CSAR data set release 2012: ligands, affinities, complexes, and docking decoys.
CSAR data set release 2012: ligands, affinities, complexes, and docking decoys.
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DOI：
10.1021/ci4000486
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发表时间：
2013-08-26
影响因子：
5.6
通讯作者：
Carlson HA
中科院分区：
文献类型：
--
作者：
Dunbar JB Jr;Smith RD;Damm-Ganamet KL;Ahmed A;Esposito EX;Delproposto J;Chinnaswamy K;Kang YN;Kubish G;Gestwicki JE;Stuckey JA;Carlson HA
药物设计的一个主要目标是改进对接和评分的计算方法。社区结构活动资源（CSAR）已从工业界收集了若干数据集，并增加了可用于此目的的内部数据集（）。CSAR目前已从Abbott、GlaxoSmithKline和Vertex获得数据，并正在努力从其他几家公司获得数据。结合我们的内部项目，我们提供了一个数据集，包括6个蛋白质靶点，647个具有生物亲和力的化合物和82个晶体结构。多个同类系列可用于几个目标，每个系列都有几个代表性的晶体结构。这些系列通常含有一些非活性化合物，通常在文献中不可用，以提供亲和力范围的上限。亲和力范围通常为每个系列3-4个数量级。对于我们的内部项目，我们已经合成了用于生物测试的化合物。通过Thermofluor、Octet RED和等温滴定量热法测量最可溶的亲和力。这允许直接比较这些化合物的生物亲和力，提供实验亲和力的方差的测量。看起来亲和力的绝对值可能存在相当大的变化，使得绝对值的预测不明确。然而，方法内的相对排名要好得多，这符合预测相对排名在计算上是一个更容易处理的问题的观察。对于这些内部化合物，我们还测量了以下物理性质：logD、logP、热力学溶解度和pKa。该数据集还提供了一个实质性的诱饵集为每个目标组成的不同的构象覆盖整个活性位点的所有58 CSAR质量的晶体结构。CSAR数据集（CSAR-NRC HiQ和2012年发布）提供了大量的、可用的、精选的数据集，用于参数化和验证对接和评分方法。
A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) has collected several data sets from industry and added in-house data sets that may be used for this purpose (). CSAR has currently obtained data from Abbott, GlaxoSmithKline, and Vertex and is working on obtaining data from several others. Combined with our in-house projects, we are providing a data set consisting of 6 protein targets, 647 compounds with biological affinities, and 82 crystal structures. Multiple congeneric series are available for several targets with a few representative crystal structures of each of the series. These series generally contain a few inactive compounds, usually not available in the literature, to provide an upper bound to the affinity range. The affinity ranges are typically 3–4 orders of magnitude per series. For our in-house projects, we have had compounds synthesized for biological testing. Affinities were measured by Thermofluor, Octet RED, and isothermal titration calorimetry for the most soluble. This allows the direct comparison of the biological affinities for those compounds, providing a measure of the variance in the experimental affinity. It appears that there can be considerable variance in the absolute value of the affinity, making the prediction of the absolute value ill-defined. However, the relative rankings within the methods are much better, and this fits with the observation that predicting relative ranking is a more tractable problem computationally. For those in-house compounds, we also have measured the following physical properties: logD, logP, thermodynamic solubility, and pKa. This data set also provides a substantial decoy set for each target consisting of diverse conformations covering the entire active site for all of the 58 CSAR-quality crystal structures. The CSAR data sets (CSAR-NRC HiQ and the 2012 release) provide substantial, publically available, curated data sets for use in parametrizing and validating docking and scoring methods.
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影响因子：
5.6
作者：
Dunbar JB Jr;Smith RD;Yang CY;Ung PM;Lexa KW;Khazanov NA;Stuckey JA;Wang S;Carlson HA
通讯作者：
Carlson HA
影响因子：
5.6
作者：
Damm-Ganamet KL;Smith RD;Dunbar JB Jr;Stuckey JA;Carlson HA
通讯作者：
Carlson HA
影响因子：
8
作者：
Day, YSN;Baird, CL;Myszka, DG
通讯作者：
Myszka, DG
影响因子：
2.9
作者：
Abdiche, Yasmina;Malashock, Dan;Pons, Jaurne
通讯作者：
Pons, Jaurne
影响因子：
2.7
作者：
Jecklin, Matthias C.;Schauer, Stefan;Zenobi, Renato
通讯作者：
Zenobi, Renato