Lead generation of cysteine based mesenchymal epithelial transition (c-Met) kinase inhibitors: Using structure-based scaffold hopping, 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics simulation. (July 2022)

• Record Type: Journal Article
• Authors: Raafat, Asmaa; Mowafy, Samar; Abouseri, Sahar M.; Fouad, Marwa A.; Farag, Nahla A.
• Is Part Of: Computers in biology and medicine. Volume 146(2022)
• Publication Date: 2022-07
• Subjects: Anti-angiogenesis -- c-Met tyrosine kinase -- Discovery studio software -- Cabozantinib -- Lead optimization -- Scaffold hopping -- HypoGen algorithm -- Molecular docking -- Pharmacophore modeling; c-Met Cysteine-based mesenchymal–epithelial transition -- 3D-QSAR three dimensional-quantitative structure activity relationship -- RMSD root mean square deviation -- RMSF Root Mean Square Fluctuation -- MD molecular dynamics -- CADD Computer-aided drug design -- DS Discovery Studio -- HBD hydrogen bond donor -- HBA hydrogen bond acceptor -- PI positive ionizable -- RA ring aromatic -- HYP hydrophobic -- Hypo1 Hypothesis 1; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2022.105526
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Cysteine-based mesenchymal–epithelial transition (c-Met) is a receptor tyrosine kinase that plays a definitive role during cancer progression and was identified as a possible target for anti-angiogenesis drugs. In the present study, different protocols of computer-based drug design were performed. Construction of predictive pharmacophore model using HypoGen algorithm resulted in a validated model of four features of positive ionizable, hydrogen bond acceptor, hydrophobic, and ring aromatic features with a correlation coefficient of 0.87, a configuration cost of 14.95, and a cost difference of 357.92. The model revealed a promising predictive power and had >90% probability of representing true correlation with the activity data. The model was established using Fisher's validation test at the 95% confidence level and test set prediction (r = 0.96), furthermore, the model was validated by mapping of set of compounds undergoing clinical trials as class Ⅱ c-met inhibitors. The generated valid pharmacophore model was then anticipated for virtual screening of three data bases. Moreover, scaffold hopping using replace fragments protocol was implemented. Hits generated were filtered according to Lipinski's rule; 510 selected hits were anatomized and subjected to molecular docking studies into the crystal structure of c-Met kinase. The good correlation between docking scores and ligand pharmacophore mapping fit values provided a reliable foundation for designing new potentially active candidates that may target c-Met kinase. Eventually, eight hits were selected as potential leads. Subsequently, seven (Hits) have displayed a higher dock score and demonstrated key residue interactions with stable molecular dynamics simulation. Therefore, these c-Met kinase inhibitors may further serve as new chemical spaces in designing new compounds. Graphical abstract: Image 1 Highlights: C-Met is a receptor tyrosine kinase which is considered a novel target for potential anti-angiogenesis drugs. The validated model of C-Met had four pharmacophoric features one hydrogen bond Acceptor (HBA), one ring aromatic (RA), one positive ionizable (PI), and one hydrophobic (HYD) features. Scaffold hopping replace fragment protocol followed by mapping on the validated pharmacophore model was used. Virtual screening hits from were filtered according to Lipinski's rule and subjected to molecular docking studies into c-Met kinase to measure binding affinity and interactions with active site of C-Met inhibitors. Dynamic simulations studies supported our concept of design and validated the entire virtual screening approach; also, they emphasized and assured the potential inhibitory effect.