Mebipred: identifying metal-binding potential in protein sequence.

ABSTRACT:

Motivation

metal-binding proteins have a central role in maintaining life processes. Nearly one-third of known protein structures contain metal ions that are used for a variety of needs, such as catalysis, DNA/RNA binding, protein structure stability, etc. Identifying metal-binding proteins is thus crucial for understanding the mechanisms of cellular activity. However, experimental annotation of protein metal-binding potential is severely lacking, while computational techniques are often imprecise and of limited applicability.

Results

we developed a novel machine learning-based method, mebipred, for identifying metal-binding proteins from sequence-derived features. This method is over 80% accurate in recognizing proteins that bind metal ion-containing ligands; the specific i

SUBMITTER: Aptekmann AA 

PROVIDER: S-EPMC9272798 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature