10.6084/m9.figshare.5579725 D. K. Behera D. K. Behera P. M. Behera P. M. Behera L. Acharya L. Acharya A. Dixit A. Dixit Pharmacophore modelling, virtual screening and molecular docking studies on PLD1 inhibitors Taylor & Francis Group 2017 Influenza phospholipase D pharmacophore modelling 3D QSAR virtual screening molecular docking 2017-11-08 09:20:00 Dataset https://tandf.figshare.com/articles/dataset/Pharmacophore_modelling_virtual_screening_and_molecular_docking_studies_on_PLD1_inhibitors/5579725 <p>Lipid metabolism plays a significant role in influenza virus replication and subsequent infection. The regulatory mechanism governing lipid metabolism and viral replication is not properly understood to date, but both Phospholipase D (PLD1 and PLD2) activities are stimulated in viral infection. <i>In vitro</i> studies indicate that chemical inhibition of PLD1 delays viral entry and reduction of viral loads. The current study reports a three-dimensional pharmacophore model based on 35 known PLD1 inhibitors. A sub-set of 25 compounds was selected as the training set and the remaining 10 compounds were kept in the test set. One hundred and twelve pharmacophore models were generated; a six-featured pharmacophore model (AADDHR.57) with survival score (2.69) produced a statistically significant three-dimensional quantitative structure–activity relationship model with <i>r</i><sup>2</sup> = 0.97 (internal training set), <i>r</i><sup>2</sup> = 0.71 (internal test set) and <i>Q</i><sup>2</sup> = 0.64. The predictive power of the pharmacophore model was validated with an external test set (<i>r</i><sup>2</sup> = 0.73) and a systematic virtual screening work-flow was employed showing an enrichment factor of 23.68 at the top 2% of the dataset (active and decoys). Finally, the model was used for screening of the filtered PubChem database to fetch molecules which can be proposed as potential PLD1 inhibitors for blocking influenza infection.</p>