Identification of selective inhibitors for phosphodiesterase 5A using e-pharmacophore modelling and large-scale virtual screening-based structure guided drug discovery approaches

Arooma Maryam; Abdul Rauf Siddiqi; Sundeep Chaitanya Vedithi; Abdulilah Ece; Rana Rehan Khalid

doi:10.1080/07391102.2023.2242491

Identification of selective inhibitors for phosphodiesterase 5A using e-pharmacophore modelling and large-scale virtual screening-based structure guided drug discovery approaches

J Biomol Struct Dyn. 2023 Aug 6:1-16. doi: 10.1080/07391102.2023.2242491. Online ahead of print.

Authors

Arooma Maryam^{1

2

3

4}, Abdul Rauf Siddiqi¹, Sundeep Chaitanya Vedithi³, Abdulilah Ece⁴, Rana Rehan Khalid⁵

Affiliations

¹ Department of Biosciences, COMSATS University Islamabad (CUI), Islamabad, Pakistan.
² Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
³ Department of Biochemistry, University of Cambridge, Cambridge, UK.
⁴ Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Biruni University, Istanbul, Turkey.
⁵ National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan.

PMID: 37545162
DOI: 10.1080/07391102.2023.2242491

Abstract

The inhibition of Phosphodiesterase 5A (PDEA5) has the potential to modulate pulmonary arterial hypertension and cardiovascular diseases. Exploring the cross-reactivity of clinically available PDE5A therapeutics with PDE6A is intriguing in order to develop highly selective PDE5A compounds in cardiovascular arena. In the current study, we leveraged e-pharmacophore based screening and molecular dynamics (MD) simulation to discover more selective PDE5A inhibitors as compared to the PDE6A catalytic domain. e-Pharmacophore based mapping of the CoCoCo database (7 million compounds: ∼ 150,000,000 conformers), followed by Glide docking, MM-GBSA, and protein-inhibitor interaction analysis, revealed 1536427, 4832637 and 6788240 as stable, tight binders of PDE5A instead of PDE6A. These compounds adhere to Lipinski Rule of Five (RO5) and ADME/Tox criteria. MD simulations analysis showed that 1536427 stays stable and tightly binds to catalytic (Q-region) core of PDE5A catalytic domain as compared to sildenafil. Pronounced inward motions of the hydrophobic (H-region) and Lid region indicate the closure of PDE5A-1536427 complex, whereas this region in PDE6A-1536427 is more open. Significant differences in the interactions, stability, and dynamics of 1536427 were observed in the catalytic domain of PDE6A, demonstrating less specificity for PDE6A in comparison to PDE5A. After lead optimization and therapeutic interventions, this proposed lead may emerge as a promising PDE5A selective inhibitor.Communicated by Ramaswamy H. Sarma.

Keywords: ADMET; Cardiovascular diseases; MM-GBSA; Molecular Dynamics Simulation; pharmacophore-based-virtual screening; selective PDE5A inhibitors.