table2_QSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites.xlsx

Parasitic diseases remain as unresolved health issues worldwide. While for some parasites the treatments involve drug combinations with serious side effects, for others, chemical therapies are inefficient due to the emergence of drug resistance. This urges the search for novel antiparasitic agents able to act through multiple mechanisms of action. Here, we report the first multi-target model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mt-QSAR-MLP) to virtually design and predict versatile inhibitors of proteins involved in the survival and/or infectivity of different pathogenic parasites. The mt-QSAR-MLP model exhibited high accuracy (>80%) in both training and test sets for the classification/prediction of protein inhibitors. Several fragments were directly extracted from the physicochemical and structural interpretations of the molecular descriptors in the mt-QSAR-MLP model. Such interpretations enabled the generation of four molecules that were predicted as multi-target inhibitors against at least three of the five parasitic proteins reported here with two of the molecules being predicted to inhibit all the proteins. Docking calculations converged with the mt-QSAR-MLP model regarding the multi-target profile of the designed molecules. The designed molecules exhibited drug-like properties, complying with Lipinski’s rule of five, as well as Ghose’s filter and Veber’s guidelines.

寄生虫病仍是全球范围内尚未解决的公共卫生难题。部分寄生虫病的治疗需采用联合用药方案，但会引发严重不良反应；而另一些则因耐药性的出现，化学疗法已难以奏效。这推动了新型抗寄生虫药物的研发需求，此类药物需能够通过多种作用机制发挥药效。本研究首次报道了一种基于定量构效关系（Quantitative Structure-Activity Relationship, QSAR）与多层感知器神经网络（Multilayer Perceptron Neural Network, MLP）的多靶点模型（mt-QSAR-MLP），用于虚拟设计并预测可靶向多种致病寄生虫存活与/或侵染相关蛋白的广谱抑制剂。该mt-QSAR-MLP模型在训练集与测试集上对蛋白抑制剂的分类与预测均展现出高于80%的高精度。研究人员直接从mt-QSAR-MLP模型中分子描述符的理化与结构解析结果中提取得到若干特征片段。通过此类解析，共设计得到4种分子，经预测可靶向本研究报道的5种寄生虫蛋白中的至少3种，其中2种分子被预测可靶向全部5种蛋白。分子对接计算结果与mt-QSAR-MLP模型对设计分子的多靶点特性预测结果一致。所设计的分子均具备类药性质，符合Lipinski五规则（Lipinski's Rule of Five）、Ghose筛选准则与Veber指南要求。