Ankyrin repeats in context with human population variation

Javier S. Utgés,, Maxim I. Tsenkov, Noah J. M. Dietrich, Stuart A. MacGowan, Geoffrey J. Barton (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
103 Downloads (Pure)

Abstract

Ankyrin protein repeats bind to a wide range of substrates and are one of the most common protein motifs in nature. Here, we collate a high-quality alignment of 7,407 ankyrin repeats and examine for the first time, the distribution of human population variants from large-scale sequencing of healthy individuals across this family. Population variants are not randomly distributed across the genome but are constrained by gene essentiality and function. Accordingly, we interpret the population variants in context with evolutionary constraint and structural features including secondary structure, accessibility and protein-protein interactions across 383 three-dimensional structures of ankyrin repeats. We find five positions that are highly conserved across homologs and also depleted in missense variants within the human population. These positions are significantly enriched in intra-domain contacts and so likely to be key for repeat packing. In contrast, a group of evolutionarily divergent positions are found to be depleted in missense variants in human but significantly enriched in protein-protein interactions. Our analysis also suggests the domain has three, not two surfaces, each with different patterns of enrichment in protein-substrate interactions and missense variants. Our findings will be of interest to those studying or engineering ankyrin-repeat containing proteins as well as those interpreting the significance of disease variants.
Original languageEnglish
Article numbere1009335
Number of pages26
JournalPLoS Computational Biology
Volume17
Issue number8
Early online date24 Aug 2021
DOIs
Publication statusPublished - Aug 2021

ASJC Scopus subject areas

  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Cellular and Molecular Neuroscience
  • Molecular Biology
  • Ecology
  • Computational Theory and Mathematics
  • Modelling and Simulation

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