Pharmacophore modeling, atom based 3D-QSAR, molecular docking and molecular dynamics studies on Escherichia coli ParE inhibitors. (February 2020)

• Record Type: Journal Article
• Authors: Azam, Mohammed Afzal; Thathan, Janarthanan; Jupudi, Srikanth
• Is Part Of: Computational biology and chemistry. Volume 84(2020)
• Publication Date: 2020-02
• Subjects: ATP Adenosine triphosphate -- BEDROC Boltzmann-Enhanced Discrimination of ROC plots -- Ecoul Coulomb energy -- EF Enrichment factor -- Gscore Glide score -- Glide emodel Glide energy model -- MD Molecular dynamics -- MM-GBSA Molecular mechanics-generalized born surface area -- OPLS Optimized potentials for liquid simulations -- PSA Polar surface area -- PDB Protein data bank -- rGyr Radius of gyraion -- ROC Receiver operator characteristic -- AUC Area under curve -- RMSD Root mean square deviation -- SASA Solvent accessible surface area -- vdW Van der Waals; ParE inhibitors -- Pharmacophore modeling -- Extra-precision docking -- Binding free energy -- HTVS -- Molecular dynamics; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2019.107197
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: A highly predictive five-point 3D-QSAR model AADHR.187 was developed. Model was validated by the external data set and enrichment study. We identified five potential hits against E. coli ParE by in silico pharmacophore-based HTVS. 30 ns MD simulation was performed to validate the docking pose. Three new molecules have been proposed having high binding affinity for E. coli ParE enzyme. Abstract: ATP dependent ParE enzyme is as an attractive target for the development of antibacterial agents. Atom based 3D-QSAR model AADHR.187 was developed based on the thirty eight Escherichia coli ParE inhibitors. The generated model showed statistically significant coefficient of determinations for the training (R 2 = 0.985) and test (R 2 = 0.86) sets. The cross-validated correlation coefficient (q2) was 0.976. The utility of the generated model was validated by the enrichment study. The model was also validated with structurally diverse external test set of ten compounds. Contour plot analysis of the generated model unveiled the chemical features necessary for the E. coli ParE enzyme inhibition. Extra-precision docking result revealed that hydrogen bonding and ionic interactions play a major role in ParE protein-ligand binding. Binding free energy was computed for the data set inhibitors to validate the binding affinity. A 30-ns molecular dynamics simulation showed high stability and effective binding of inhibitor 34 within the active site of ParE enzyme. Using the best fitted model AADHR.187, pharmacophore-based high-throughput virtual screening was performed to identify virtual hits. Based on the above studies three new molecules are proposed as E. coli ParE inhibitors with high binding affinity and favourable ADME properties.