Identification of potential type 4 cAMP phosphodiesterase inhibitors via 3D pharmacophore modeling, virtual screening, DFT and structural bioisostere design
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Cyclic nucleotide phosphodiesterase Type 4 specifically metabolizes Cyclic Adenosine Monophosphate and has widespread distribution across the human body. The aim of this study was to generate a well-validated ligand-based 3D Quantitative Structure Activity Relationship pharmacophore model to identify potential phosphodiesterase Type 4 inhibitors using a set of 18 known chemically diverse phosphodiesterase Type 4 inhibitors. The HypoGen module of Discovery Studio v4.1 was used to generate the aforementioned pharmacophore model which was then employed as 3D query for virtual screening of four chemical and two natural product databases. The top hits were evaluated for their drug-like properties. The binding orientations of the best fits were predicted by molecular docking. Orbital energies were predicted for top hits and the density functional theory based minimum energy gap (Highest Occupied Molecular Orbital–Lowest Unoccupied Molecular Orbital gap) was used to further cull the selection and identify the most potential phosphodiesterase Type 4 inhibitors. Chemical similarity search was performed and structural analogs of the best hits were designed to discover novel potential phosphodiesterase Type 4 inhibitors. Use of Hypo1 as 3D query for virtual screening yielded 1243 compounds and subsequent molecular docking studies narrowed it down to 19 potential phosphodiesterase Type 4 inhibitors while a density functional theory-based study further culled this selection down to six most potential inhibitors. Six structurally diverse chemical structures with novel scaffolds and six analogs of the best hits were identified using pharmacophore modeling to be potential phosphodiesterase Type 4 inhibitors.
KeywordsPharmacophore PDE4 Molecular docking Virtual screening Quantitative structure-activity relationship Density function theory
Authors thankfully acknowledge Department of Biotechnology, Government of India for providing financial support for the Bioinformatics Infrastructure Facility (BIF) and the DBT e-library Consortium (DelCON) facility at the Centre for Biotechnology and Bioinformatics, Dibrugarh University in which the present work has been performed. The authors are also grateful to Dr. R. L. Bezbaruah, Chief Scientist (Retired) and Coordinator, BIF, CSIR-NEIST, Jorhat for his advice in the study. The Authors also thankful to Dr. Bulumoni Kalita, Assistant Professor, Department of Physics and Mr. Vishwa Jyoti Baruah, Assistant Professor, Centre for Biotechnology and Bioinformatics, Dibrugarh University for their valuable support in the present work.
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Conflict of Interests
The authors declares that they have no competing interests.
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