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Cannabinoid (CB) receptors selectivity is an active area of research interest for several therapeutic reasons. The limited pool of potent analgesics has resulted in widespread use of opioid analgesics, causing rising cases of opioid addiction in the US. Targeting CB2 selectively has the potential to introduce a potent analgesic, without the psychoactive effects of CB1 binding, potentially reducing the usage of opioid based analgesics.
Virtual screening can be a great first step in designing receptor subtype-specific ligands and can be performed using protein-ligand structural data. We demonstrate how, by applying ligand-based computational methods combined with knowledge of structural biology and chemistry, we can define a novel ligand starting point prior to carrying out a virtual screen, resulting in hits with better receptor subtype selectivity.
