BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization.
BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization.
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BCL::Mol2D - 用于 QSAR 建模和先导化合物优化的强大原子环境描述符。
DOI：
10.1007/s10822-019-00199-8
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发表时间：
2019
影响因子：
3.5
通讯作者：
Meiler,Jens
中科院分区：
文献类型：
--
作者：
Vu,Oanh;Mendenhall,Jeffrey;Altarawy,Doaa;Meiler,Jens
比较基于片段的类药物分子指纹图谱是计算机辅助药物发现中最可靠和最常用的方法之一。Molprint2D是一种流行的原子环境（AE）描述符，在最近的一项大规模研究中，它在不同的靶标上产生了最好的活性化合物富集。我们在此展示了BCL::Mol2D描述符，它在九个PubChem数据集上的表现优于Molprint2D，这些数据集涵盖了广泛的蛋白质类别。由于BCL::Mol2D记录了通用AE库中的AE数量，因此BCL::Mol2D优于Molprint2D的一个新方面是其可逆性。这一特性使得从机器学习模型到特定分子子结构的预测分解成为可能。当在BCL::Mol2D描述符上训练时，带有dropout的人工神经网络在logAUC指标上的表现比在Molprint2D描述符上训练的神经网络高出26%。当与我们之前发布的针对qsar优化的描述符集（BCL::Mol2D）结合使用时，BCL::Mol2D产生了适度的改进。最后，我们展示了BCL::Mol2D的可逆性如何使“药效团图”可视化，从而指导丝氨酸/苏氨酸激酶33抑制剂的先导物优化。
Comparing fragment based molecular fingerprints of drug-like molecules is one of the most robust and frequently used approaches in computer-assisted drug discovery. Molprint2D, a popular atom environment (AE) descriptor, yielded the best enrichment of active compounds across a diverse set of targets in a recent large-scale study. We present here BCL::Mol2D descriptors that outperformed Molprint2D on nine PubChem datasets spanning a wide range of protein classes. Because BCL::Mol2D records the number of AEs from a universal AE library, a novel aspect of BCL::Mol2D over the Molprint2D is its reversibility. This property enables decomposition of prediction from machine learning models to particular molecular substructures. Artificial neural networks with dropout, when trained on BCL::Mol2D descriptors outperform those trained on Molprint2D descriptors by up to 26% in logAUC metric. When combined with the Reduced Short Range descriptor set, our previously published set of descriptors optimized for QSARs, BCL::Mol2D yields a modest improvement. Finally, we demonstrate how the reversibility of BCL::Mol2D enables visualization of a ‘pharmacophore map’ that could guide lead optimization for serine/threonine kinase 33 inhibitors.