Roy Ambrish, Skolnick Jeffrey
Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.
Bioinformatics. 2015 Feb 15;31(4):539-44. doi: 10.1093/bioinformatics/btu692. Epub 2014 Oct 21.
Shape-based alignment of small molecules is a widely used approach in computer-aided drug discovery. Most shape-based ligand structure alignment applications, both commercial and freely available ones, use the Tanimoto coefficient or similar functions for evaluating molecular similarity. Major drawbacks of using such functions are the size dependence of the score and the fact that the statistical significance of the molecular match using such metrics is not reported.
We describe a new open-source ligand structure alignment and virtual screening (VS) algorithm, LIGSIFT, that uses Gaussian molecular shape overlay for fast small molecule alignment and a size-independent scoring function for efficient VS based on the statistical significance of the score. LIGSIFT was tested against the compounds for 40 protein targets available in the Directory of Useful Decoys and the performance was evaluated using the area under the ROC curve (AUC), the Enrichment Factor (EF) and Hit Rate (HR). LIGSIFT-based VS shows an average AUC of 0.79, average EF values of 20.8 and a HR of 59% in the top 1% of the screened library.
LIGSIFT software, including the source code, is freely available to academic users at http://cssb.biology.gatech.edu/LIGSIFT.
Supplementary data are available at Bioinformatics online.
在计算机辅助药物发现中，基于形状的小分子比对是一种广泛使用的方法。大多数基于形状的配体结构比对应用程序，无论是商业的还是免费的，都使用塔尼莫托系数或类似函数来评估分子相似性。使用这些函数的主要缺点是得分的大小依赖性以及未报告使用此类指标的分子匹配的统计显著性。
我们描述了一种新的开源配体结构比对和虚拟筛选（VS）算法LIGSIFT，它使用高斯分子形状叠加进行快速小分子比对，并基于得分的统计显著性使用与大小无关的评分函数进行高效的VS。针对《有用诱饵目录》中可用的40种蛋白质靶点的化合物对LIGSIFT进行了测试，并使用ROC曲线下面积（AUC）、富集因子（EF）和命中率（HR）评估性能。基于LIGSIFT的VS在筛选库的前1%中显示平均AUC为0.79，平均EF值为20.8，HR为59%。
学术用户可在http://cssb.biology.gatech.edu/LIGSIFT免费获得包括源代码在内的LIGSIFT软件。
补充数据可在《生物信息学》在线获取。
