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In Silico Exploration of Vinca Domain Tubulin Inhibitors: A Combination of 3D‐QSAR‐Based Pharmacophore Modeling, Docking and Molecular Dynamics Simulations
Author(s) -
Lone Mohsin Y.,
Athar Mohd,
Manhas Anu,
Jha Prakash C.,
Bhatt Shruti,
Shah Anamik
Publication year - 2017
Publication title -
chemistryselect
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 34
ISSN - 2365-6549
DOI - 10.1002/slct.201701971
Subject(s) - pharmacophore , molecular dynamics , chemistry , quantitative structure–activity relationship , docking (animal) , in silico , stereochemistry , hydrogen bond , virtual screening , computational biology , computational chemistry , molecule , biochemistry , organic chemistry , biology , medicine , nursing , gene
A predictive ligand based quantitative pharmacophore model has been constructed to extract the essential features accountable for the inhibition of vinca domain inhibitors. To generate pharmacophore model a set of 23 functionally diverse training compounds was exploited by employing the Phase algorithm. The statistically significant ( R 2 =0.81, Q 2 =0.61, RMSE=0.63 and Pearson‐R=0.79) five feature pharmacophore model consist of one hydrogen‐bond acceptor, one hydrogen‐bond donor, a hydrophobic feature, one positive ionizable and a ring aromatic feature was chosen to screen the ZINC natural product database of IBScreen. The retreived hits were subjected to molecular docking examination by using FlexX . Furthermore, the dynamic behaviour and conformational features of the top scored docked molecule was envisioned via molecular dynamics simulations. The rationale behind the present work was to bid healthier perceptive about the binding of the tubulin inhibitors and abet in discovering new leads with potent antitumor activities.