Unifying view of mechanical and functional hotspots across class A GPCRs

G protein-coupled receptors (GPCRs) are the largest superfamily of signaling proteins. Their activation process is accompanied by conformational changes that have not yet been fully uncovered. Here, we carry out a novel comparative analysis of internal structural fluctuations across a variety of receptors from class A GPCRs, which currently has the richest structural coverage. We infer the local mechanical couplings underpinning the receptors' functional dynamics and finally identify those amino acids whose virtual deletion causes a significant softening of the mechanical network. The relevance of these amino acids is demonstrated by their overlap with those known to be crucial for GPCR function, based on static structural criteria. The differences with the latter set allow us to identify those sites whose functional role is more clearly detected by considering dynamical and mechanical properties. Of these sites with a genuine mechanical/dynamical character, the top ranking is amino acid 7x52, a previously unexplored, and experimentally verifiable key site for GPCR conformational response to ligand binding. \ua9 2017 Ponzoni et al

Evolution of a Signaling Nexus Constrained by Protein Interfaces and Conformational States

Heterotrimeric G proteins act as the physical nexus between numerous receptors that respond to extracellular signals and proteins that drive the cytoplasmic response. The Gα subunit of the G protein, in particular, is highly constrained due to its many interactions with proteins that control or react to its conformational state. Various organisms contain differing sets of Gα-interacting proteins, clearly indicating that shifts in sequence and associated Gα functionality were acquired over time. These numerous interactions constrained much of Gα evolution; yet Gα has diversified, through poorly understood processes, into several functionally specialized classes, each with a unique set of interacting proteins. Applying a synthetic sequence-based approach to mammalian Gα subunits, we established a set of seventy-five evolutionarily important class-distinctive residues, sites where a single Gα class is differentiated from the three other classes. We tested the hypothesis that shifts at these sites are important for class-specific functionality. Importantly, we mapped known and well-studied class-specific functionalities from all four mammalian classes to sixteen of our class-distinctive sites, validating the hypothesis. Our results show how unique functionality can evolve through the recruitment of residues that were ancestrally functional. We also studied acquisition of functionalities by following these evolutionarily important sites in non-mammalian organisms. Our results suggest that many class-distinctive sites were established early on in eukaryotic diversification and were critical for the establishment of new Gα classes, whereas others arose in punctuated bursts throughout metazoan evolution. These Gα class-distinctive residues are rational targets for future structural and functional studies

G-protein signaling: back to the future

Heterotrimeric G-proteins are intracellular partners of G-protein-coupled receptors (GPCRs). GPCRs act on inactive Gα·GDP/Gβγ heterotrimers to promote GDP release and GTP binding, resulting in liberation of Gα from Gβγ. Gα·GTP and Gβγ target effectors including adenylyl cyclases, phospholipases and ion channels. Signaling is terminated by intrinsic GTPase activity of Gα and heterotrimer reformation — a cycle accelerated by ‘regulators of G-protein signaling’ (RGS proteins). Recent studies have identified several unconventional G-protein signaling pathways that diverge from this standard model. Whereas phospholipase C (PLC) β is activated by Gαq and Gβγ, novel PLC isoforms are regulated by both heterotrimeric and Ras-superfamily G-proteins. An Arabidopsis protein has been discovered containing both GPCR and RGS domains within the same protein. Most surprisingly, a receptor-independent Gα nucleotide cycle that regulates cell division has been delineated in both Caenorhabditis elegans and Drosophila melanogaster. Here, we revisit classical heterotrimeric G-protein signaling and explore these new, non-canonical G-protein signaling pathways

Phospholipase D signaling: orchestration by PIP2 and small GTPases

Hydrolysis of phosphatidylcholine by phospholipase D (PLD) leads to the generation of the versatile lipid second messenger, phosphatidic acid (PA), which is involved in fundamental cellular processes, including membrane trafficking, actin cytoskeleton remodeling, cell proliferation and cell survival. PLD activity can be dramatically stimulated by a large number of cell surface receptors and is elaborately regulated by intracellular factors, including protein kinase C isoforms, small GTPases of the ARF, Rho and Ras families and, particularly, by the phosphoinositide, phosphatidylinositol 4,5-bisphosphate (PIP2). PIP2 is well known as substrate for the generation of second messengers by phospholipase C, but is now also understood to recruit and/or activate a variety of actin regulatory proteins, ion channels and other signaling proteins, including PLD, by direct interaction. The synthesis of PIP2 by phosphoinositide 5-kinase (PIP5K) isoforms is tightly regulated by small GTPases and, interestingly, by PA as well, and the concerted formation of PIP2 and PA has been shown to mediate receptor-regulated cellular events. This review highlights the regulation of PLD by membrane receptors, and describes how the close encounter of PLD and PIP5K isoforms with small GTPases permits the execution of specific cellular functions

Evaluation of an artificial intelligence clinical trial matching system in Australian lung cancer patients

Objective: The objective of this technical study was to evaluate the performance of an artificial intelligence (AI)-based system for clinical trials matching for a cohort of lung cancer patients in an Australian cancer hospital. Methods: A lung cancer cohort was derived from clinical data from patients attending an Australian cancer hospital. Ten phases I-III clinical trials registered on clinicaltrials.gov and open to lung cancer patients at this institution were utilized for assessments. The trial matching system performance was compared to a gold standard established by clinician consensus for trial eligibility. Results: The study included 102 lung cancer patients. The trial matching system evaluated 7252 patient attributes (per patient median 74, range 53-100) against 11 467 individual trial eligibility criteria (per trial median 597, range 243-4132). Median time for the system to run a query and return results was 15.5 s (range 7.2-37.8). In establishing the gold standard, clinician interrater agreement was high (Cohen's kappa 0.70-1.00). On a per-patient basis, the performance of the trial matching system for eligibility was as follows: accuracy, 91.6%; recall (sensitivity), 83.3%; precision (positive predictive value), 76.5%; negative predictive value, 95.7%; and specificity, 93.8%. Discussion and Conclusion: The AI-based clinical trial matching system allows efficient and reliable screening of cancer patients for clinical trials with 95.7% accuracy for exclusion and 91.6% accuracy for overall eligibility assessment; however, clinician input and oversight are still required. The automated system demonstrates promise as a clinical decision support tool to prescreen a large patient cohort to identify subjects suitable for further assessment