AI-based identification of therapeutic agents targeting GPCRs: introducing ligand type classifiers and systems biology.

Identifying ligands targeting G protein coupled receptors (GPCRs) with novel chemotypes other than the physiological ligands is a challenge for in silico screening campaigns. Here we present an approach that identifies novel chemotype ligands by combining structural data with a random forest agonist/antagonist classifier and a signal-transduction kinetic model. As a test case, we apply this approach to identify novel antagonists of the human adenosine transmembrane receptor type 2A, an attractive target against Parkinson's disease and cancer. The identified antagonists were tested here in a radio ligand binding assay. Among those, we found a promising ligand whose chemotype differs significantly from all so-far reported antagonists, with a binding affinity of 310 ± 23.4 nM. Thus, our protocol emerges as a powerful approach to identify promising ligand candidates with novel chemotypes while preserving antagonistic potential and affinity in the nanomolar range.

GABAA receptor family: overview on structural characterization.

The pentameric γ-aminobutyric acid type A receptors are ion channels activated by ligands, which intervene in the rapid inhibitory transmission in the mammalian CNS. Due to their rich pharmacology and therapeutic potential, it is essential to understand their structure and function thoroughly. This deep characterization was hampered by the lack of experimental structural information for many years. Thus, computational techniques have been extensively combined with experimental data, in order to undertake the study of γ-aminobutyric acid type A receptors and their interaction with drugs. Here, we review the exciting journey made to assess the structures of these receptors and outline major outcomes. Finally, we discuss the brand new structure of the α1ß2γ2 subtype and the amazing advances it brings to the field.