Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response

Abstract

Signaling diversity of G protein-coupled (GPCR) ligands provides novel opportunities to develop more effective, better-tolerated therapeutics. Taking advantage of these opportunities requires identifying which effectors should be specifically activated or avoided so as to promote desired clinical responses and avoid side effects. However, identifying signaling profiles that support desired clinical outcomes remains challenging. This study describes signaling diversity of mu opioid receptor (MOR) ligands in terms of logistic and operational parameters for ten different in vitro readouts. It then uses unsupervised clustering of curve parameters to: classify MOR ligands according to similarities in type and magnitude of response, associate resulting ligand categories with frequency of undesired events reported to the pharmacovigilance program of the Food and Drug Administration and associate signals to side effects. The ability of the classification method to associate specific in vitro signaling profiles to clinically relevant responses was corroborated using β2-adrenergic receptor ligands.

Intrinsic Efficacy of Opioid Ligands and Its Importance for Apparent Bias, Operational Analysis, and Therapeutic Window

“…If measurements of efficacy in the G protein system are confounded or not made with high confidence, all further assessments of bias between G protein and other signals are difficult to interpret. As discussed by Conibear and Kelly (2019) and shown in McPherson et al (2010) and Benredjem et al (2019), MOR agonists with low G protein efficacy consistently produce a very low response in assays of arrestin recruitment, and this may not reflect true ligand bias (see below). Additionally, if the efficacy and affinity parameters are not separated, their relative contribution to agonist effects in vivo cannot be independently assessed.…”

“…The null hypothesis in any examination of proposed ligand or receptor bias should be consistent activity across pathways. Given the robust prediction of rank order of arrestin-recruitment efficacy by G protein efficacy at the MOR (McPherson et al, 2010;Benredjem et al, 2019;Gillis et al, 2020), this is a reasonable starting place. It is theoretically (Fig.…”

“…A recent paper that analyzed the signaling characteristics of existing analgesics and compounds in development found that efficacy predicted clinical outcomes in terms of reported adverse events (Benredjem et al, 2019). The authors concluded that partial agonism was a route to improved opioid safety.…”

Vasopressin V2 is a promiscuous G protein-coupled receptor that is biased by its peptide ligands

“…The realisation that some ligands can be agonists for one pathway and antagonists for another led to the development of the concept of biased signalling [12][13][14][15][16][17]. Importantly, such biased ligands are very promising pharmaceuticals because pharmacological benefits are often associated with one particular pathway while the undesired side-effects are mediated by another [13,[18][19][20][21][22]. To compare ligands with each other, a quantitative measure of their signalling efficacy towards individual effectors and their signalling bias is required.…”

Pharmacological Characterization of the Stick Insect Carausius morosus Allatostatin-C Receptor with Its Endogenous Agonist

“… 2 At the vertebrate end of the GPCR spectrum, fluorescence and bioluminescence resonance energy transfer (FRET and BRET)-based, genetically encoded biosensors can measure receptor downstream signaling robustly. These sensors are extensively used for identifying the pharmacology and signaling by ligands, 10 , 11 kinetic properties of receptor-mediated signaling, 12 as well as deorphanization and characterization of GPCRs. 13 Due to a high degree of homology between human and insect GPCRs, vertebrate signaling protein-based biosensors may also be functional for characterizing insect receptors.…”