Assessing predictions on fitness effects of missense variants in calmodulin

Jing Zhang, Lisa N. Kinch, Qian Cong, Panagiotis Katsonis, Olivier Lichtarge, Castrense Savojardo, Giulia Babbi, Pier Luigi Martelli, Emidio Capriotti, Rita Casadio, Aditi Garg, Debnath Pal, Jochen Weile, Song Sun, Marta Verby, Frederick P. Roth, Nick V. Grishin

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1463-1473
Number of pages11
JournalHuman mutation
Issue number9
StatePublished - Sep 1 2019


  • CAGI
  • calmodulin
  • disease
  • missense variants
  • predictors

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)


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