Comparative analysis of Rosetta stone events in Klebsiella pneumoniae and Streptococcus pneumoniae for drug target identification

• Main Authors: Poornima Ramesh, Jayashree Honnebailu Nagendrappa, Santosh Kumar Hulikal Shivashankara
• Format: Article
• Language: English
• Published: SpringerOpen 2021-06-01
• Series: Beni-Suef University Journal of Basic and Applied Sciences
• Subjects: Rosetta stones; Protein modeling; Drug target discovery; Virtual screening; Pneumonia; Protein domains
• Online Access: https://doi.org/10.1186/s43088-021-00126-7

Abstract Background Drug target identification is a fast-growing field of research in many human diseases. Many strategies have been devised in the post-genomic era to identify new drug targets for infectious diseases. Analysis of protein sequences from different organisms often reveals cases of exon/ORF shuffling in a genome. This results in the fusion of proteins/domains, either in the same genome or that of some other organism, and is termed Rosetta stone sequences. They help link disparate proteins together describing local and global relationships among proteomes. The functional role of proteins is determined mainly by domain-domain interactions and leading to the corresponding signaling mechanism. Putative proteins can be identified as drug targets by re-annotating their functional role through domain-based strategies. Results This study has utilized a bioinformatics approach to identify the putative proteins that are ideal drug targets for pneumonia infection by re-annotating the proteins through position-specific iterations. The putative proteome of two pneumonia-causing pathogens was analyzed to identify protein domain abundance and versatility among them. Common domains found in both pathogens were identified, and putative proteins containing these domains were re-annotated. Among many druggable protein targets, the re-annotation of EJJ83173 (which contains the GFO_IDH_MocA domain) showed that its probable function is glucose-fructose oxidoreduction. This protein was found to have sufficient interactor proteins and homolog in both pathogens but no homolog in the host (human), indicating it as an ideal drug target. 3D modeling of the protein showed promising model parameters. The model was utilized for virtual screening which revealed several ligands with inhibitory activity. These ligands included molecules documented in traditional Chinese medicine and currently marketed drugs. Conclusions This novel strategy of drug target identification through domain-based putative protein re-annotation presents a prospect to validate the proposed drug target to confer its utility as a typical protein targeting both pneumonia-causing species studied herewith.