Abstract
Target based virtual screening has surpassed ligand based virtual screening methods in the recent past mainly as it provides more clues regarding intermolecular interactions and takes into consideration the flexible receptor as well. The current methodology describes a computational strategy of predicting Mycobacterium tuberculosis (M. tuberculosis) binders for five well studied targets representing M. tuberculosis proteome encompassing most of the known mechanisms of action. The diversity of the targets was affirmed by their active site analysis and structural studies. The current approach employed pharmacophore searching, docking and clustering techniques in tandem and was validated by enrichment studies using the available Schrödinger data set consisting of 1000 decoys. The application of this methodology was demonstrated by predicting potential molecular targets for fifty newly synthesized compounds. Cross docking studies on the targets were carried out with 4512 known inhibitors utilizing a high performance computing platform to reveal underlying affinity and promiscuity patterns. Optimum binding energy range for all targets as determined by high throughput docking was found to be -3 to -13 kcal/mol.
Keywords: Binding energy, docking, Mycobacterium tuberculosis, open source drug discovery (OSDD), pharmacophore, structure based drug design (SBDD).
Combinatorial Chemistry & High Throughput Screening
Title:Pharmacophore and Docking Based Virtual Screening of Validated Mycobacterium tuberculosis Targets
Volume: 18 Issue: 7
Author(s): Renu Vyas, Muthukumarasamy Karthikeyan, Ganesh Nainaru and Murugan Muthukrishnan
Affiliation:
Keywords: Binding energy, docking, Mycobacterium tuberculosis, open source drug discovery (OSDD), pharmacophore, structure based drug design (SBDD).
Abstract: Target based virtual screening has surpassed ligand based virtual screening methods in the recent past mainly as it provides more clues regarding intermolecular interactions and takes into consideration the flexible receptor as well. The current methodology describes a computational strategy of predicting Mycobacterium tuberculosis (M. tuberculosis) binders for five well studied targets representing M. tuberculosis proteome encompassing most of the known mechanisms of action. The diversity of the targets was affirmed by their active site analysis and structural studies. The current approach employed pharmacophore searching, docking and clustering techniques in tandem and was validated by enrichment studies using the available Schrödinger data set consisting of 1000 decoys. The application of this methodology was demonstrated by predicting potential molecular targets for fifty newly synthesized compounds. Cross docking studies on the targets were carried out with 4512 known inhibitors utilizing a high performance computing platform to reveal underlying affinity and promiscuity patterns. Optimum binding energy range for all targets as determined by high throughput docking was found to be -3 to -13 kcal/mol.
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Cite this article as:
Vyas Renu, Karthikeyan Muthukumarasamy, Nainaru Ganesh and Muthukrishnan Murugan, Pharmacophore and Docking Based Virtual Screening of Validated Mycobacterium tuberculosis Targets, Combinatorial Chemistry & High Throughput Screening 2015; 18 (7) . https://dx.doi.org/10.2174/1386207318666150703112759
DOI https://dx.doi.org/10.2174/1386207318666150703112759 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
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