A pharmacoinformatic approach on Cannabinoid receptor 2 (CB2) and different small molecules: Homology modelling, molecular docking, MD simulations, drug designing and ADME analysis.

CB2 receptor belongs to the family of G-protein coupled receptors (GPCRs), which extensively controls a range of pointer transduction. CB2 plays an essential role in the immune system. It also associates in the pathology of different ailment conditions. In this scenario, the synthetic drugs are inducing side effects to the human beings after the drug use. Therefore, this study is seeking novel alternate drug molecules with least side effects than conventional drugs. The alternative drug molecules were chosen from the natural sources. These molecules were selected from cyanobacteria with the help of earlier research findings. The target and ligand molecules were obtained from recognized databases. The bioactive molecules are selected from various cyanobacterial species, which are selected by their biological and pharmacological properties, after, which we incorporated to the crucial findings such as homology modelling, molecular docking, MD simulations along with absorption, distribution, metabolism, and excretion (ADME) analysis. Initially, the homology modelling was performed to frame the target from unknown sequences of CB2, which revealed 44% of similarities and 66% of identities with the A2A receptor. Subsequently, the CB2 protein molecule has docked with already known and prepared bioactive molecules, agonists and antagonist complex. In the present study, the agonists (5) and antagonist (1) were also taken for comparing the results with natural molecules. At the end of the docking analysis, the cyanobacterial molecules and an antagonist TNC-201 are revealed better docking scores with well binding contacts than the agonists. Especially, the usneoidone shows better results than other cyanobacterial molecules, and it is very close docking scores with that of TCN-201. Therefore, the usneoidone has incorporated to MD simulation with Cannabinoid receptors 2 (CB2). In MD simulations, the complex (CB2 and usneoidone) reveals better stability in 30 ns. Based on the computational outcome, we concluded that usneoidone is an effectual and appropriate drug candidate for activating CB2 receptors and it will be serving as a better component for the complications of CB2. Moreover, these computational approaches can be motivated to discover novel drug candidates in the pharmacological and healthcare sectors.