The extracellular loop 2 (ECL2) is the longest and the most diverse loop among class A G protein-coupled receptors (GPCRs). It connects the transmembrane (TM) helices 4 and 5 and contains a highly conserved cysteine through which it is bridged with TM3. In this paper, experimental ECL2 structures were analyzed based on their sequences, shapes, and intramolecular contacts. To take into account the flexibility, we incorporated into our analyses information from the molecular dynamics trajectories available on the GPCRmd website. Despite the high sequence variability, shapes of the analyzed structures, defined by the backbone volume overlaps, can be clustered into seven main groups. Conformational differences within the clusters can be then identified by intramolecular interactions with other GPCR structural domains. Overall, our work provides a reorganization of the structural information of the ECL2 of class A GPCR subfamilies, highlighting differences and similarities on sequence and conformation levels.

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here, we report two additional agonists and functional data of the most potent compound on two mutants, L104 3.32 and L255 6.51 . Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

Tryptophan is an essential amino acid, required for the production of serotonin. It is the most bitter amino acid and its bitterness was found to be mediated by the bitter taste receptor TAS2R4. Di-tryptophan has a different selectivity profile and was found to activate three bitter taste receptors, whereas tri-tryptophan activated five TAS2Rs. In this work, the selectivity/promiscuity profiles of the mono-to-tri-tryptophans were explored using molecular modeling simulations to provide new insights into the molecular recognition of the bitter tryptophan. Tryptophan epitopes were found in all five peptide-sensitive TAS2Rs and the best tryptophan epitope was identified and characterized at the core of the orthosteric binding site of TAS2R4.

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available and the low sequence identity of ORs to experimentally solved GPCRs is a major challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here we investigate the binding modes of identified ligands into the OR5K1 orthosteric binding site using structural information both from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from template-based modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Side chain residue sampling and model selection were guided by mutagenesis data. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models, and also capture differences in activity related to small structural differences. We, therefore, provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

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