Suvaiyarasan Suvaithenamudhan and Subbiah Parthasarathy* Pages 234 - 248 ( 15 )
Background: Top five best hit compounds (ZINC59376795, ZINC60175365, ZINC36922620, ZINC39550705 and ZINC36953975) were obtained through our high throughput virtual screening (HTVS) analysis with resistant 5204-PBP2B (5204 Penicillin Binding Protein 2B) and sensitive R6-PBP2B (R6 Penicillin Binding Protein 2B) proteins of Streptococcus pneumoniae. Objective: To gain insight in molecular docking and dynamics simulations of these top five best hit compounds with both resistant 5204-PBP2B and sensitive R6-PBP2B targets.Methods: We have employed Glide XP docking and molecular dynamics simulations of these five best hit compounds with 5204-PBP2B and R6-PBP2B targets. The stability analysis has been carried out through DFT, prime-MM/GBSA binding free energy, RMSD, RMSF and Principal Component Analysis. Results: The reference drug, penicillin G forms stable complex with sensitive R6-PBP2B protein. Similar stability is observed for the mutant resistant 5204-PBP2B with the top scoring compound ZINC592376795 which implies that this compound may act as an effective potential inhibitor. The compound ZINC59376795 forms a total of five hydrogen bonds with resistant 5204-PBP2B protein of which three are with mutated residues. Similarly, the other four compounds including penicillin G also form hydrogen bonds with mutated residue. The MD simulations and stability analysis of the complexes of wild and mutant forms are evaluated for a trajectory period of 16ns and further MD simulations of ZINC59376795 with resistant 5204-PBP2B and sensitive R6-PBP2B confirmed the stability for 50 ns. Conclusion: These results suggest that the top five best hit compounds are found to be a promising gateway for the further development of anti-pneumococcal therapeutics.
Glide docking, molecular dynamics simulation, penicillin G, penicillin binding protein 2B, Streptococcus pneumoniae, resistant 5204 strain, sensitive R6 strain.
Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli – 620 024, Tamil Nadu, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli – 620 024, Tamil Nadu