3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors.
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.
DBT-Bioinformatics Infrastructure Facility, Centre for Biotechnology and Bioinformatics, School of Science and Engineering, Dibrugarh University, Dibrugarh, Assam, India.
Dhrubajyoti
D
Gogoi
DBT-Bioinformatics Infrastructure Facility, Centre for Biotechnology and Bioinformatics, School of Science and Engineering, Dibrugarh University, Dibrugarh, Assam, India.
Vishwa Jyoti
VJ
Baruah
DBT-Bioinformatics Infrastructure Facility, Centre for Biotechnology and Bioinformatics, School of Science and Engineering, Dibrugarh University, Dibrugarh, Assam, India.
Amrita Kashyap
AK
Chaliha
DBT-Bioinformatics Infrastructure Facility, Centre for Biotechnology and Bioinformatics, School of Science and Engineering, Dibrugarh University, Dibrugarh, Assam, India.
Bibhuti Bhushan
BB
Kakoti
Department of Chemistry, School of Science and Engineering, Dibrugarh University, Dibrugarh, Assam, India.
Diganta
D
Sarma
DBT-Bioinformatics Infrastructure Facility, Centre for Biotechnology and Bioinformatics, School of Science and Engineering, Dibrugarh University, Dibrugarh, Assam, India. Electronic address: alak@dibru.ac.in.
Alak Kumar
AK
Buragohain
D000465:Algorithms; D020134:Catalytic Domain; D019295:Computational Biology / Q000379:methods; D055808:Drug Discovery / Q000379:methods*; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D008024:Ligands; D008962:Models, Theoretical; D062105:Molecular Docking Simulation; D015394:Molecular Structure; D009369:Neoplasms / Q000188:drug therapy* / Q000378:metabolism; D047428:Protein Kinase Inhibitors / Q000737:chemistry / Q000378:metabolism / Q000494:pharmacology*; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism; D015203:Reproducibility of Results
D008024:Ligands; D047428:Protein Kinase Inhibitors; D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human
ADMET; DFT; Docking; HER2; Pharmacophore model