Using computational techniques to model G protein-coupled receptors for drug discovery

Nearly one-third of medication approved by the Federal Drug Administration targets a family of proteins called the G protein-coupled receptors (GPCRs). GPCRs are located in the cellular membranes and are responsible for activating internal cellular pathways in response to external cellular stimuli. GPCRs are potential targets for medication that aims to treat obesity, depression, and chronic pain. Despite the recent advances in protein-structure determination, GPCR-targeted drug design proves to be difficult because GPCRs are very flexible and dynamic, and different structures can elicit different cellular responses. The focus of this research is to use computational techniques to predict the most energetically favorable structures at different activation states in order to design drugs that bind to and stabilize those conformations. Our lab uses Schrodinger software to optimize and minimize protein structures before running molecular dynamics simulations of the proteins in a solvated and neutralized cellular bilayer at physiological temperature and pressure to sample protein conformational space. Once the most stable structure is identified, software programs such as DockBlaster and MTIOpenScreen search libraries of commercially-available small molecules to identify known compounds that can potentially bind to and stabilize our protein conformations in a desired activation state. The selected ligands are then docked to the proteins using Glide software, where the binding energies are calculated. Here, we present compounds that can potentially bind to GPCRs, such as the cannabinoid and opioid receptors, in order to treat diseases such as chronic pain and depression.