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Assessing predictions on fitness effects of missense variants in calmodulin
Author(s) -
Zhang Jing,
Kinch Lisa N.,
Cong Qian,
Katsonis Panagiotis,
Lichtarge Olivier,
Savojardo Castrense,
Babbi Giulia,
Martelli Pier Luigi,
Capriotti Emidio,
Casadio Rita,
Garg Aditi,
Pal Debnath,
Weile Jochen,
Sun Song,
Verby Marta,
Roth Frederick P.,
Grishin Nick V.
Publication year - 2019
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23857
Subject(s) - biology , missense mutation , calmodulin , genetics , computational biology , evolutionary biology , mutation , gene , biochemistry , enzyme
Abstract This paper reports the evaluation of predictions for the “CALM1” challenge in the fifth round of the Critical Assessment of Genome Interpretation held in 2018. In the challenge, the participants were asked to predict effects on yeast growth caused by missense variants of human calmodulin, a highly conserved protein in eukaryotic cells sensing calcium concentration. The performance of predictors implementing different algorithms and methods is similar. Most predictors are able to identify the deleterious or tolerated variants with modest accuracy, with a baseline predictor based purely on sequence conservation slightly outperforming the submitted predictions. Nevertheless, we think that the accuracy of predictions remains far from satisfactory, and the field awaits substantial improvements. The most poorly predicted variants in this round surround functional CALM1 sites that bind calcium or peptide, which suggests that better incorporation of structural analysis may help improve predictions.