Assessing multiple score functions in Rosetta for drug discovery.
Assessing multiple score functions in Rosetta for drug discovery.
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DOI：
10.1371/journal.pone.0240450
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发表时间：
2020
期刊：
影响因子：
3.7
通讯作者：
Meiler J
中科院分区：
文献类型：
--
作者：
Smith ST;Meiler J
Rosetta是一个计算软件套件，包含各种大分子结构预测和设计任务的算法，包括药物发现或酶设计中常用的小分子协议。在这里，我们将RosettaLigand评分函数和协议与最近发表在评分函数比较评估（CASF-2016）中的其他软件的结果进行了比较。CASF-2016基准涵盖了各种各样的测试，包括针对靶标对多种化合物进行评分和排名，小分子与靶标的配体对接，以及从化合物库中提取结合剂的虚拟筛选。与CASF-2016提供的评分功能直接对比结果显示，原始RosettaLigand评分功能在评分、排名、对接和筛选测试软件中名列前茅。最值得注意的是，RosettaLigand评分函数在CASF-2016中的其他报告评分函数中排名第2/34。我们还使用全采样执行配体对接测试，以模拟典型用例。尽管较新的评分函数在典型蛋白质结构预测和设计中的性能有所提高，但我们在这里证明，最近的Rosetta评分函数在所有小分子基准中的性能都有所降低。这里描述的测试也已上传到Rosetta科学基准服务器，并将每周运行一次，以跟踪代码持续开发的性能。
Rosetta is a computational software suite containing algorithms for a wide variety of macromolecular structure prediction and design tasks including small molecule protocols commonly used in drug discovery or enzyme design. Here, we benchmark RosettaLigand score functions and protocols in comparison to results of other software recently published in the Comparative Assessment of Score Functions (CASF-2016). The CASF-2016 benchmark covers a wide variety of tests including scoring and ranking multiple compounds against a target, ligand docking of a small molecule to a target, and virtual screening to extract binders from a compound library. Direct comparison to the score functions provided by CASF-2016 results shows that the original RosettaLigand score function ranks among the top software for scoring, ranking, docking and screening tests. Most notably, the RosettaLigand score function ranked 2/34 among other report score functions in CASF-2016. We additionally perform a ligand docking test with full sampling to mimic typical use cases. Despite improved performance of newer score functions in canonical protein structure prediction and design, we demonstrate here that more recent Rosetta score functions have reduced performance across all small molecule benchmarks. The tests described here have also been uploaded to the Rosetta scientific benchmarking server and will be run weekly to track performance as the code is continually being developed.
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DOI：
10.1007/978-1-61779-465-0_10
发表时间：
2012
期刊：
Methods in molecular biology (Clifton, N.J.)
影响因子：
--
作者：
Lemmon, Gordon;Meiler, Jens
通讯作者：
Meiler, Jens
影响因子：
3.7
作者：
DeLuca S;Khar K;Meiler J
通讯作者：
Meiler J
影响因子：
64.8
作者：
Bhardwaj, Gaurav;Mulligan, Vikram Khipple;Bahl, Christopher D.;Gilmore, Jason M.;Harvey, Peta J.;Cheneval, Olivier;Buchko, Garry W.;Pulavarti, Surya V. S. R. K.;Kaas, Quentin;Eletsky, Alexander;Huang, Po-Ssu;Johnsen, William A.;Greisen, Per Jr;Rocklin, Gabriel J.;Song, Yifan;Linsky, Thomas W.;Watkins, Andrew;Rettie, Stephen A.;Xu, Xianzhong;Carter, Lauren P.;Bonneau, Richard;Olson, James M.;Coutsias, Evangelos;Correnti, Colin E.;Szyperski, Thomas;Craik, David J.;Baker, David
通讯作者：
Baker, David
影响因子：
5.5
作者：
O'Meara, Matthew J.;Leaver-Fay, Andrew;Tyka, Michael D.;Stein, Amelie;Houlihan, Kevin;DiMaio, Frank;Bradley, Philip;Kortemme, Tanja;Baker, David;Snoeyink, Jack;Kuhlman, Brian
通讯作者：
Kuhlman, Brian
影响因子：
5.5
作者：
Cavasotto CN;Adler NS;Aucar MG
通讯作者：
Aucar MG