Assessing predictions on fitness effects of missense variants in calmodulin. Issue 9 (3rd September 2019)

• Record Type: Journal Article
• Authors: 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.
• Editors: Moult, John; Brenner, Steven E.
• Other Names: Karchin Rachel guestEditor.; Pal Lipika R. specialEditor.
• Is Part Of: Human mutation. Volume 40:Issue 9(2019)
• Page Start: 1463
• Page End: 1473
• Publication Date: 2019-09-03
• Subjects: CAGI -- calmodulin -- disease -- missense variants -- predictors; Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.23857
• Languages: English
• ISSNs: 1059-7794

Abstract

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.