M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings.

ABSTRACT:

Motivation

Understanding metal-protein interaction can provide structural and functional insights into cellular processes. As the number of protein sequences increases, developing fast yet precise computational approaches to predict and annotate metal-binding sites becomes imperative. Quick and resource-efficient pre-trained protein language model (pLM) embeddings have successfully predicted binding sites from protein sequences despite not using structural or evolutionary features (multiple sequence alignments). Using residue-level embeddings from the pLMs, we have developed a sequence-based method (M-Ionic) to identify metal-binding proteins and predict residues involved in metal binding.

Results

On independent validation of recent proteins, M-Ionic reports an area under th

SUBMITTER: Shenoy A 

PROVIDER: S-EPMC10792727 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature