NYU-ECNU Center for Computational Chemistry at New York University Shanghai , Shanghai 200062 , China.
Chem Res Toxicol. 2018 Nov 19;31(11):1260-1268. doi: 10.1021/acs.chemrestox.8b00231. Epub 2018 Oct 22.
Nucleotide excision repair (NER) excises a variety of environmentally derived DNA lesions. However, NER efficiencies for structurally different DNA lesions can vary by orders of magnitude; yet the origin of this variance is poorly understood. Our goal is to develop computational strategies that predict and identify the most hazardous, repair-resistant lesions from the plethora of such adducts. In the present work, we are focusing on lesion recognition by the xeroderma pigmentosum C protein complex (XPC), the first and required step for the subsequent assembly of factors needed to produce successful NER. We have performed molecular dynamics simulations to characterize the initial binding of Rad4, the yeast orthologue of human XPC, to a library of 10 different lesion-containing DNA duplexes derived from environmental carcinogens. These vary in lesion chemical structures and conformations in duplex DNA and exhibit a wide range of relative NER efficiencies from repair resistant to highly susceptible. We have determined a promising set of structural descriptors that characterize initial binding of Rad4 to lesions that are resistant to NER. Key initial binding requirements for successful recognition are absent in the repair-resistant cases: There is little or no duplex unwinding, very limited interaction between the β-hairpin domain 2 of Rad4 and the minor groove of the lesion-containing duplex, and no conformational capture of a base on the lesion partner strand. By contrast, these key binding features are present to different degrees in NER susceptible lesions and correlate to their relative NER efficiencies. Furthermore, we have gained molecular understanding of Rad4 initial binding as determined by the lesion structures in duplex DNA and how the initial binding relates to the repair efficiencies. The development of a computational strategy for identifying NER-resistant lesions is grounded in this molecular understanding of the lesion recognition mechanism.
核苷酸切除修复（NER）能切除多种环境衍生的 DNA 损伤。然而，不同结构的 DNA 损伤的 NER 效率可能相差几个数量级；但这种差异的起源尚不清楚。我们的目标是开发计算策略，从大量的加合物中预测和识别最危险、最难修复的损伤。在目前的工作中，我们专注于 Xeroderma pigmentosum C 蛋白复合物（XPC）识别损伤，这是随后组装进行成功 NER 所需的因素的第一步。我们进行了分子动力学模拟，以表征 Rad4（人类 XPC 的酵母同源物）与从环境致癌物衍生的 10 种不同含有损伤的 DNA 双链体文库的初始结合。这些双链体在损伤的化学结构和在双链体 DNA 中的构象上有所不同，并且表现出从修复抵抗到高度敏感的广泛的相对 NER 效率范围。我们确定了一组有前途的结构描述符，用于表征 Rad4 与对 NER 有抗性的损伤的初始结合。成功识别的关键初始结合要求在修复抵抗的情况下不存在：双链体几乎没有或没有解开，Rad4 的β发夹结构域 2 与含有损伤的双链体的小沟之间的相互作用非常有限，并且没有对损伤伴侣链上的碱基进行构象捕获。相比之下，这些关键结合特征在 NER 敏感的损伤中以不同程度存在，并与它们的相对 NER 效率相关。此外，我们通过双链体 DNA 中的损伤结构以及初始结合与修复效率的关系，获得了对 Rad4 初始结合的分子理解。基于对损伤识别机制的这种分子理解，开发了一种用于识别 NER 抵抗性损伤的计算策略。
