3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors. (21st December 2016)

• Record Type: Journal Article
• Authors: Gogoi, Dhrubajyoti; Baruah, Vishwa Jyoti; Chaliha, Amrita Kashyap; Kakoti, Bibhuti Bhushan; Sarma, Diganta; Buragohain, Alak Kumar
• Is Part Of: Journal of theoretical biology. Volume 411(2016)
• Page Start: 68
• Page End: 80
• Publication Date: 2016-12-21
• Subjects: Pharmacophore model -- HER2 -- ADMET -- Docking -- DFT; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2016.09.016
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract: Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating ( r =0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques. Highlights: 3D ligand-based Pharmacophore modeling developed for identifying Human Epidermal Growth factor Receptor 2 (HER2) inhibitors. Pharmacophore validation and evaluation was performed based on established techniques. Pharmacophore-based virtual screening was applied to retrieve potent HER2 inhibitors from four databases. Studies on Molecular interactions and Binding orientation were performed by Molecular Docking analysis. Electronic properties and charge transfer of best hits identified through docking was analysed by DFT.