Computational identification of potential lead molecules targeting rho receptor of Neisseria gonorrhoeae

Abstract

Gonorrhea, one of the sexually transmitted disease caused by a gram negative diplococcus bacteria Neisseria gonorrhoeae. Rho protein is indispensable for bacterial viability due to its versatile functions in physiology apart from RNA dependent transcription termination. Based on conserved function and wider role in several cellular processes, inhibitors specifically targeting Rho proteins are largely in use these days to treat various bacterial infections. In this study, three dimensional structure of Rho protein was modeled using the template protein from E. coli and further the optimized model was simulated for 100 ns to understand the structural stability and compactness. Owing to the therapeutic potential of Rho, traditional structure-based virtual screening was applied to identify potential inhibitors for the selected target. Based on empirical glide scoring functions two potent lead molecules (ChemBridge_6121956 and ChemBridge_5232688) were selected from ChemBridge database. The pharmacokinetic properties of these lead molecules are within the permissible range. DFT descriptor revealed that the lead molecules are more reactive, which also supports the molecular docking studies. The stability of Rho and Rho-inhibitor complexes was studied using molecular dynamics simulation. Parameters include binding free energy calculation, RMSD, RMSF and hydrogen bond analysis depicts the stability of Rho and Rho-inhibitors throughout the simulation. Altogether, the identified lead molecules require further optimization towards the design and development of new antibiotics against N. gonorrhoeae.

Communicated by Ramaswamy H. Sarma

Keywords:

• Neisseria gonorrhoeae
• Rho
• structure-based virtual screening
• DFT and molecular dynamics simulation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Acknowledgements

SR sincerely acknowledges MHRD-RUSA for financial assistance. RMV sincerely acknowledges University Grants Commission (UGC), New Delhi for providing Teaching faculty position to Department of Bioinformatics through Innovative program (No. F. 14-13/2013 (Inno/ASIST). JJ and RM thankfully acknowledge the DST-FIST [SR/FST/LSI-667/2016(C)], DST-PURSE [SR/PURSE Phase 2/38 (G)] and MHRD-RUSA 2.0 [F.24/51/2014-U, Policy (TNMulti-Gen), Dept. of Edn. Govt. of India] for the financial supports and infrastructure facilities.