ArticlePLoS computational biology2015
Systematic Mapping of Protein Mutational Space by Prolonged Drift Reveals the Deleterious Effects of Seemingly Neutral Mutations.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Redesign of energetically frustrated regions rescues function in defective T4 clamp loaders.Molecular biology and evolution · 2026Article
- Selective control of ligand binding through a distal mutation that alters the protein native ensemble.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Computational scoring and experimental evaluation of enzymes generated by neural networks.Nature biotechnology · 2025Article
- Enzyme-substrate co-display on yeast empowers engineering of tobacco etch virus protease activity.Protein engineering, design & selection : PEDS · 2025Article
- MMRT: MultiMut Recursive Tree for predicting functional effects of high-order protein variants from low-order variants.Computational and structural biotechnology journal · 2025Article
- Neutral drift upon threshold-like selection promotes variation in antibiotic resistance phenotype.Nature communications · 2024Article
- Sequence modeling and design from molecular to genome scale with Evo.Science (New York, N.Y.) · 2024Article
- Understanding epistatic networks in the B1 β-lactamases through coevolutionary statistical modeling and deep mutational scanning.Nature communications · 2024Article
- Unsupervised evolution of protein and antibody complexes with a structure-informed language model.Science (New York, N.Y.) · 2024Article
- A systematic analysis of regression models for protein engineering.PLoS computational biology · 2024Article
- Inverse folding of protein complexes with a structure-informed language model enables unsupervised antibody evolution.bioRxiv : the preprint server for biology · 2023Article
- ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction.bioRxiv : the preprint server for biology · 2023Article
- Developmental Selection and the Perception of Mutation Bias.Molecular biology and evolution · 2023Article
- A review of visualisations of protein fold networks and their relationship with sequence and function.Biological reviews of the Cambridge Philosophical Society · 2023Review
- Dan Tawfik's Lessons for Protein Engineers about Enzymes Adapting to New Substrates.Biochemistry · 2023Review
- Accurate prediction of functional effect of single amino acid variants with deep learning.Computational and structural biotechnology journal · 2023Article
- Intragenic compensation through the lens of deep mutational scanning.Biophysical reviews · 2022Review
- Phenotypic mutations contribute to protein diversity and shape protein evolution.Protein science : a publication of the Protein Society · 2022Review
- Mechanisms of protein evolution.Protein science : a publication of the Protein Society · 2022Review
- Inter-paralog amino acid inversion events in large phylogenies of duplicated proteins.PLoS computational biology · 2022Article
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systematic mappings of the effects of protein mutations are becoming increasingly popular. Unexpectedly, these experiments often find that proteins are tolerant to most amino acid substitutions, including substitutions in positions that are highly conserved in nature. To obtain a more realistic distribution of the effects of protein mutations, we applied a laboratory drift comprising 17 rounds of random mutagenesis and selection of M.HaeIII, a DNA methyltransferase. During this drift, multiple mutations gradually accumulated. Deep sequencing of the drifted gene ensembles allowed determination of the relative effects of all possible single nucleotide mutations. Despite being averaged across many different genetic backgrounds, about 67% of all nonsynonymous, missense mutations were evidently deleterious, and an additional 16% were likely to be deleterious. In the early generations, the frequency of most deleterious mutations remained high. However, by the 17th generation, their frequency was consistently reduced, and those remaining were accepted alongside compensatory mutations. The tolerance to mutations measured in this laboratory drift correlated with sequence exchanges seen in M.HaeIII's natural orthologs. The biophysical constraints dictating purging in nature and in this laboratory drift also seemed to overlap. Our experiment therefore provides an improved method for measuring the effects of protein mutations that more closely replicates the natural evolutionary forces, and thereby a more realistic view of the mutational space of proteins.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.