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Functional Assessment of Cancer-Linked Mutations in Sensitive Regions of Regulators of G Protein Signaling Predicted
Carolina Montañez-Miranda1, Riley E Perszyk1, Nicholas H Harbin1
1Department of Pharmacology and Chemical Biology (C.M.-M., R.E.P., N.H.H., S.R., S.F.T., J.R.H.) and Aflac Cancer and Blood Disorders Center, Department of Pediatrics (J.O.), Emory University School of Medicine, Atlanta, Georgia.
Abstract:
Regulators of G protein signaling (RGS) proteins modulate G protein-coupled receptor (GPCR) signaling by acting as negative regulators of G proteins. Genetic variants in RGS proteins are associated with many diseases, including cancers, although the impact of these mutations on protein function is uncertain. Here we analyze the RGS domains of 15 RGS protein family members using a novel bioinformatic tool that measures the missense tolerance ratio (MTR) using a three-dimensional (3D) structure (3DMTR). Subsequent permutation analysis can define the protein regions that are most significantly intolerant (P < 0.05) in each dataset. We further focused on RGS14, RGS10, and RGS4. RGS14 exhibited seven significantly tolerant and seven significantly intolerant residues, RGS10 had six intolerant residues, and RGS4 had eight tolerant and six intolerant residues. Intolerant and tolerant-control residues that overlap with pathogenic cancer mutations reported in the COSMIC cancer database were selected to define the functional phenotype. Using complimentary cellular and biochemical approaches, proteins were tested for effects on GPCR-Gα activation, Gα binding properties, and downstream cAMP levels. Identified intolerant residues with reported cancer-linked mutations RGS14-R173C/H and RGS4-K125Q/E126K, and tolerant RGS14-S127P and RGS10-S64T resulted in a loss-of-function phenotype in GPCR-G protein signaling activity. In downstream cAMP measurement, tolerant RGS14-D137Y and RGS10-S64T and intolerant RGS10-K89M resulted in change of function phenotypes. These findings show that 3DMTR identified intolerant residues that overlap with cancer-linked mutations cause phenotypic changes that negatively impact GPCR-G protein signaling and suggests that 3DMTR is a potentially useful bioinformatics tool for predicting functionally important protein residues. SIGNIFICANCE STATEMENT: Human genetic variant/mutation information has expanded rapidly in recent years, including cancer-linked mutations in regulator of G protein signaling (RGS) proteins. However, experimental testing of the impact of this vast catalogue of mutations on protein function is not feasible. We used the novel bioinformatics tool three-dimensional missense tolerance ratio (3DMTR) to define regions of genetic intolerance in RGS proteins and prioritize which cancer-linked mutants to test. We found that 3DMTR more accurately classifies loss-of-function mutations in RGS proteins than other databases thereby offering a valuable new research tool.
Insights
A novel bioinformatics tool, 3D missense tolerance ratio (3DMTR), identifies critical residues in Regulators of G protein signaling (RGS) proteins. This tool accurately predicts how cancer mutations impact RGS protein function in G protein-coupled receptor signaling.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genetics
Background:
- Regulators of G protein signaling (RGS) proteins are crucial negative regulators of G protein-coupled receptor (GPCR) signaling pathways.
- Genetic variations in RGS proteins are linked to various diseases, including cancers, but their functional consequences remain largely uncharacterized.
- Understanding the impact of these mutations is vital for disease mechanism elucidation and therapeutic target identification.
Purpose of the Study:
- To develop and validate a novel bioinformatic tool, three-dimensional missense tolerance ratio (3DMTR), for predicting the functional impact of missense mutations in RGS proteins.
- To identify functionally important residues within RGS protein domains, particularly those associated with cancer-linked mutations.
- To correlate bioinformatic predictions with experimental findings on RGS protein function in GPCR signaling.
Main Methods:
- Analysis of RGS domains from 15 RGS protein family members using a novel 3D missense tolerance ratio (3DMTR) bioinformatic tool.
- Permutation analysis to define significantly intolerant and tolerant protein regions (P < 0.05).
- Integration of 3DMTR data with cancer mutation data from the COSMIC database and subsequent experimental validation using cellular and biochemical assays.
Main Results:
- The 3DMTR tool successfully identified significantly intolerant and tolerant residues in RGS14, RGS10, and RGS4.
- Specific intolerant residues (e.g., RGS14-R173, RGS4-K125) and tolerant residues (e.g., RGS14-S127) with known cancer mutations exhibited loss-of-function phenotypes.
- Other identified residues (e.g., RGS14-D137Y, RGS10-S64T, RGS10-K89M) demonstrated altered function in downstream cAMP signaling.
Conclusions:
- The 3DMTR tool accurately predicts the functional impact of missense mutations in RGS proteins, outperforming existing databases in classifying loss-of-function mutations.
- Cancer-linked mutations in intolerant residues identified by 3DMTR lead to significant functional impairments in GPCR-G protein signaling.
- 3DMTR represents a valuable bioinformatics resource for prioritizing functionally significant genetic variants and understanding disease-associated mutations in RGS proteins.
