Pharmacophore modeling, molecular docking and molecular dynamics simulation for screening and identifying anti-dengue phytocompounds

Vora J.;Patel S.;Athar M.

Second

Methodology

;Sinha S.;Chhabria M. T.;Jha P. C.;Shrivastava N.

2020-01-01

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Abstract

Dengue is a fast spreading mosquito borne viral disease that poses a serious threat to human health. Lack of therapeutic drugs and vaccines signify that more resources need to be explored. Accumulated evidence has suggested that plants offer a vast reservoir for antiviral drug discovery which are safe for human consumption. Plant-based drug discovery is a complex and time-consuming process as plants possess rich repository of chemically diverse compounds. Various in silico methods can make this process simple and economic. We, therefore, performed pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations and ADME (absorption, distribution, metabolism, excretion) prediction to screen potential candidates against dengue. In particular, combined pharmacophore mapping and molecular docking were used to prioritize the potentially active ligands from a ligand library. Biological activities of plant based ligands were predicted using 3D-QSAR pharmacophore modeling. Interaction between proteins, namely, envelope G protein, NS2B/NS3 protease, NS5 methyltransferase, NS1, NS5 polymerase and active plant-based ligands (pIC50 > 5.1) were analyzed using molecular docking. Best docked complex, namely, envelope G protein–mulberroside C, NS2B-NS3 protease–curcumin, NS5 methyltransferase–chebulic acid, NS1–mulberroside A, NS5 methyltransferase–punigluconin and NS5 methyltransferase–chebulic acid were further subjected to MD simulations study to assess the fluctuation and conformational changes during protein–ligand interaction. ADME studies were performed to assess their drug-likeness properties. Collectively, these in silico results helped to identify the potential plant-based hits against the various receptors of dengue virus which can be further validated by bioactivity-based experiments. Communicated by Ramaswamy H. Sarma.