一类新的有效的非手性吲哚-3-羧胺基肾素抑制剂的对接对准- 3d - qsar

Jahan B. Ghasemi, S. Pirhadi
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引用次数: 7

摘要

利用CDOCKER算法对接分析生成的构象,建立3D-QSAR模型;CoMFA区域聚焦(CoMFA- rf)和CoMSIA是一类新的有效的非手性肾素抑制剂。与CoMFA相比,CoMFA- rf和CoMSIA基于对接对准的预测结果令人满意。通过使用测试集、交叉验证(留一个和留十个)、bootstrapping和渐进置乱进一步验证了模型的鲁棒性和可预测性。采用全取向搜索(AOS)策略获取最佳取向,最大限度地减少初始取向对定向化合物的影响。3D-QSAR模型的结果与对接结果一致。此外,所得到的3D CoMFA-RF/ CoMSIA等高线图和相应的模型被用于设计新的和更有效的抑制剂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Docking alignment-3D-QSAR of a new class of potent and non-chiral indole-3-carboxamide-based renin inhibitors
Using generated conformations from docking analysis by CDOCKER algorithm, some 3D-QSAR models; CoMFA region focusing (CoMFA-RF) and CoMSIA have been created on a series of a new class of potent and non-chiral renin inhibitors. The satisfactory predictions were obtained by CoMFA-RF and CoMSIA based on docking alignment in comparison to CoMFA. Robustness and predictability of the models were further verified by using the test set, cross validation (leave one out and leave ten out), bootstrapping, and progressive scrambling. All-orientation search (AOS) strategy was used to acquire the best orientation and minimize the effect of the initial orientation of aligned compounds. The results of 3D-QSAR models are in agreement with docking results. Moreover, the resulting 3D CoMFA-RF/ CoMSIA contour maps and corresponding models were applied to design new and more active inhibitors.
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