Identification of Structurally Diverse Antimicrobials Through Sequential Application of Pharmacophore Modeling, Virtual Screening, Molecular Docking and In Vitro Microbiological Assay

Abstract Dihydrofolate reductase enzyme has been an attractive biological target for the design and development of antimicrobials. Considering this, we have attempted to identify novel dihydrofolate reductase inhibitors through our well-defined in silico and in vitro work flow. An accurate and predictive pharmacophore model comprising of one hydrogen bond acceptor, two hydrophobic and one ring aromatic was developed and utilized as a query to search the National Cancer Institute and Maybridge database leading to retrieval of various compounds which were filtered on the basis of estimated activity, fit value and Lipinski’s violation. Selected hits NSC3423, KM09759, NSC391, NSC2091 and HTS00630 were subjected to docking studies which resulted into visualization of potential interaction capabilities of hits in line to pharmacophoric features. The identified hits were evaluated for in vitro antimicrobial potential, and the results revealed that among all the five hits, NSC3423 is the most potent compound with activity against E. coli, P. aeruginosa, S. aureus, B. substilis, A. niger and F. oxysporum. On the other hand, KM09759, NSC391, NSC2091 and HTS00630 showed varying degree of activities against gram-positive, gram-negative and fungal strains.
Source: Interdisciplinary Sciences, Computational Life Sciences - Category: Bioinformatics Source Type: research