Discovery of potential lumazine synthase antagonists for pathogens involved in bacterial meningitis: In silico study

• Main Authors: Manne Munikumar, Pradeep Natarajan, Umamaheswari Amineni, K.V. Radha Krishna
• Format: Article
• Language: English
• Published: Elsevier 2019-01-01
• Series: Informatics in Medicine Unlocked
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352914819300577

Bacterial meningitis, an infection of the membranes (meninges) and cerebrospinal fluid (CSF) surrounding the brain and spinal cord, is a major cause of death and disability worldwide. Streptococcus pneumonia, Neisseria meningitidis, Haemophilus influenzae type b and Staphylococcus aureus are the predominant pathogens of bacterial meningitis. In our previous study, we have identified lumazine synthase as a common drug target in pathogens of bacterial meningitis. The three dimensional (3D) structure of lumazine synthase complex with 5-nitro-6-ribityl-amino-2,4(1 h, 3 h)-pyrimidinedione (INI) was generated based on PDBID: 1RVV as a template using Modeller 9v12. Multiple docking strategies including rigid receptor docking (RRD), QPLD and IFD were performed for lumazine synthase with 29 existing inhibitors, and screened for 13050 ligands, respectively. Three stages of RRD (HTVS, SP, XP) were carried out using Glide v5.9 resulted in 134 leads. The 134 leads were compared to 29 inhibitors; eight best leads were obtained, which were further utilized for QPLD-MM-GBSA analysis. Eight compounds had a least docking score, lower binding free energy, and better binding orientation towards lumazine synthase. Furthermore, to analyse the stability of the lumazine synthase, the lead1 complex was subjected to 50 ns MD simulations and found to be stable. The results from multiple docking analysis and MD simulations affirmed that lead1 may be a promising inhibitor for efficient inhibition of lumazine synthase activity in common pathogens of bacterial meningitis. Keywords: Bacterial meningitis, Lumazine synthase, Rigid receptor docking, QM-Polarized ligand docking, Induced fit docking, Molecular dynamics simulations