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评估 Rosetta 中的多种评分函数在药物发现中的应用。

Assessing multiple score functions in Rosetta for drug discovery.

机构信息

Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee, United States of America.

Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.

出版信息

PLoS One. 2020 Oct 12;15(10):e0240450. doi: 10.1371/journal.pone.0240450. eCollection 2020.

DOI:10.1371/journal.pone.0240450
PMID:33044994
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7549810/
Abstract

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.

摘要

罗塞塔是一个包含各种大分子结构预测和设计任务算法的计算软件套件,包括在药物发现或酶设计中常用的小分子方案。在这里,我们对罗塞塔配体评分函数和方案进行了基准测试,与最近在比较评分函数评估(CASF-2016)中发表的其他软件的结果进行了比较。CASF-2016 基准测试涵盖了广泛的测试,包括对目标进行多种化合物的评分和排序、小分子与目标的配体对接以及从化合物库中提取结合物的虚拟筛选。与 CASF-2016 提供的评分函数的直接比较表明,原始的罗塞塔配体评分函数在评分、排序、对接和筛选测试中排名前几位的软件之一。最值得注意的是,在 CASF-2016 中,罗塞塔配体评分函数在其他报告评分函数中排名第 2/34。我们还进行了一次带有全采样的配体对接测试,以模拟典型的使用情况。尽管在典型的蛋白质结构预测和设计中,较新的评分函数的性能有所提高,但我们在这里证明,最近的罗塞塔评分函数在所有小分子基准测试中的性能都有所下降。这里描述的测试也已上传到罗塞塔科学基准测试服务器,并将每周运行一次,以跟踪代码不断开发时的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/72d042027871/pone.0240450.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/81a819a3568d/pone.0240450.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/5e24ce9f68b0/pone.0240450.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/403ad9c023f7/pone.0240450.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/72d042027871/pone.0240450.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/81a819a3568d/pone.0240450.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/5e24ce9f68b0/pone.0240450.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/403ad9c023f7/pone.0240450.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/385f/7549810/72d042027871/pone.0240450.g004.jpg

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