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一种用于可视化癌症相关突变如何影响趋化因子受体CCR3结构可塑性的计算机框架。

An in silico framework to visualize how cancer-associated mutations influence structural plasticity of the chemokine receptor CCR3.

作者信息

van Aalst Evan J, Wylie Benjamin J

机构信息

Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas, USA.

出版信息

Protein Sci. 2025 Jan;34(1):e70013. doi: 10.1002/pro.70013.

Abstract

G protein Coupled Receptors (GPCRs) are the largest family of cell surface receptors in humans. Somatic mutations in GPCRs are implicated in cancer progression and metastasis, but mechanisms are poorly understood. Emerging evidence implicates perturbation of intra-receptor activation pathway motifs whereby extracellular signals are transmitted intracellularly. Recently, sufficiently sensitive methodology was described to calculate structural strain as a function of missense mutations in AlphaFold-predicted model structures, which was extensively validated on experimental and predicted structural datasets. When paired with Molecular Dynamics (MD) simulations, these tools provide a facile approach to screen mutations in silico. We applied this framework to calculate the structural and dynamic effects of cancer-associated mutations in the chemokine receptor CCR3, a Class A GPCR involved in cancer and autoimmune disorders. Residue-residue contact scoring refined effective strain results, highlighting significant remodeling of inter- and intra-motif contacts along the highly conserved GPCR activation pathway network. We then integrated AlphaFold-derived predicted Local Distance Difference Test scores with per-residue Root Mean Square Fluctuations and activation pathway Contact Analysis (CONAN) from coarse grain MD simulations to identify statistically significant changes in receptor dynamics upon mutation. Finally, analysis of negative control mutants suggests false positive results in AlphaFold pipelines should be considered but can be mitigated with stricter control of statistical analysis. Our results indicate selected mutants influence structural plasticity of CCR3 related to ligand interaction, activation, and G protein coupling, using a framework that could be applicable to a wide range of biochemically relevant protein targets following further validation.

摘要

G蛋白偶联受体(GPCRs)是人类细胞表面受体中最大的家族。GPCRs中的体细胞突变与癌症进展和转移有关,但其机制尚不清楚。新出现的证据表明,受体内部激活途径基序受到干扰,细胞外信号通过该途径传递到细胞内。最近,有人描述了一种足够灵敏的方法,用于计算结构应变,该应变是AlphaFold预测模型结构中错义突变的函数,并在实验和预测的结构数据集上进行了广泛验证。当与分子动力学(MD)模拟结合使用时,这些工具提供了一种在计算机上筛选突变的简便方法。我们应用这个框架来计算趋化因子受体CCR3(一种参与癌症和自身免疫性疾病的A类GPCR)中癌症相关突变的结构和动力学效应。残基-残基接触评分优化了有效应变结果,突出了沿着高度保守的GPCR激活途径网络的基序间和基序内接触的显著重塑。然后,我们将AlphaFold衍生的预测局部距离差异测试分数与粗粒度MD模拟中的每个残基均方根波动和激活途径接触分析(CONAN)相结合,以确定突变后受体动力学的统计学显著变化。最后,对阴性对照突变体的分析表明,应考虑AlphaFold管道中的假阳性结果,但可以通过更严格的统计分析控制来减轻这种情况。我们的结果表明,选定的突变体利用一个框架影响CCR3与配体相互作用、激活和G蛋白偶联相关的结构可塑性,该框架在进一步验证后可适用于广泛的生物化学相关蛋白质靶点。

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