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Identifying new topoisomerase II poison scaffolds by combining publicly available toxicity data and 2D/3D-based virtual screening
Journal of Cheminformatics ( IF 8.6 ) Pub Date : 2019-11-09 , DOI: 10.1186/s13321-019-0390-3
Anna Lovrics , Veronika F. S. Pape , Dániel Szisz , Adrián Kalászi , Petra Heffeter , Csaba Magyar , Gergely Szakács

Molecular descriptor (2D) and three dimensional (3D) shape based similarity methods are widely used in ligand based virtual drug design. In the present study pairwise structure comparisons among a set of 4858 DTP compounds tested in the NCI60 tumor cell line anticancer drug screen were computed using chemical hashed fingerprints and 3D molecule shapes to calculate 2D and 3D similarities, respectively. Additionally, pairwise biological activity similarities were calculated by correlating the 60 element vectors of pGI50 values corresponding to the cytotoxicity of the compounds across the NCI60 panel. Subsequently, we compared the power of 2D and 3D structural similarity metrics to predict the toxicity pattern of compounds. We found that while the positive predictive value and sensitivity of 3D and molecular descriptor based approaches to predict biological activity are similar, a subset of molecule pairs yielded contradictory results. By simultaneously requiring similarity of biological activities and 3D shapes, and dissimilarity of molecular descriptor based comparisons, we identify pairs of scaffold hopping candidates displaying characteristic core structural changes such as heteroatom/heterocycle change and ring closure. Attempts to discover scaffold hopping candidates of mitoxantrone recovered known Topoisomerase II (Top2) inhibitors, and also predicted new, previously unknown chemotypes possessing in vitro Top2 inhibitory activity.

中文翻译:

通过结合公开获得的毒性数据和基于2D / 3D的虚拟筛选来识别新的拓扑异构酶II毒物支架

基于分子描述符(2D)和基于三维(3D)形状的相似性方法已广泛用于基于配体的虚拟药物设计中。在本研究中,使用化学哈希指纹和3D分子形状分别计算2D和3D相似度,计算了在NCI60肿瘤细胞系抗癌药物筛选中测试的4858种DTP化合物之间的成对结构比较。另外,通过将pGI50值的60个元素载体与对应于整个NCI60组的化合物的细胞毒性相关联,来计算成对的生物学活性相似性。随后,我们比较了2D和3D结构相似性指标的功效,以预测化合物的毒性模式。我们发现,虽然3D的阳性预测值和敏感性以及基于分子描述符的预测生物活性的方法相似,但一部分分子对却产生了矛盾的结果。通过同时要求相似的生物活性和3D形状,以及基于分子描述子的比较的相似性,我们确定了成对的支架跳跃候选物,它们显示出特征性的核心结构变化,例如杂原子/杂环变化和闭环。尝试发现米托蒽醌的支架跳跃候选者回收了已知的拓扑异构酶II(Top2)抑制剂,并且还预测了具有体外Top2抑制活性的新的,以前未知的化学型。通过同时要求相似的生物活性和3D形状,以及基于分子描述子的比较的相似性,我们确定了成对的支架跳跃候选物,它们显示出特征性的核心结构变化,例如杂原子/杂环变化和闭环。尝试发现米托蒽醌的支架跳跃候选者回收了已知的拓扑异构酶II(Top2)抑制剂,并且还预测了具有体外Top2抑制活性的新的,以前未知的化学型。通过同时要求相似的生物活性和3D形状,以及基于分子描述符的比较的相似性,我们确定了支架跳跃候选对,它们显示出特征性的核心结构变化,例如杂原子/杂环变化和闭环。尝试发现米托蒽醌的支架跳跃候选者回收了已知的拓扑异构酶II(Top2)抑制剂,并且还预测了具有体外Top2抑制活性的新的,以前未知的化学型。
更新日期:2019-11-09
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