# Insilico exploration C. koseri ATP synthase inhibitors by pharmacophore-based virtual screening, molecular docking and MD simulation

## TL;DR

This study uses computational methods to find potential inhibitors of ATP synthase in Citrobacter koseri, a drug-resistant bacteria.

## Contribution

A pharmacophore-based virtual screening and molecular docking approach identifies novel ATP synthase inhibitors for C. koseri.

## Key findings

- Top compounds showed strong binding affinities ranging from -10.021 to -8.452 kcal/mol.
- MD simulations confirmed the stability of the top four compounds in the ATP synthase binding pocket.
- The study highlights targeting essential metabolic pathways to combat antibiotic-resistant bacteria.

## Abstract

Citrobacter koseri is a gram-negative rod that causes infections in people who have significant comorbidities and are immunocompromised. Antibiotic-resistant strains are becoming more common, which complicates infection treatment and highlights the need for innovative, effective drugs to fight these resistant strains. The enzyme complex ATP synthase participates in the adenosine triphosphate (ATP) synthesis, the fundamental energy currency of cells. This study used Computer-Aided Drug Design approaches to identify potential inhibitors of C. koseri ATP synthase. SWISS-MODEL was used to predict the 3D structure of C. koseri ATP synthase. A ligand-based pharmacophore model was developed using chemical features of ampicillin. Following ligand-based virtual screening across nine databases, the 2043 screened hits were docked to the ATP synthase active site using the standard precision mode of the glide tool. Based on their binding affinities, the top ten compounds were selected for additional investigation. The binding affinities of the chosen compounds ranged from -10.021 to -8.452 kcal/mol. The top four compounds (PubChem-25230613, PubChem-74936833, CHEMBL263035, PubChem-44208924) with the best ADMET characteristics and binding modes were chosen. Thus, the feasible binding mechanisms of the selected compounds were subjected to stability analysis using the MD Simulation study, which revealed the compounds’ stability as potent inhibitors within the protein binding pocket. This computational approach provides important insights into the rational design of novel therapeutics and emphasizes the importance of targeting essential metabolic pathways when combating antibiotic-resistant pathogens. Future experimental validation and optimization of the identified inhibitors is required to determine their efficacy and safety profiles for clinical use.