Centre for Computational Biology, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G 1X8, Canada.
Molecules. 2010 Jun 17;15(6):4382-400. doi: 10.3390/molecules15064382.
This work proposes a computational procedure for structure-based lead generation and optimization, which relies on the complementarity of the protein-ligand interactions. This procedure takes as input the known structure of a protein-ligand complex. Retaining the positions of the ligand heavy atoms in the protein binding site it designs structurally similar compounds considering all possible combinations of atomic species (N, C, O, CH(3), NH, etc). Compounds are ranked based on a score which incorporates energetic contributions evaluated using molecular mechanics force fields. This procedure was used to design new inhibitor molecules for three serine/threonine protein kinases (p38 MAP kinase, p42 MAP kinase (ERK2), and c-Jun N-terminal kinase 3 (JNK3)). For each enzyme, the calculations produce a set of potential inhibitors whose scores are in agreement with IC50 data and Ki values. Furthermore, the native ligands for each protein target, scored within the five top-ranking compounds predicted by our method, one of the top-ranking compounds predicted to inhibit JNK3 was synthesized and his inhibitory activity confirmed against ATP hydrolysis. Our computational procedure is therefore deemed to be a useful tool for generating chemically diverse molecules active against known target proteins.
这项工作提出了一种基于结构的先导物生成和优化的计算程序，该程序依赖于蛋白质-配体相互作用的互补性。该程序以已知的蛋白质-配体复合物结构为输入，保留配体在蛋白质结合部位的重原子位置，考虑所有可能的原子种类（N、C、O、CH(3)、NH 等）的组合，设计结构相似的化合物。化合物根据包含使用分子力学力场评估的能量贡献的分数进行排序。该程序用于设计三种丝氨酸/苏氨酸蛋白激酶（p38 MAP 激酶、p42 MAP 激酶（ERK2）和 c-Jun N 末端激酶 3（JNK3））的新抑制剂分子。对于每种酶，计算产生一组潜在的抑制剂，其分数与 IC50 数据和 Ki 值一致。此外，对于每个蛋白质靶标，在我们的方法预测的五个排名最高的化合物中对天然配体进行评分，预测对 JNK3 具有抑制活性的排名最高的化合物之一被合成并证实对 ATP 水解具有抑制活性。因此，我们的计算程序被认为是生成针对已知靶蛋白的化学多样性分子的有用工具。
