我们何其脆弱：干扰素基因刺激因子(STING)变体对病原体识别和免疫反应效率的影响
本数据集包含四种STING变体的分子动力学模拟和机器学习分析数据，用于揭示变体对免疫应答效率的影响，支撑个性化疾病治疗研究。
基本信息
资源简介
我们何其脆弱：干扰素基因刺激因子(STING)变体对病原体识别和免疫反应效率的影响
【数据集背景】
本数据集源站标题为《How Fragile We Are: Influence of Stimulator of Interferon
Genes (STING) Variants on Pathogen Recognition and Immune Response
Efficiency》。配套论文《How Fragile We Are: Influence of Stimulator of Interferon Genes (STING) Variants on Pathogen Recognition and Immune Response Efficiency》发表于 Journal of Chemical Information and Modeling（2022），DOI：10.1021/acs.jcim.2c00315。源站首次发布：2022-06-08。
【数据内容】
源站原始描述：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 I interferons 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 medic…
【数据结构与技术规格】
文件数 1 个，合计 30.94 MB。数据集 DOI：10.1021/acs.jcim.2c00315.s002。
【主题与分类】
源站学科分类：Biochemistry、Microbiology、Molecular Biology、Biotechnology、Ecology、Immunology。主题标签：personalized medicine treatments、machine learning techniques、key structural elements、interaction patterns within、exhibit dramatic differences、cytosolic dna stimulates、binding cavity together、human immune response、variants opens perspectives、immune response efficiency。
【适用方向】
源站学科分类标注为 Biochemistry、Microbiology、Molecular Biology、Biotechnology、Ecology、Immunology。
【获取与许可】
源站页面：https://acs.figshare.com/articles/dataset/How_Fragile_We_Are_Influence_of_Stimulator_of_Interferon_Genes_STING_Variants_on_Pathogen_Recognition_and_Immune_Response_Efficiency/20032617
使用许可：CC BY-NC 4.0（https://creativecommons.org/licenses/by-nc/4.0/）。
规范引用：Morere, Jeremy; Hognon, Cécilia; Miclot, Tom; Jiang, Tao; Dumont, Elise; Barone, Giampaolo; et al. (1753). How Fragile We Are: Influence of Stimulator of Interferon Genes (STING) Variants on Pathogen Recognition and Immune Response Efficiency. ACS Publications. Dataset
【使用注意】
· 源站最后修改于 2023-06-01，引用时请注意版本时效。
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：How Fragile We Are: Influence of Stimulator of Interferon
Genes (STING) Variants on Pathogen Recognition and Immune Response
Efficiency - DOI：10.1021/acs.jcim.2c00315.s002
- 发布日期：2022-06-08
- 文件数：1 个
- 文件总体积：30.94 MB
- 源站页面：https://acs.figshare.com/articles/dataset/How_Fragile_We_Are_Influence_of_Stimulator_of_Interferon_Genes_STING_Variants_on_Pathogen_Recognition_and_Immune_Response_Efficiency/20032617
命令行下载
curl -L -o "ci2c00315_si_002.zip" "https://ndownloader.figshare.com/files/35779062"
文件清单
ci2c00315_si_002.zip（30.94 MB）
文件总体积 30.94 MB（源站 API 实测）。
数据说明
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 I interferons 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 autoinflammatory 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.
许可
CC BY-NC 4.0
引用
学术使用请引用 DOI 10.1021/acs.jcim.2c00315.s002（source: https://acs.figshare.com/articles/dataset/How_Fragile_We_Are_Influence_of_Stimulator_of_Interferon_Genes_STING_Variants_on_Pathogen_Recognition_and_Immune_Response_Efficiency/20032617）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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