Functional proteins from a random-sequence library

By Anthony D. Keefe, J. Szostak. 2001

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How researchers see this paper

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The coming of age of de novo protein design (2016, background): “Functional folded proteins have been retrieved from random-sequence libraries 10–12 but this is a laborious (and non-systematic) process.”
Navigating the protein fitness landscape with Gaussian processes (2012, background): “Second, within this vast space, functional proteins are extremely scarce, with estimates that range from a high of 1 in 10 11 to as little as 1 in 10 77 (4, 5).”
Generative Models for Graph-Based Protein Design (2019, background): “Random protein sequences under these null models are unlikely to be functional without further selection [44].”
Natural protein sequences are more intrinsically disordered than random sequences (2016, background): “For example, only several functional proteins [12] resulted from initial 4 9 10 12 random sequences followed by many iterations of in vitro selections and directed evolution [13].”
Experimental assay of a fitness landscape on a macroevolutionary scale (2017, background): “Because the vast majority of mutations in protein sequences are deleterious 23 , a randomly sampled protein sequence is non-functional 28,29 .”