Scientists map disease mutations in key cell signaling protein
Researchers have structurally characterized seven common mutations in a G protein that controls critical cellular signals, using a novel technique that overcomes previous scientific barriers. The work could accelerate drug development for diseases caused by these mutations, including certain cancers and endocrine disorders where these proteins malfunction.
Originaltitel: Interaction networks within disease-associated GaS variants characterized by an integrative biophysical approach
<p>Activation of G proteins through nucleotide exchange initiates intracellular signaling cascades essential for life processes. Under normal conditions, nucleotide exchange is regulated by the formation of G protein-G protein-coupled receptor complexes. Single point mutations in the Ga subunit of G proteins bypass this interaction, leading to loss of function or constitutive gain of function, which is closely linked with the onset of multiple diseases. Despite the recognized significance of Ga mutations in disease pathology, structural information for most variants is lacking, potentially due to inherent protein dynamics that pose challenges for crystallography. To address this, we leveraged an integrative spectroscopic and computational approach to structurally characterize seven of the most frequently observed and clinically relevant mutations in the stimulatory Ga subunit, GaS. A previously proposed allosteric model of Ga activation linked structural changes in the nucleotide-binding pocket with functionally important changes in interactions between switch regions. We investigated this allosteric connection in GaS by integrating data from variable temperature CD spectroscopy, which measured changes in global protein structure and stability, and molecular dynamics simulations, which observed changes in interaction networks between GaS switch regions. Additionally, saturation-transfer difference NMR spectroscopy was applied to observe changes in nucleotide interactions with residues within the nucleotide binding site. These data have enabled testing of predictions regarding how mutations in GaS result in loss or gain of function and evaluation of proposed structural mechanisms. The integration of experimental and computational data allowed us to propose a more nuanced classification of mechanisms underlying GaS gain-of-function and loss-of-function mutations.</p>