Abstract
MurI is one of the most significant role players in the biosynthesis of the peptidoglycan layer in Neisseria gonorrhoeae (Ng). We attempted to highlight the structural and functional relationship between Ng-MurI and D-glutamate to design novel molecules targeting this interaction. The three-dimensional (3D) model of the protein was constructed by homology modeling and the quality and consistency of generated model were assessed. The binding site of the protein was identified by molecular docking studies and a pharmacophore was identified using the interactions of the control ligand. The structure-based pharmacophore model was validated and employed for high-throughput virtual screening and molecular docking to identify novel Ng-MurI inhibitors. Finally, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with the substrate glutamate and novel molecules facilitated us to confirm the stability of the protein-ligand docked complexes. The 100 ns MD simulations of the potential lead compounds with protein confirmed that the modeled complexes were stable. This study identifies novel potential compounds with good fitness and docking scores, which made the interactions of biological significance within the protein active site. Hence, the identified compounds may act as new leads to design and develop Ng-MurI inhibitors.
Communicated by Ramaswamy H. Sarma
Acknowledgments
The authors highly acknowledge the support from the Department of Biotechnology, Govt. of India (Grant Number: BT/PR40153/BTIS/137/8/2021) for the Bioinformatics Centre (BIC) at Dr. B.R. Ambedkar Center for Biomedical Research. The authors also acknowledge ‘Bioinformatics Resources and Applications Facility (BRAF), C-DAC, Pune’ for providing server assistance. Ravi Kant gratefully acknowledges the Indian Council of Medical Research (ICMR) for awarding him the Senior Research Fellowship (Grant Number: HIV/STI/17/02/2022-ECD-II). Prakash Jha would like to thank the Department of Science and Technology, Government of India for awarding him the DST-INSPIRE fellowship (Grant Number: DST/INSPIRE/03/2016/000026).
Disclosure statement
The authors declare that there is no conflict of interest.
Authors’ contribution statement
Conceptualization: Ravi Kant, Daman Saluja, and Madhu Chopra. Methodology: Ravi Kant, Prakash Jha, Daman Saluja, and Madhu Chopra. Software: Ravi Kant, and Prakash Jha. Formal Analysis: Ravi Kant, and Prakash Jha. Data Curation: Ravi Kant, and Prakash Jha. Writing original draft: Ravi Kant, Prakash Jha, Daman Saluja, and Madhu Chopra. Writing—review, and editing: Daman Saluja, and Madhu Chopra. Supervision: Daman Saluja, and Madhu Chopra.
Data availability statement
Data is available upon request to the corresponding author.