Accurate Identification and Mechanistic Evaluation of Pathogenic Missense Variants with <i>Rhapsody-2</i>.

ABSTRACT: Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here Rhapsody-2, a machine learning tool for discriminating pathogenic and neutral SAVs, significantly expanding on a precursor limited by the availability of structural data. With the advent of AlphaFold2 as a powerful tool for structure prediction, Rhapsody-2 is trained on a significantly expanded dataset of 117,525 SAVs corresponding to 12,094 human proteins reported in the ClinVar database. Adopting a broad set of descriptors composed of sequence evolutionary, structural, dynamic, and energetics features in the training algorithm, Rhapsody-2 achieved an AUROC of 0.94 i

SUBMITTER: Banerjee A 

PROVIDER: S-EPMC11870481 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature