CSAR benchmark exercise 2011-2012: evaluation of results from docking and relative ranking of blinded congeneric series.
CSAR benchmark exercise 2011-2012: evaluation of results from docking and relative ranking of blinded congeneric series.
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DOI：
10.1021/ci400025f
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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：
Damm-Ganamet KL;Smith RD;Dunbar JB Jr;Stuckey JA;Carlson HA
社区结构-活动资源（CSAR）最近根据密歇根大学安阿伯的雅培、顶点和同事提供的数据进行了首次盲法练习。共有20个研究小组提交了基准测试的结果，其目标是比较同类化合物系列的姿态预测、富集和相对排名的不同改进。该练习是围绕来自四种蛋白质靶点的盲法高质量实验数据构建的：LpxC，尿激酶，Chk 1和Erk 2。姿势预测被证明是最简单的任务，大多数方法都能够成功地再现结合姿势时，所采用的晶体结构与来自相同的化学系列的配体共结晶。多个评估指标进行了检查，我们发现，RMSD和本地接触指标一起提供了一个强大的评估预测的姿态。值得注意的是，大多数评分函数低估了杂原子之间的接触（即，N、O、S等）蛋白质和配体。相对排名被认为是最困难的领域的方法，但许多评分功能能够正确地识别尿激酶活性的非活性的系列。最后，我们发现，最小化的蛋白质和校正组氨酸互变异构体的状态积极的趋势与低RMSD的姿态预测，但最小化的配体呈负趋势。预生成的配体构象比那些在飞行中产生的表现更好。优化对接参数和预训练与天然配体的对接性能有积极的影响，使用限制，子结构拟合，形状拟合。最后，无论是抽样和排名评分功能，使用的经验评分功能出现的趋势与RMSD积极。在此，通过结合多种方法的结果，我们希望为社会提供一个统计相关的评估和阐明对接方法的具体不足。
The Community Structure–Activity Resource (CSAR) recently held its first blinded exercise based on data provided by Abbott, Vertex, and colleagues at the University of Michigan, Ann Arbor. A total of 20 research groups submitted results for the benchmark exercise where the goal was to compare different improvements for pose prediction, enrichment, and relative ranking of congeneric series of compounds. The exercise was built around blinded high-quality experimental data from four protein targets: LpxC, Urokinase, Chk1, and Erk2. Pose prediction proved to be the most straightforward task, and most methods were able to successfully reproduce binding poses when the crystal structure employed was co-crystallized with a ligand from the same chemical series. Multiple evaluation metrics were examined, and we found that RMSD and native contact metrics together provide a robust evaluation of the predicted poses. It was notable that most scoring functions underpredicted contacts between the hetero atoms (i.e., N, O, S, etc.) of the protein and ligand. Relative ranking was found to be the most difficult area for the methods, but many of the scoring functions were able to properly identify Urokinase actives from the inactives in the series. Lastly, we found that minimizing the protein and correcting histidine tautomeric states positively trended with low RMSD for pose prediction but minimizing the ligand negatively trended. Pregenerated ligand conformations performed better than those that were generated on the fly. Optimizing docking parameters and pretraining with the native ligand had a positive effect on the docking performance as did using restraints, substructure fitting, and shape fitting. Lastly, for both sampling and ranking scoring functions, the use of the empirical scoring function appeared to trend positively with the RMSD. Here, by combining the results of many methods, we hope to provide a statistically relevant evaluation and elucidate specific shortcomings of docking methodology for the community.
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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：
7.3
作者：
Cozzini P;Kellogg GE;Spyrakis F;Abraham DJ;Costantino G;Emerson A;Fanelli F;Gohlke H;Kuhn LA;Morris GM;Orozco M;Pertinhez TA;Rizzi M;Sotriffer CA
通讯作者：
Sotriffer CA
影响因子：
5.6
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
通讯作者：
Carlson HA
影响因子：
7.3
作者：
Hawkins, Paul C. D.;Skillman, A. Geoffrey;Nicholls, Anthony
通讯作者：
Nicholls, Anthony
影响因子：
7.3
作者：
Halgren, TA;Murphy, RB;Banks, JL
通讯作者：
Banks, JL