Identification of Potential Small Molecule Inhibitors against Selected Proteins of Neisseria Menningitidis in Silico

Abstract

Summary Meningitis is a disease that affects the central nervous system. It leads to inflammation of meninges that protect brain and spinalcord.The pathogenesis is supported by way of different biological processes i.e transcellularly or paracellularly.we identify the 19 theraputic small inhibitor against those proteins which is responsible for the virulence of the N. meningitidis. Out of 12 proteins two are hypothetical and structure of NspA is available in PDB. Remaining 9 are selected for the structure predication by using HHpread, Swiss model and ITASER. after the comperative assesment of predicted proteins based on the RAMPAGE and Qmin scale only 4 proteins give a positive result acording standerd criteria. Toal 5 protein docked with 40 ligand which have a antibiotic and anti microbial activity.Except polymyxin B due to their high molecular weight remaining 39 compounds successfully docked with all 5 targeted proteins. Successfully docked compound further analysed by Swiss ADME and molinspiration server foe ADME prediction. Those molecule which have a ability to inhibit the theraputic target proteins and follow the stadered criteria of ADME study i.e physioogical properties, lipophilicity, watersolubility , GI absorption, BBB penitration and CYP inhibitor. Our target is CNS because meningitis casue a inflamation in CNS. Selected drug must be pass through the BBB and follow the all criteria of ADME study. We generate two group for pharmacophore modeling one have a eight compound which have ability to penitrate BBB and second group consist 11 compound which do not have a ability to penitrate BBB butfollow the all criteria of ADME. Pharmacophore genration is done by using PharmaGist online server and give a result in based of highest scoring. pharmacophore of eleven ligand compound and eight ligand compounds. Pharmacophore model for eleven compounds out of eleven best score is 28.904 of three molecules Nalidixic acid, Norfloxacin and Levofloxacin. Ten molecules NalidixicAcid Sulbactam, ethambutol, Levofloxacin, Stavudine, Norfloxacin, Trimethoprim, Linezolid, Chloramphenicol, Ofloxacin gave score 12.728. Pharmacophore modeling for eight compounds out of eight best score 18.371 of three molecules Nevirapine, Voriconazole, Pyrimethamine. Eight molecules Nevirapine, Voriconazole, Praziquantel, 2BiarylCarbapenems, Trimipramine, Citalopram, Pyrimethamine, Efavirenz gave score 12.700.