Elucidation of partial activation of cannabinoid receptor type 2 and identification of potential partial agonists: Molecular dynamics simulation and structure-based virtual screening

Abdullahi Ibrahim Uba, Harika Aluwala, Haiguang Liu, Chun Wu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Cannabinoid receptor type 2 (CB2R) is a member of the class A G protein-coupled receptor (GPCRs) family and a component of the endocannabinoid system that is modulated by the psychoactive chemical from Cannabis sativa, partial agonist Δ9-tetrahydrocannabinol (Δ9-THC). Selective activation of CB2R allows for the treatment of inflammatory and immune-related conditions without the psychotropic effects of CB1R. While CB2R-selective agonists are available, CB2R partial agonists are scarce. Hence, the pharmacological difference between CB2R full agonists and partial agonists remains to be deciphered, prompting the search for novel partial agonists. Here, using an induced-fit docking approach, we built a partial agonist Δ9-THC bound CB2R system from the inactive CB2R structure (PDB ID: 5ZTY) and performed microsecond molecular dynamics (MD) simulations. The simulations reveal an upward shift of the “toggle switch” W6.48(258) and minor outward movement of the transmembrane helix 6 (TM6). Dynamic network model identifies a possible communication path between the ligand and the toggle switch” W6.48(258). Furthermore, to identify potential CB2R partial agonists, we conducted structure-based virtual screening of ZINC15 “Druglike” library containing 17,900742 compounds against 3 conformations derived from MD simulation of CB2R complexed with partial agonist Δ9-THC using Glide virtual screening protocol comprising various filters with increasing accuracy. Nine diverse compounds predicted to have high MM-GBSA binding energy scores and good ADMET properties (including high gastrointestinal absorption and low toxicity) are proposed as potential CB2R partial agonists.

Original languageEnglish (US)
Article number107723
JournalComputational Biology and Chemistry
Volume99
DOIs
StatePublished - Aug 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Structural Biology
  • Biochemistry
  • Organic Chemistry
  • Computational Mathematics

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