Iterative refinement of a binding pocket model: active computational steering of lead optimization.
Iterative refinement of a binding pocket model: active computational steering of lead optimization.
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DOI：
10.1021/jm301210j
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发表时间：
2012-10-25
影响因子：
7.3
通讯作者：
Jain, Ajay N.
中科院分区：
文献类型：
--
作者：
Varela, Rocco;Walters, W. Patrick;Goldman, Brian B.;Jain, Ajay N.
结合亲和力预测的计算方法最常通过一系列分子内的交叉验证或通过盲法测试集上显示的性能来证明。在这里，我们展示了这样一个系统如何在迭代，时间领先的优化练习。一系列具有已知合成顺序的促旋酶抑制剂形成了一组可以被选择用于“合成”的分子。从少量分子开始，仅基于结构和活性，构建了一个模型。化合物的选择是通过计算进行的，每次选择五个基于高活性的置信预测，五个基于三维结构新奇的定量测量。化合物选择后，使用新数据进行模型优化。迭代计算候选选择产生快速改善所选化合物的活性，并纳入明确的新化合物发现更多样化的活性抑制剂比缺乏积极的新奇选择的策略。
Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.” Beginning with a small number of molecules, based only on structures and activities, a model was constructed. Compound selection was done computationally, each time making five selections based on confident predictions of high activity and five selections based on a quantitative measure of three-dimensional structural novelty. Compound selection was followed by model refinement using the new data. Iterative computational candidate selection produced rapid improvements in selected compound activity, and incorporation of explicitly novel compounds uncovered much more diverse active inhibitors than strategies lacking active novelty selection.
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DOI：
10.1021/ci010132r
发表时间：
2002-11-01
期刊：
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
影响因子：
--
作者：
Durant, JL;Leland, BA;Nourse, JG
通讯作者：
Nourse, JG
影响因子：
3.5
作者：
Jain AN;Cleves AE
通讯作者：
Cleves AE
影响因子：
5.6
作者：
Fujiwara, Yukiko;Yamashita, Yoshiko;Shimizu, Ryo
通讯作者：
Shimizu, Ryo
影响因子：
5.6
作者：
Chen, Bin;Sheridan, Robert P.;Voigt, Johannes H.
通讯作者：
Voigt, Johannes H.
影响因子：
7.3
作者：
Langham, James J.;Cleves, Ann E.;Jain, Ajay N.
通讯作者：
Jain, Ajay N.