2012
DOI: 10.22146/ijc.21354
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Construction and Optimization of Structure-Based Virtual Screening Protocols to Identify Cyclooxygenase-1 Inhibitors Using Open Babel, Spores and Plants

Abstract: Structure-Based Virtual Screening (SBVS) protocols to identify cyclooxygenase-1 (COX-1) inhibitors have been constructed and optimized based on their Root Mean

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Cited by 6 publications
(26 citation statements)
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“…The modification in the SBVS protocol was using three independent molecular docking simulations for each compound instead of one as performed in the initial SBVS protocol [8]. One of the advantages of using some more independent simulations is that we can sample more converged docking poses for every compounds although it increases the computing cost [27,[30][31]. Fig.…”
Section: Resultsmentioning
confidence: 99%
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“…The modification in the SBVS protocol was using three independent molecular docking simulations for each compound instead of one as performed in the initial SBVS protocol [8]. One of the advantages of using some more independent simulations is that we can sample more converged docking poses for every compounds although it increases the computing cost [27,[30][31]. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…The protocol was then challenged to redock the co-crystal ligands 4-hydroxytamoxifen in the ERα binding pocket [7] for 1000 times [27,31]. Remarkably, in all redocking simulations the protocol showed its ability to reproduce the co-crystal pose with RMSD values of < 2.00 Å.…”
Section: Resultsmentioning
confidence: 99%
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“…Open babel were used to perform stochastic conformational searches followed by energy minimizations to each cocrystallized ligand while the atom and bond types were assigned by SPORES. Followed by docking simulation by PLANTS1.2 using stochastic algorithm, will produce a completely non-deterministic docked pose of each reference ligand (12). The best docking poses of each cocrystallized ligand has RMSD values < 2Å as presented in Table 1.…”
Section: Resultsmentioning
confidence: 99%