Abstract
Background: Various challenges exist in the treatment of infectious diseases due to the significant rise in drug resistance, resulting in the failure of antibiotic treatment. As a consequence, a dire need has arisen for the rethinking of the drug discovery cycle because of the challenge of drug resistance. The underlying cause of the infectious diseases depends upon associations within the Host-pathogen Protein- Protein Interactions (HP-PPIs) network, which represents a key to unlock new pathogenesis mechanisms. Hence, the elucidation of significant PPIs is a promising approach for the identification of potential drug targets. Objective: Identification of the most significant HP-PPIs and their partners, and targeting them to prioritize potential new drug targets against Vancomycin-resistant Enterococcus faecalis (VRE). Methods: We applied a computational approach based on one of the emerging techniques i.e. Interolog methodology to predict the significant Host-Pathogen PPIs. Structure-Based Studies were applied to model shortlisted protein structures and validate them through PSIPRED, PROCHECK, VERIFY3D, and ERRAT tools. Furthermore, 18,000 drug-like compounds from the ZINC library were docked against these proteins to study protein-chemical interactions using the AutoDock based molecular docking method. Results: The study resulted in the identification of 118 PPIs for Enterococcus faecalis, and prioritized two novel drug targets i.e. Exodeoxyribonuclease (ExoA) and ATP-dependent Clp protease proteolytic subunit (ClpP). Consequently, the docking program ranked 2,670 and 3,154 compounds as potential binders against Exodeoxyribonuclease and ATP-dependent Clp protease proteolytic subunit, respectively. Conclusion: Thereby, the current study enabled us to identify and prioritize potential PPIs in VRE and their interacting proteins in human hosts along with the pool of novel drug candidates.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.