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G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. Three-dimensional structural comparisons of the GPCRs that bind to the same ligand revealed local 3D structural similarities and often these regions overlap with locations of binding pockets. These pockets were found to be similar (based on backbone geometry and side-chain orientation using APoc), and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs.
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This content will become publicly available on December 23, 2025
To bind or not to bind: diagnosing false positives for 1:1 binding to G-Protein
Binding studies are ubiquitous in chemistry, but their extensive usefulness is undermined by false positive and false negative results. Centering on the G-protein mini-Gs, we present a thorough study with both simulated and experimental spectrophotometric titration data to diagnose the validity of both binding and non-binding models. Without the use of statistical tests like Bayesian Information Criterion (BIC) and data reconstruction fractions, spurious binding models may go undetected. Furthermore, if the signal change upon binding is too minute, false negatives can also result. Delineating such issues is paramount to effective science.
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- Award ID(s):
- 2004005
- PAR ID:
- 10579048
- Publisher / Repository:
- Taylor & Francis
- Date Published:
- Journal Name:
- Supramolecular Chemistry
- ISSN:
- 1061-0278
- Page Range / eLocation ID:
- 1 to 11
- Subject(s) / Keyword(s):
- Binding false positive thermodynamic modelling global analysis G-protein
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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