Computational analysis of hypertrophic cardiomyopathy-associated proteins identified five novel post-translational modifications in MYH7 and MYBPC3, with prediction accuracy varying by tool.
Different machine learning tools vary in their precision for predicting PTMs in HCM-associated proteins, and five novel PTM sites in MYH7 and MYBPC3 were identified as high-priority candidates for experimental validation.
In this study, we have performed computational PTM analysis on a panel of hypertrophic cardiomyopathy (HCM)-associated proteins: MYH7, MYBPC3, TNNT2, and TNNI3. We aimed to benchmark the prediction of PTM sites of three ML-based tools: MusiteDeep, PTMGPT2, and SiteTack, using PhosphoSitePlus as a reference for true positives. Notably, because the highest precision tool varied by protein and PTM type, our results indicate there is no single best tool for PTM prediction. Specifically, for HCM-associated proteins, MusiteDeep had the highest precision for MYBPC3 and MYH7; PTMGPT2 was best for TNNI3, and SiteTack for TNNT2. Examining PTM type and phosphorylation in particular, MusiteDeep had the highest precision, followed by PTMGPT2 and SiteTack. However, MusiteDeep did not identify acetylation sites, where PTMGPT2 outperformed SiteTack. Beyond these benchmarking results, we also report on five high-priority candidates for experimental validation in two HCM-associated proteins: MYH7 (K1451 acetylation, K129 methylation) and MYBPC3 (T705 phosphorylation, K14 acetylation, R44 methylation).
Trajkovska et al. (2026) studied this question. Computational analysis of hypertrophic cardiomyopathy-associated proteins identified five novel post-translational modifications in MYH7 and MYBPC3, with prediction accuracy varying by tool.