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In silico de novo design of novel NNRTIs: a bio-molecular modelling approach

机译：在新型NNRTIS的Silico De Novo设计中：生物分子建模方法

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Six novel non-nucleoside reverse transcriptase inhibitors exhibiting high efficacy are designed using in silico mathematical modelling techniques and the results are validated using a docking technique. An in silico assessment of interaction potential and structural requirements of 5-alkyl-2-alkylamino-6-(2,6-difluorophenylalkyl)-3,4-dihydropyrimidin-4(3H)-one (DABO) analogues in the non-nucleoside inhibitor binding pocket is also performed. Efficient use of 3D-pharamacophoric (S-ALL, HDALL, HA(ALL) and R-ALL) and 3D-averaged alignment (C log P and dipole moment) descriptors is made in this study. The chemometric analyses, using support vector machine, back propagation neural network and multiple linear regression, are performed. The relative potentials of these chemometric methods is also assessed and the results, SVM (r = 0.939, MSE = 0.071, q(2) = 0.876), BPNN (r = 0.923, MSE = 0.104, q(2) = 0.818) and MLR (r = 0.912, MSE = 0.096, q(2) = 0.832), indicates that SVM describes the relationship between the descriptors and inhibitory activity in a better manner. The results also suggest that there is a non-linear relationship between the descriptors and inhibitory activity. The study further suggests that isopropyl/propenyl groups as R and R', oxobutyl group as X and di or tri-substitution as R" are the best suited substituents for exhibiting better inhibitory activity.
机译：六种新的非核苷逆转录酶抑制剂，在硅数学建模技术中设计了高功效，并使用对接技术进行验证结果。在非核苷中的三烷基-2-烷基氨基-6-（2,6-二氟苯烷基烷基）-3,4-二氢吡啶胺-4（3h） - One（Dabo）类似物的相互作用电位和结构要求的硅的相互作用电位和结构要求还进行抑制剂结合袋。在本研究中有效地使用3D-Pharamophoric（S-All，HDALL，HA（ALL）和3D平均对准（C log P和偶极矩）描述符。使用支持向量机，后传播神经网络和多个线性回归的化学计量分析。还评估了这些化学计量方法的相对电位，结果SVM（R = 0.939，MSE = 0.071，Q（2）= 0.876），BPNN（r = 0.923，MSE = 0.104，Q（2）= 0.818）和MLR（r = 0.912，MSE = 0.096，Q（2）= 0.832），表明SVM以更好的方式描述了描述符和抑制活动之间的关系。结果还表明描述符和抑制活动之间存在非线性关系。该研究进一步表明，作为R和R'，氧丁基作为X和DI或三级作为R“的异丙基/丙基是最适合于表现出更好的抑制活性的最终取代基。

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