution

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Kimura, Motoo, Ohta, Tomoko·1974·Proceedings of the National Academy of Sciences

Abstract

The following five principles were deduced from the accumulated evidence on molecular evolution and theoretical considerations of the population dynamics of mutant substitutions: ( i ) for each protein, the rate of evolution in terms of amino acid substitutions is approximately constant/site per year for various lines, as long as the function and tertiary structure of the molecule remain essentially unaltered. ( ii ) Functionally less important molecules or parts of a molecule evolve (in terms of mutant substitutions) faster than more important ones. ( iii ) Those mutant substitutions that disrupt less the existing structure and function of a molecule (conservative substitutions) occur more frequently in evolution than more disruptive ones. ( iv ) Gene duplication must always precede the emergence of a gene having a new function. ( v ) Selective elimination of definitely deleterious mutants and random fixation of selectively neutral or very slightly deleterious mutants occur far more frequently in evolution than positive Darwinian selection of definitely advantageous mutants.

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Metadata

Authors
Kimura, M., & Ohta, T.
Venue
Proceedings of the National Academy of Sciences
Published
1974-07
Volume
71
Issue
7
Pages
2848-2852
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2054017637
Cited by
503
References
2
FWCI
8.61
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: On Some Principles Governing Molecular Evolution. https://app.cochat.ai/papers/10.1073/pnas.71.7.2848
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Kimura, M., & Ohta, T. (1974). On Some Principles Governing Molecular Evolution. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.71.7.2848

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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.