Volume 74, February 2024, 102427Author links open overlay panel, , , Abstract

This article investigates the role of recent advances in Artificial Intelligence (AI) to revolutionise the study of G protein-coupled receptors (GPCRs). AI has been applied to many areas of GPCR research, including the application of machine learning (ML) in GPCR classification, prediction of GPCR activation levels, modelling GPCR 3D structures and interactions, understanding G-protein selectivity, aiding elucidation of GPCRs structures, and drug design. Despite progress, challenges in predicting GPCR structures and addressing the complex nature of GPCRs remain, providing avenues for future research and development.

Section snippetsIntroduction to GPCRs

G protein-coupled receptors (GPCRs) are members of the largest and most diverse group of membrane receptors in eukaryotes, accounting for 4 % of human genes [1] and responsible for approximately two-thirds of hormones and neurotransmitters [2]. GPCRs are grouped into five families: rhodopsin-like (class A), secretin-receptor-like (class B1), metabotropic glutamate receptor (class C), adhesion receptor (class B2), frizzled/taste2 receptor (class F) [3] (Figure 1). They are involved and

Challenges of studying GPCRs

GPCRs are highly flexible and dynamic membrane proteins. This conformational complexity and variability make it difficult to obtain high-resolution structures experimentally [15], with engineering usually required to minimise conformational heterogeneity and maximise crystal contacts and stability [16, 17, 18, 19, 20]. The methods involved in this process are usually costly and slow. Hence, the development of computational approaches to support structure elucidation of these essential receptors

Conservation and variation in GPCRs

GPCRs represent the largest protein family in the human genome [34], presenting great diversity in terms of their amino acid sequence composition. They possess, however, common and recurring structural features, including a domain comprising seven-transmembrane (7TM) helices linked by three extracellular loops (ECL), three intracellular loops (ICL) (Figure 3) [35], and a orthosteric ligand binding site, where the primary ligand binds. This binding site region varies from GPCR to GPCR because

How could AI help? Advances and limitations

In 1951 the first successful AI program was written by Christopher Strachey. It could play a complete game of checkers in a reasonable time. In the 21st century, AI finally started to proliferate and started being developed and used largely in academia and industry thanks to availability of data and computational resources. Machine learning (ML) is a subfield of AI that has particularly revolutionised biological research. ML allows identification of complex patterns in the data as well as the

Future directions and challenges

GPCRs are the most extensively evaluated protein family as a drug target. This is mainly due to their large in involvement in human pathophysiology. Despite the recent and significant progress in tools for GPCR studies, these approaches are challenged by the significant complexity of these receptors and many of the ML tools developed for GPCRs have presented limited performance. Consequently, the development of tools that can support structure elucidation, drug design and protein–protein

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported in part by The National Health and Medical Research Council of Australia (GNT1174405 to D.B.A.), and The Victorian Government's Operational Infrastructure Support Program.

References (110)J. Selent et al.Induced effects of sodium ions on dopaminergic G-protein coupled receptors

PLoS Comput Biol

(2010)

M. Silk et al.Insights from spatial measures of intolerance to identifying pathogenic variants in developmental and epileptic encephalopathies

Int J Mol Sci

(2023)

C. Bushdid et al.Agonists of G-protein-coupled odorant receptors are predicted from chemical features

J Phys Chem Lett

(2018)

J.W. Jang et al.Novel scaffold identification of mGlu1 receptor negative allosteric modulators using a hierarchical virtual screening approach

Chem Biol Drug Des

(2016)

M. Congreve et al.Impact of GPCR structures on drug discovery

Cell

(2020)

C.H. Rodrigues et al.DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability

Nucleic Acids Res

(2018)

C.H.M. Rodrigues et al.DynaMut2: assessing changes in stability and flexibility upon single and multiple point missense mutations

Protein Sci

(2021)

D.S. Wishart et al.DrugBank 5.0: a major update to the DrugBank database for 2018

Nucleic Acids Res

(2018)

A.J. Kooistra et al.GPCRdb in 2021: integrating GPCR sequence, structure and function

Nucleic Acids Res

(2021)

S.R. Foster et al.Discovery of human signaling systems: pairing peptides to G protein-coupled receptors

Cell

(2019)

R. Fredriksson et al.The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints

Mol Pharmacol

(2003)

A. de Mendoza et al.The evolution of the GPCR signaling system in eukaryotes: modularity, conservation, and the transition to metazoan multicellularity

Genome Biol Evol

(2014)

J. Cherfils et al.Regulation of small GTPases by GEFs, GAPs, and GDIs

Physiol Rev

(2013)

C.R. McCudden et al.G-protein signaling: back to the future

Cell Mol Life Sci

(2005)

G.J. Digby et al.Some G protein heterotrimers physically dissociate in living cells

Proc Natl Acad Sci U S A

(2006)

R.J. LefkowitzA brief history of G-protein coupled receptors (Nobel Lecture)

Angew Chem Int Ed Engl

(2013)

R. Zhang et al.Tools for GPCR drug discovery

Acta Pharmacol Sin

(2012)

A.S. Hauser et al.Trends in GPCR drug discovery: new agents, targets and indications

Nat Rev Drug Discov

(2017)

D. Wootten et al.Mechanisms of signalling and biased agonism in G protein-coupled receptors

Nat Rev Mol Cell Biol

(2018)

F. Magnani et al.Co-evolving stability and conformational homogeneity of the human adenosine A2a receptor

Proc Natl Acad Sci U S A

(2008)

R.M. Bill et al.Overcoming barriers to membrane protein structure determination

Nat Biotechnol

(2011)

J. Jumper et al.Highly accurate protein structure prediction with AlphaFold

Nature

(2021)

M. Baek et al.Accurate prediction of protein structures and interactions using a three-track neural network

Science

(2021)

L. Heo et al.Multi-state modeling of G-protein coupled receptors at experimental accuracy

Proteins

(2022)

G. Pandy-Szekeres et al.GPCRdb in 2023: state-specific structure models using AlphaFold2 and new ligand resources

Nucleic Acids Res

(2022)

C. Lee et al.Comparative studies of AlphaFold, RoseTTAFold and Modeller: a case study involving the use of G-protein-coupled receptors

Briefings Bioinf

(2022)

T. Schoneberg et al.Mutations in G Protein-Coupled receptors: mechanisms, pathophysiology and potential therapeutic approaches

Pharmacol Rev

(2021)

T. Gudermann et al.Diversity and selectivity of receptor-G protein interaction

Annu Rev Pharmacol Toxicol

(1996)

W.I. Weis et al.The molecular basis of G protein-coupled receptor activation

Annu Rev Biochem

(2018)

L.T. May et al.Allosteric modulation of G protein-coupled receptors

Curr Pharmaceut Des

(2004)

R.A. Adan et al.Inverse agonism gains weight

Trends Pharmacol Sci

(2003)

E.T. van der Westhuizen et al.Endogenous allosteric modulators of G protein-coupled receptors

J Pharmacol Exp Therapeut

(2015)

E. HermansBiochemical and pharmacological control of the multiplicity of coupling at G-protein-coupled receptors

Pharmacol Ther

(2003)

H. Chen et al.A forward chemical genetic screen reveals gut microbiota metabolites that modulate host physiology

Cell

(2019)

J.A. Ballesteros et al.[19] Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptorsQ. Zhou et al.Common activation mechanism of class A GPCRs

Elife

(2019)

D. Yang et al.G protein-coupled receptors: structure- and function-based drug discovery

Signal Transduct Targeted Ther

(2021)

A.S. Dore et al.Structure of class C GPCR metabotropic glutamate receptor 5 transmembrane domain

Nature

(2014)

A.C. Bertalovitz et al.Frizzled-4 C-terminus distal to KTXXXW motif is essential for normal dishevelled recruitment and norrin-stimulated activation of Lef/Tcf-dependent transcriptional activation

J Mol Signal

(2016)

S. Moro et al.Role of the extracellular loops of G protein-coupled receptors in ligand recognition: a molecular modeling study of the human P2Y1 receptor

Biochemistry

(1999)

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