Work

Report on the Post-Translational Modifications (PTMs) Prediction in Hypertrophic Cardiomyopathy-Associated Proteins MYH7, MYBPC3, TNNT2, and TNNI3, and Five Unknown PTMs in MYH7 (K129, K1451) and MYBPC3 (K14, R44, T705)

Year: 2026

Type: article

Abstract: 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).

Source: Cardiogenetics

DOI: 10.3390/cardiogenetics16020007

Authors: Natasha Trajkovska, Lenche Jovova, Done Stojanov

Institutions: University of Applied Sciences Upper Austria, Ss. Cyril and Methodius University in Skopje, Goce Delcev University

Language: English

Topic: Machine Learning in Bioinformatics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,689