Prediction of Protein Secondary Structures Based on Substructural Descriptors of Molecular Fragments.

ABSTRACT: The accurate prediction of secondary structures of proteins (SSPs) is a critical challenge in molecular biology and structural bioinformatics. Despite recent advancements, this task remains complex and demands further exploration. This study presents a novel approach to SSP prediction using atom-centric substructural multilevel neighborhoods of atoms (MNA) descriptors for protein molecular fragments. A dataset comprising over 335,000 SSPs, annotated by the Dictionary of Secondary Structure in Proteins (DSSP) software from 37,000 proteins, was constructed from Protein Data Bank (PDB) records with a resolution of 2 Å or better. Protein fragments were converted into structural formulae using the RDKit Python package and stored in SD files using the MOL V3000 format. Classification sequence-st

SUBMITTER: Zakharov OS 

PROVIDER: S-EPMC11641695 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature