An in silico structure-based approach to map the druggable allosteric space of membrane receptors

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Membrane receptors enable cells to respond to chemical and physical signals, activate a complex chain of biological events inside the cell and ultimately lead to a change in cell biology. The G protein-coupled receptors (GPCRs), ligand- and voltage-gated ion channel receptors and tyrosine kinase receptors are effective targets of nearly 60 % of the medicines currently used in clinics. The receptor biological state can be modulated by small molecule ligands acting on spatially distinct allosteric binding sites that result in more selective and safer medicines than those targeting orthosteric sites. Recent studies point to common mechanisms of allosteric regulation and the discovery of synthetic allosteric modulators for these receptor families. However, the discovery of allosteric sites and modulators has been largely serendipitous, achieved through high-throughput screening. A recent breakthrough in structural biology disclosed the crystal structures of several GPCRs bounded to allosteric modulators providing opportunities to develop predictive computational methodologies for allosteric medicine discovery in the membrane receptors. We aim to develop a general structure-based computational methodology to search for allosteric binding sites in the membrane receptors. Since the newly available crystal structures of GPCR-allosteric modulator complexes indicate a diverse location of allosteric sites, we aim to develop computational procedures to map allosteric sites inside of the receptors; and outside of the receptor at the interface with the lipid bilayer. Our methodology will rely on the study of receptor dynamics in realistic cellular environment with the presence of carefully selected organic solvents. The organic solvents will be used as probes to search for binding sites. We will initially develop the methodology, where we predict allosteric sites for the receptors with the available crystal structures of a receptor-allosteric ligand complex (the training set) and then explore developed computational procedures predicting allosteric sites for new receptors (the test set) with further validation of the results of prediction in mutagenesis and compound screening. The bioamine, peptide and nucleotide receptors will be used to develop the methodology. We will use our receptor case studies together with sequence approaches to predict a general molecular basis of allosteric site location in GPCRs. Our computational methodology will facilitate the development of new therapies for the treatment of GPCR-related diseases such as inflammation, infertility, metabolic and neurological disorders, viral infections and cancer. The computational strategy developed for one membrane receptor family will enable its applications to other receptor families.