ArticlePLoS computational biology2016
A New Take on John Maynard Smith's Concept of Protein Space for Understanding Molecular Evolution.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Maynard Smith's analogy, realized: Common ancestry constrains evolutionary percolation through protein space.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.Current medicinal chemistry · 2024Review
- A Genomic Conceptualization of Species.Journal of molecular evolution · 2023Article
- Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity.Protein science : a publication of the Protein Society · 2019Article
- Lexical Landscapes as large in silico data for examining advanced properties of fitness landscapes.PloS one · 2019Article
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Authors and funding
2 authors.
Funding
Abstract
Much of the public lacks a proper understanding of Darwinian evolution, a problem that can be addressed with new learning and teaching approaches to be implemented both inside the classroom and in less formal settings. Few analogies have been as successful in communicating the basics of molecular evolution as John Maynard Smith's protein space analogy (1970), in which he compared protein evolution to the transition between the terms WORD and GENE, changing one letter at a time to yield a different, meaningful word (in his example, the preferred path was WORD → WORE → GORE → GONE → GENE). Using freely available computer science tools (Google Books Ngram Viewer), we offer an update to Maynard Smith's analogy and explain how it might be developed into an exploratory and pedagogical device for understanding the basics of molecular evolution and, more specifically, the adaptive landscape concept. We explain how the device works through several examples and provide resources that might facilitate its use in multiple settings, ranging from public engagement activities to formal instruction in evolution, population genetics, and computational biology.
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