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Trends in application of advancing computational approaches in GPCR ligand discovery
- Source :
- Exp Biol Med (Maywood)
- Publication Year :
- 2021
-
Abstract
- G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological structures, as well as improvements on computer power and algorithms, have led to unprecedented use of CADD for the discovery of novel GPCR modulators. Similarly, machine learning approaches are now widely applied in various fields of drug target research. This review briefly summarizes the application of rising CADD methodologies, as well as novel machine learning techniques, in GPCR structural studies and bioligand discovery in the past few years. Recent novel computational strategies and feasible workflows are updated, and representative cases addressing challenging issues on olfactory receptors, biased agonism, and drug-induced cardiotoxic effects are highlighted to provide insights into future GPCR drug discovery.
- Subjects :
- 0301 basic medicine
Hematological disorders
Computer science
Drug discovery
SUPERFAMILY
Computational biology
Ligands
General Biochemistry, Genetics and Molecular Biology
GPCR Signaling
Receptors, G-Protein-Coupled
Actual cost
Machine Learning
03 medical and health sciences
030104 developmental biology
0302 clinical medicine
Drug development
Drug Design
Drug Discovery
Functional selectivity
Humans
Minireview
030217 neurology & neurosurgery
G protein-coupled receptor
Subjects
Details
- ISSN :
- 15353699
- Volume :
- 246
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- Experimental biology and medicine (Maywood, N.J.)
- Accession number :
- edsair.doi.dedup.....8dc1b910468945dadfab6a3a70730088