Natural language processing in text mining for structural modeling of protein complexes.

ABSTRACT:

Background

Structural modeling of protein-protein interactions produces a large number of putative configurations of the protein complexes. Identification of the near-native models among them is a serious challenge. Publicly available results of biomedical research may provide constraints on the binding mode, which can be essential for the docking. Our text-mining (TM) tool, which extracts binding site residues from the PubMed abstracts, was successfully applied to protein docking (Badal et al., PLoS Comput Biol, 2015; 11: e1004630). Still, many extracted residues were not relevant to the docking.

Results

We present an extension of the TM tool, which utilizes natural language processing (NLP) for analyzing the context of the residue occurrence. The procedure was tested using

SUBMITTER: Badal VD 

PROVIDER: S-EPMC5838950 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature