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Structure–activity relationship and binding mode studies for a series of diketo-acids as HIV integrase inhibitors by 3D-QSAR, molecular docking and molecular dynamics simulations

机译:通过3D-QSAR,分子对接和分子动力学模拟作为HIV整合酶抑制剂为HIV整合酶抑制剂的结构 - 活性关系和结合模式研究

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At present, the approved HIV integrase (IN) inhibitors are all diketo-acids (DKAs). To have a better understanding of DKA inhibitors, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), docking, and molecular dynamics (MD) were performed on 88 DKAs. The constructed CoMFA and CoMSIA models were shown to be statistically significant for the training set with the cross-validated value ( q ~(2) ) of 0.94, non cross-validated value ( r ~(2) ) of 0.96 for CoMFA; q ~(2) of 0.96, r ~(2) of 0.94 for CoMSIA. External q ~(2) of the test set Q ~(2) _(F1) , Q ~(2) _(F2) and Q ~(2) _(F3) were 0.79, 0.77 and 0.81 for CoMFA; Q ~(2) _(F1) , Q ~(2) _(F2) and Q ~(2) _(F3) were 0.60, 0.56 and 0.63 for CoMSIA. Further interpretation of contour maps provided instructive insights into the optimization and designing of lead compounds. The interaction between IN and two DKAs (the inhibitors with the highest and lowest activity) were investigated using ‘relaxed receptor’ molecular docking and molecular dynamics simulations. Molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) and molecular mechanics Generalized-Born surface area (MM-GBSA) were employed to evaluate the binding affinity and the energy decomposition for residues, respectively. Further analysis indicated that the dominating effect of van der Waals drives the binding of IN and DKA inhibitors and key residues. In addition, we found that the MD conclusion was consistent with QSAR models after the analysis of the interaction between DKA s and each residue. These findings may be of immense importance in the development of DKA inhibitors.
机译:目前,批准的HIV整合酶(IN)抑制剂是所有Diketo-酸(DKAS)。为了更好地了解DKA抑制剂,对比较分子场分析(COMFA),对比较分子相似性指数分析(COMSIA),对接和分子动力学(MD)进行了88位DKA。对于具有0.94的交叉验证值(Q〜(2))的训练集,构造的COMFA和COMSIA模型被证明是统计学意义的0.94,非交叉验证值(R〜(2))为0.96的COMFA; Q〜(2)为0.96,R〜(2)为0.94的COMSIA。试验集的外部Q〜(2)Q〜(2)_(F1),Q〜(2)_(F2)和Q〜(2)_(F3)为COMFA的0.79,0.77和0.81; Q〜(2)_(F1),Q〜(2)_(F2)和Q〜(2)_(F3)为COMSIA的0.60,0.56和0.63。进一步解释轮廓图提供了对铅化合物的优化和设计的有效洞察。使用“放松的受体”分子对接和分子动力学模拟来研究与两种DKA之间的相互作用(具有最高和最高和最低活性)的相互作用。分子力学泊松博尔兹曼表面积(MM-PBSA)和分子力学广义出生的表面积(MM-GBSA)分别评价残留物的结合亲和力和能量分解。进一步的分析表明,范德沃尔斯的主导效果驱动了in和DKA抑制剂和关键残留物的结合。此外,我们发现MD结论在分析DKA S和每个残留物之间的相互作用后与QSAR模型一致。这些发现在DKA抑制剂的发展中可能具有巨大的重要性。

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