cpxDeepMSA: A Deep Cascade Algorithm for Constructing Multiple Sequence Alignments of Protein–Protein Interactions

• Published in: International journal of molecular sciences Vol. 23; no. 15; p. 8459
• Main Authors: Liu, Zi, Yu, Dong-Jun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 30.07.2022; MDPI
• Subjects: Accuracy; Algorithms; Amino acid sequence; Binding sites; Biological activity; Coevolution; Construction; Genomes; genomic distance; Methods; multiple sequence alignment; Nucleotide sequence; Phylogeny; phylogeny information; protein complex; Protein interaction; Protein structure; Proteins; protein–protein interactions; Residues; Sequence analysis; Software; STRING interaction network; Taxonomy
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms23158459

Protein–protein interactions (PPIs) are fundamental to many biological processes. The coevolution-based prediction of interacting residues has made great strides in protein complexes that are known to interact. A multiple sequence alignment (MSA) is the basis of coevolution analysis. MSAs have recently made significant progress in the protein monomer sequence analysis. However, no standard or efficient pipelines are available for the sensitive protein complex MSA (cpxMSA) collection. How to generate cpxMSA is one of the most challenging problems of sequence coevolution analysis. Although several methods have been developed to address this problem, no standalone program exists. Furthermore, the number of built-in properties is limited; hence, it is often difficult for users to analyze sequence coevolution according to their desired cpxMSA. In this article, we developed a novel cpxMSA approach (cpxDeepMSA. We used different protein monomer databases and incorporated the three strategies (genomic distance, phylogeny information, and STRING interaction network) used to join the monomer MSA results of protein complexes, which can prevent using a single method fail to the joint two-monomer MSA causing the cpxMSA construction failure. We anticipate that the cpxDeepMSA algorithm will become a useful high-throughput tool in protein complex structure predictions, inter-protein residue-residue contacts, and the biological sequence coevolution analysis.