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Updated: Jun 21, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
Published on: January 26, 2024
Prediction of protein-protein interfaces on G-protein beta subunits reveals a novel phospholipase C beta2 binding
Erin J Friedman1, Brenda R S Temple, Stephanie N Hicks
1Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Abstract:
Gbeta subunits from heterotrimeric G-proteins (guanine nucleotide-binding proteins) directly bind diverse proteins, including effectors and regulators, to modulate a wide array of signaling cascades. These numerous interactions constrained the evolution of the molecular surface of Gbeta. Although mammals contain five Gbeta genes comprising two classes (Gbeta1-like and Gbeta5-like), plants and fungi have a single ortholog, and organisms such as Caenorhabditis elegans and Drosophila melanogaster contain one copy from each class. A limited number of crystal structures of complexes containing Gbeta subunits and complementary biochemical data highlight specific sites within Gbetas needed for protein interactions. It is difficult to determine from these interaction sites what, if any, additional regions of the Gbeta molecular surface comprise interaction interfaces essential to Gbeta's role as a nexus in numerous signaling cascades. We used a comparative evolutionary approach to identify five known and eight previously unknown putative interfaces on the surface of Gbeta. We show that one such novel interface occurs between Gbeta and phospholipase C beta2 (PLC-beta2), a mammalian Gbeta interacting protein. Substitutions of residues within this Gbeta-PLC-beta2 interface reduce the activation of PLC-beta2 by Gbeta1, confirming that our de novo comparative evolutionary approach predicts previously unknown Gbeta-protein interfaces. Similarly, we hypothesize that the seven remaining untested novel regions contribute to putative interfaces for other Gbeta interacting proteins. Finally, this comparative evolutionary approach is suitable for application to any protein involved in a significant number of protein-protein interactions.
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