Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.
Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.
复制标题
人组蛋白脱乙酰酶和 Sirtuin 家族的比较建模和基准数据集
DOI：
10.1021/ci5005515
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发表时间：
2015-02-23
影响因子：
5.6
通讯作者：
Wang XS
中科院分区：
文献类型：
--
作者：
Xia J;Tilahun EL;Kebede EH;Reid TE;Zhang L;Wang XS
组蛋白脱乙酰酶 (HDAC) 是治疗癌症、神经退行性疾病和其他类型疾病的一类重要药物靶点。虚拟筛选（VS）已成为新型高选择性组蛋白脱乙酰酶抑制剂（HDACIs）药物发现的相当有效的方法。为了促进这一过程，我们使用最近发布的方法构建了 HDAC 的最大无偏基准数据集 (MUBD-HDAC)，这些方法最初是为构建基于配体的虚拟筛选 (LBVS) 的无偏基准数据集而开发的。 MUBD-HDAC 涵盖所有四个类别，包括 III 类（Sirtuins 家族）和 14 种 HDAC 亚型，由 631 个抑制剂和 24609 个无偏诱饵组成。其配体组已被广泛验证为化学多样性，而诱饵组被证明与配体性质匹配，并且在“人工富集”和“类似物偏差”方面具有最大无偏差。我们还使用 DUD-E 和 DEKOIS 2.0 集针对 HDAC2 和 HDAC8 目标进行了比较研究，并证明我们的 MUBD-HDAC 的独特之处在于它们可以公正地应用于 LBVS 和 SBVS 方法。此外，我们定义了一个新颖的指标，即 NLBScore，来检测基准测试集中的“2D 偏差”和“LBVS 有利”效果。总之，MUBD-HDAC 是迄今为止可用的唯一全面且最大无偏的 HDAC（包括 Sirtuins）基准数据集。 MUBD-HDAC 可在 http://www.xswlab.org/ 上免费获取。
Histone deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases, and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors (HDACIs). To facilitate the process, we constructed maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs cover all four classes including Class III (Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors and 24609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of "artificial enrichment" and "analogue bias". We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the "2D bias" and "LBVS favorable" effect within the benchmarking sets. In summary, MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that are available so far. MUBD-HDACs are freely available at http://www.xswlab.org/ .