Design of novel leads: ligand based computational modeling studies on non-nucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1
Design of novel leads: ligand based computational modeling studies on non-nucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1
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DOI：
10.1039/c3mb70218a
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发表时间：
2014-01-01
影响因子：
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通讯作者：
Sapre, Nitin S.
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文献类型：
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作者：
Jain (Pancholi), Nilanjana;Gupta, Swagata;Sapre, Nitin S.
研究人员一直在寻找治疗艾滋病的新抗病毒药物。在目前的工作中，对取代的苯硫基胸腺嘧啶的类似物进行了基于配体的建模研究，该类似物充当非核苷逆转录酶抑制剂（NNRTI）并提取了新的先导化合物。使用基于组中心重叠（S-ALL、HDALL、HA(ALL) 和 R-ALL）的对齐相关描述符、与对齐无关的描述符 (S log P)、拓扑描述符（Balaban 指数 (J)）和 3D 描述符偶极矩 (mu) 以及基于形状的描述符（Kappa 2 指数 ((2)kappa)），导出与抑制活性的相关性。线性和非线性技术已被用来实现该目标。支持向量机（SVM，R = 0.929，R-2 = 0.863）和反向传播神经网络（BPNN，R = 0.928，R-2 = 0.861）方法产生了接近相似的结果，并且优于多元线性回归（MLR，R = 0.915，R-2 = 0.837）。使用测试数据集（SVM：R = 0.846，R-2 = 0.716，BPNN：R = 0.841，R-2 = 0.707 和 MLR：R = 0.833，R-2 = 0.694）对模型的预测能力进行交叉验证。结论是配体的疏水性 (S log P) 和极性 (m) 以及氢供体 (HDALL) 部分的存在是提高抗病毒活性和药物治疗特性的决定因素。基于上述发现，创建了一个虚拟数据集，以提取具有合理抗病毒活性以及更好的药效特性的可能先导化合物。
Researchers are on the constant lookout for new antiviral agents for the treatment of AIDS. In the present work, ligand based modeling studies are performed on analogues of substituted phenyl-thio-thymines, which act as non-nucleoside reverse transcriptase inhibitors (NNRTIs) and novel leads are extracted. Using alignment-dependent descriptors, based on group center overlap (S-ALL, HDALL, HA(ALL) and R-ALL), an alignment-independent descriptor (S log P), a topological descriptor (Balaban index (J)) and a 3D descriptor dipole moment (mu) and shape based descriptors (Kappa 2 index ((2)kappa)), a correlation is derived with inhibitory activity. Linear and non-linear techniques have been used to achieve the goal. Support Vector Machine (SVM, R = 0.929, R-2 = 0.863) and Back Propagation Neural Network (BPNN, R = 0.928, R-2 = 0.861) methods yielded near similar results and outperformed Multiple Linear Regression (MLR, R = 0.915, R-2 = 0.837). The predictive ability of the models are cross-validated using a test dataset (SVM: R = 0.846, R-2 = 0.716, BPNN: R = 0.841, R-2 = 0.707 and MLR: R = 0.833, R-2 = 0.694). It is concluded that the hydrophobicity (S log P) and the polarity (m) of a ligand and the presence of hydrogen donor (HDALL) moieties are the deciding factors in improving antiviral activity and pharmaco-therapeutic properties. Based on the above findings, a virtual dataset is created to extract probable leads with reasonable antiviral activity as well as better pharmacophoric properties.