Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 62, Issue 12, Pages 3096-3106Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.2c00315
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Funding
- Italian Ministry of Research
- French Ministry of Research
- CNRS
- French Ministry of Higher Education Research and Innovation (MESRI)
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The STING protein is crucial for the human immune response, and its variants have significant impact on host defense efficiency. By using molecular modeling and machine learning techniques, we reveal the dynamic behavior of different STING variants and provide an explanation for the variability in their efficiency.
The stimulator of interferon genes (STING) protein is a cornerstone of the human immune response. Its activation by cGAMP in the presence of cytosolic DNA stimulates the production of type Iinterferons and inflammatory cytokines. In the human population, several STING variants exist and exhibit dramatic differences in their activity, impacting the efficiency of the host defense against infections. Understanding the molecular mechanisms of these variants opens perspectives for personalized medicine treatments against diseases such as viral infections, cancers, or autointlammatory diseases. Through microsecond-scale molecular modeling simulations, contact analyses, and machine learning techniques, we reveal the dynamic behavior of four STING variants (wild type, G230A, R293Q, and G230A/R293Q) and rationalize the variability of efficiency observed experimentally. Our results show that the decrease in STING activity is linked to a stiffening of key structural elements of the binding cavity together with changes in the interaction patterns within the protein.
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