Annotating Cancer-Related Variants at Protein-Protein Interface with Structure-PPi

Methods Mol Biol. 2022:2493:315-330. doi: 10.1007/978-1-0716-2293-3_20.

Abstract

A comprehensive analysis of germline and somatic variants requires complex computational approaches that combine next-generation sequencing (NGS)-based omics data with curated annotations from public repositories. Here, we describe Structure-PPi, which facilitates the analysis of cancer-related variants onto protein 3D structures, interaction interfaces, and other important functional sites (i.e., catalytic, ligand-binding, posttranslational modification). Our approach relies on features extracted from Interactome3D, UniProtKB, InterPro, APPRIS, dbNSFP, and COSMIC databases and provides complementary information to pathogenicity prediction methods. Thus, Structure-PPi helps in the discrimination of false-positive predictions and adds both mechanistic and biological insights into the role of variants in a given cancer. An online version of the tools is available at https://rbbt.bsc.es/StructurePPI/ .

Keywords: 3D structure analysis; Cancer mutations; Protein isoforms; Protein–protein interactions; Rbbt workflows; Variants prioritization.

MeSH terms

  • Computational Biology / methods
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Neoplasms* / genetics
  • Proteins* / genetics

Substances

  • Proteins