Structure-Based Virtual Screening and Molecular Dynamics Simulation Assessments of Depsidones as Possible Selective Cannabinoid Receptor Type 2 Agonists

Author:

Mohamed Gamal A.1ORCID,Omar Abdelsattar M.23ORCID,AlKharboush Dana F.2ORCID,Fallatah Mona A.24,Sindi Ikhlas A.5,El-Agamy Dina S.6,Ibrahim Sabrin R. M.78ORCID

Affiliation:

1. Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia

2. Department of Pharmaceutical Chemistry, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia

3. Center for Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah 21589, Saudi Arabia

4. King Abdulaziz Medical City, Jeddah 21423, Saudi Arabia

5. Department of Biology, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia

6. Department of Pharmacology and Toxicology, Faculty of Pharmacy, Mansoura University, Mansoura 35516, Egypt

7. Department of Chemistry, Preparatory Year Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia

8. Department of Pharmacognosy, Faculty of Pharmacy, Assiut University, Assiut 71526, Egypt

Abstract

The discovery of natural drug metabolites is a leading contributor to fulfilling the sustainable development goal of finding solutions to global health challenges. Depsidones are a class of polyketides that have been separated from lichens, fungi, sponges, and plants and possess various bioactivities, including cytotoxic, antimicrobial, antimalarial, antituberculosis, acetylcholinesterase and α-glucosidase inhibition, and anti-inflammatory effects. Endocannabinoid receptors (CB1 and CB2) are G-protein-coupled receptors (GPCRs), and their activation mediates many physiological processes. CB1 is the dominant subtype in the central nervous system, while CB2 is mainly expressed in the immune system. The two receptors exhibit high heterogeneity, making developing selective ligands a great challenge. Attempts to develop CB2 selective agonists for treating inflammatory diseases and neuropathic pain have not been successful due to the high homology of the binding sites of the CB receptors. In this work, 235 depsidones from various sources were investigated for the possibility of identifying CB2-selective agonists by performing multiple docking studies, including induced fit docking and Prime/molecular mechanics–generalized Born surface area (MM-GBSA) calculations to predict the binding mode and free energy. Simplicildone J (10), lobaric acid (110), mollicellin Q (101), garcinisidone E (215), mollicellin P (100), paucinervin Q (149), and boremexin C (161) had the highest binding scores (−12.134 kcal/mol, −11.944 kcal/mol, −11.479 kcal/mol, −11.394 kcal/mol, −11.322 kcal/mol, −11.305 kcal/mol, and −11.254 kcal/mol, respectively) when screened against the CB2 receptor (PDB ID: 6KPF). The molecular dynamic simulation was performed on the compounds with the highest binding scores. The computational outcomes show that garcinisidone E (215) and paucinervin Q (149) could be substantial candidates for CB2 receptor activation and warrant further in vivo and in vitro investigations.

Funder

The Deanship of Scientific Research (DSR) at King Abdulaziz University (KAU), Jeddah, Saudi Arabia

Publisher

MDPI AG

Subject

Chemistry (miscellaneous),Analytical Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Molecular Medicine,Drug Discovery,Pharmaceutical Science

Reference33 articles.

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4. (2022, December 29). Contemporary Computational Applications and Tools in Drug Discovery|ACS Medicinal Chemistry Letters. Available online: https://pubs.acs.org/doi/10.1021/acsmedchemlett.1c00662.

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