The Julius Spokojny Bioorganic Chemistry Laboratory, Department of Chemistry, Bar Ilan University, Ramat Gan 52900, Israel.
J Chem Inf Model. 2010 Dec 27;50(12):2256-65. doi: 10.1021/ci100330y. Epub 2010 Nov 19.
We introduce an enzyme mechanism-based method (EMBM) aimed at rational design of chemical sites (CS) of reaction coordinate analog inhibitors. The energy of valence reorganization of CS, caused by the formation of the enzyme-inhibitor covalent complex, is accounted for by new covalent descriptors W1 and W2. We considered CS fragments with a carbonyl reactivity center, like in native protease substrates. The W1 and W2 descriptors are calculated quantum mechanically on small molecular clusters simulating the reaction core of the formed covalent tetrahedral complex, anionic TC(O-) or neutral TC(OH). The modeling on a reaction core allows generation of various CS and corresponding TC(O-) and TC(OH) as universal building blocks of real inhibitors and their covalent complexes with serine or cysteine hydrolases. Moreover, the approach avoids the need for 3D structure of the target enzyme, so EMBM may be used for ligand-based design. We have built a chemical site of inhibitors (CSI) databank with pairs of W1 and W2 descriptors precalculated for both CH₃O(-) and CH₃S(-) nucleophiles for every collected CS fragment. We demonstrated that contribution of a CS fragment to the binding affinity of an inhibitor depends on both its covalent reorganization during the chemical transformation and its noncovalent interactions in the enzyme active site. Consequently, prediction of inhibitors binding trend can be done only by accounting for all of these factors, using W1 and W2 in combination with noncovalent QSAR descriptors.
我们介绍了一种基于酶机制的方法(EMBM),旨在合理设计反应坐标类似物抑制剂的化学位点(CS)。CS 的价重组能,由酶-抑制剂共价复合物的形成引起,由新的共价描述符 W1 和 W2 来解释。我们考虑了具有羰基反应性中心的 CS 片段,就像天然蛋白酶底物一样。W1 和 W2 描述符是在模拟形成的共价四面体复合物、阴离子 TC(O-) 或中性 TC(OH)的反应核心的小分子团簇上进行量子力学计算的。在反应核心上进行建模允许生成各种 CS 以及相应的 TC(O-)和 TC(OH),它们是真实抑制剂及其与丝氨酸或半胱氨酸水解酶形成的共价复合物的通用构建块。此外,该方法避免了对靶酶 3D 结构的需求,因此 EMBM 可用于基于配体的设计。我们构建了一个抑制剂化学位点(CSI)数据库,其中为每个收集的 CS 片段预先计算了 CH₃O(-)和 CH₃S(-)亲核试剂的 W1 和 W2 描述符对。我们证明,CS 片段对抑制剂结合亲和力的贡献取决于其在化学转化过程中的共价重排以及其在酶活性位点中的非共价相互作用。因此,只有通过考虑所有这些因素,使用 W1 和 W2 与非共价 QSAR 描述符相结合,才能预测抑制剂的结合趋势。