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PLoS Comput Biol DOI:10.1371/journal.pcbi.1009911

Characterization of intrinsically disordered regions in proteins informed by human genetic diversity.

Publication TypeJournal Article
Year of Publication2022
AuthorsAhmed, SS, Rifat, ZT, Lohia, R, Campbell, AJ, A Dunker, K, M Rahman, S, Iqbal, S
JournalPLoS Comput Biol
Volume18
Issue3
Pagese1009911
Date Published2022 03
ISSN1553-7358
KeywordsAmino Acid Sequence, Genetic Variation, Humans, Intrinsically Disordered Proteins, Protein Conformation, Proteome
Abstract

All proteomes contain both proteins and polypeptide segments that don't form a defined three-dimensional structure yet are biologically active-called intrinsically disordered proteins and regions (IDPs and IDRs). Most of these IDPs/IDRs lack useful functional annotation limiting our understanding of their importance for organism fitness. Here we characterized IDRs using protein sequence annotations of functional sites and regions available in the UniProt knowledgebase ("UniProt features": active site, ligand-binding pocket, regions mediating protein-protein interactions, etc.). By measuring the statistical enrichment of twenty-five UniProt features in 981 IDRs of 561 human proteins, we identified eight features that are commonly located in IDRs. We then collected the genetic variant data from the general population and patient-based databases and evaluated the prevalence of population and pathogenic variations in IDPs/IDRs. We observed that some IDRs tolerate 2 to 12-times more single amino acid-substituting missense mutations than synonymous changes in the general population. However, we also found that 37% of all germline pathogenic mutations are located in disordered regions of 96 proteins. Based on the observed-to-expected frequency of mutations, we categorized 34 IDRs in 20 proteins (DDX3X, KIT, RB1, etc.) as intolerant to mutation. Finally, using statistical analysis and a machine learning approach, we demonstrate that mutation-intolerant IDRs carry a distinct signature of functional features. Our study presents a novel approach to assign functional importance to IDRs by leveraging the wealth of available genetic data, which will aid in a deeper understating of the role of IDRs in biological processes and disease mechanisms.

DOI10.1371/journal.pcbi.1009911
Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/35275927?dopt=Abstract

Alternate JournalPLoS Comput Biol
PubMed ID35275927
PubMed Central IDPMC8942211