基于受体结构的虚拟筛选在先导化合物发现中的应用
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摘要
基于受体结构的虚拟筛选（分子对接）在新型先导化合物的发现中具有重要意义。为了提高配体结合自由能计算的精度，我们在前人工作的基础上系统研究了基于经典物理学原理的MM-PB/SA方法。本论文主要包括以下几个方面：
1.我们发现在MM-PB/SA方法中存在“溶剂真空”等问题，通过固定外壳层溶剂分子和多次平衡补水可以显著提高其预测能力，并且在不同类型的药物靶标上都具有良好的适用性。
2.为了将这种能够更精确计算结合能的方法用于寻找先导化合物的实践工作中，我们按照兼顾效率和准确性的原则，发展了一套逐级虚拟筛选的策略，并以传统抗癌靶点——微管蛋白作为研究对象来检验该策略的实用性。针对秋水仙素结合位点，逐级虚拟筛选方法从超过100000个不同的类药性分子中产生了63个候选化合物，我们从中挑选出9个结构相似、预测作用模式相同的化合物进行实验验证，5个分子被确认为阳性化合物，进一步的构效关系研究验证了计算预测的作用模式。同时，先导化合物在细胞水平上有抑制肿瘤细胞增殖的能力，并且证明能作用于秋水仙素位点。
3.我们进一步发展了组合虚拟筛选的方法来寻找多靶标配体分子，以BCR-ABL融合蛋白作为研究对象，针对ATP结合位点寻找能够同时抑制野生型和耐药型（T315I突变）的ABL激酶抑制剂。从组合虚拟筛选自动产生的18个共有噻吩母核结构的化合物中，我们挑选出9个作用模式相同的候选分子进行实验验证，3个化合物被证明有明显的双抑制活性。和正常的Ba/F3细胞系相比，先导化合物能够显著抑制ABL（野生型和耐药型）驱动的细胞增殖，同时对其他肿瘤细胞系也都有一定的抑制作用。
4.在以上两个不同靶点（微管蛋白和ABL激酶）的筛选结果中，有相同先导化合物被证实为双靶标配体分子。在该基础上，我们发现了ATP结合位点和秋水仙素位点在口袋形状和与小分子的作用模式上存在很大的相似性，而这种特征是传统的基于比对的结构分析方法很难揭示的。
Structure-based virtual screening (molecular docking) plays important role indiscovering novel lead compounds. To improve the accuracy of ligand bindingfree-energy calculation, we systematically investigated physics-based MM-PB/SAmethod based on previous published work. This thesis mainly includes the followingaspects:
1. Current default MM-PB/SA protocol may be improved, including the setup ofsolvent model and the adjustments of parameters. We demonstrated that the optimizedMM-PB/SA protocol significantly improves the prediction power in data setcontaining three representative drug targets.
2. To impletement MM-PB/SA method in the practice of lead compounddiscovery, we developed a hierarchical virtual screening strategy to strike thebanlance between efficiency and accuracy. We evaluated the performance of thisstrategy in the case of tubulin. Our hierarchical strategy generated63candidatesautomatically from more than100000diverse drug-like compounds.9molecules withsimilar strcture and predicted binding modes were selected for experimental test,among which5were active. Further structure-activity relationship study validated ourcomputational model.
3. We further developed combinatorial virtual screening method to exploremulti-target inhibitors. Using BCR-ABL protein as our model system, we aimed toidentify dual-inhibitors to target the ATP-site on both wild-type ABL kinase anddrug-resistance T315I mutant. Consequently,3of9candidates resulted from virtualscreening were experimentally validated as true binders with significantdual-inhibition activity. Encouragingly, the identified candidates inhibit proliferationof ABL-driven Ba/F3cell lines (both wild-type and drug-resistance) comparing withnormal Ba/F3cell line. These compounds also show inhibition on BCR-ABL highlyexpressed tumor cell, such as K562.
4. Interestingly, one same lead compound was identified to target both tubulinand ABL kinase. Thus, we discovered the similar binding characteristics between twocompletely dissimilar binding sites, colchicine site in Tubulin and ATP binding site inABL kinase. Importantly, these characteristics can’t be revealed by conventionalsequence or structural similarity analysis.
1.我们发现在MM-PB/SA方法中存在“溶剂真空”等问题，通过固定外壳层溶剂分子和多次平衡补水可以显著提高其预测能力，并且在不同类型的药物靶标上都具有良好的适用性。
2.为了将这种能够更精确计算结合能的方法用于寻找先导化合物的实践工作中，我们按照兼顾效率和准确性的原则，发展了一套逐级虚拟筛选的策略，并以传统抗癌靶点——微管蛋白作为研究对象来检验该策略的实用性。针对秋水仙素结合位点，逐级虚拟筛选方法从超过100000个不同的类药性分子中产生了63个候选化合物，我们从中挑选出9个结构相似、预测作用模式相同的化合物进行实验验证，5个分子被确认为阳性化合物，进一步的构效关系研究验证了计算预测的作用模式。同时，先导化合物在细胞水平上有抑制肿瘤细胞增殖的能力，并且证明能作用于秋水仙素位点。
3.我们进一步发展了组合虚拟筛选的方法来寻找多靶标配体分子，以BCR-ABL融合蛋白作为研究对象，针对ATP结合位点寻找能够同时抑制野生型和耐药型（T315I突变）的ABL激酶抑制剂。从组合虚拟筛选自动产生的18个共有噻吩母核结构的化合物中，我们挑选出9个作用模式相同的候选分子进行实验验证，3个化合物被证明有明显的双抑制活性。和正常的Ba/F3细胞系相比，先导化合物能够显著抑制ABL（野生型和耐药型）驱动的细胞增殖，同时对其他肿瘤细胞系也都有一定的抑制作用。
4.在以上两个不同靶点（微管蛋白和ABL激酶）的筛选结果中，有相同先导化合物被证实为双靶标配体分子。在该基础上，我们发现了ATP结合位点和秋水仙素位点在口袋形状和与小分子的作用模式上存在很大的相似性，而这种特征是传统的基于比对的结构分析方法很难揭示的。
Structure-based virtual screening (molecular docking) plays important role indiscovering novel lead compounds. To improve the accuracy of ligand bindingfree-energy calculation, we systematically investigated physics-based MM-PB/SAmethod based on previous published work. This thesis mainly includes the followingaspects:
1. Current default MM-PB/SA protocol may be improved, including the setup ofsolvent model and the adjustments of parameters. We demonstrated that the optimizedMM-PB/SA protocol significantly improves the prediction power in data setcontaining three representative drug targets.
2. To impletement MM-PB/SA method in the practice of lead compounddiscovery, we developed a hierarchical virtual screening strategy to strike thebanlance between efficiency and accuracy. We evaluated the performance of thisstrategy in the case of tubulin. Our hierarchical strategy generated63candidatesautomatically from more than100000diverse drug-like compounds.9molecules withsimilar strcture and predicted binding modes were selected for experimental test,among which5were active. Further structure-activity relationship study validated ourcomputational model.
3. We further developed combinatorial virtual screening method to exploremulti-target inhibitors. Using BCR-ABL protein as our model system, we aimed toidentify dual-inhibitors to target the ATP-site on both wild-type ABL kinase anddrug-resistance T315I mutant. Consequently,3of9candidates resulted from virtualscreening were experimentally validated as true binders with significantdual-inhibition activity. Encouragingly, the identified candidates inhibit proliferationof ABL-driven Ba/F3cell lines (both wild-type and drug-resistance) comparing withnormal Ba/F3cell line. These compounds also show inhibition on BCR-ABL highlyexpressed tumor cell, such as K562.
4. Interestingly, one same lead compound was identified to target both tubulinand ABL kinase. Thus, we discovered the similar binding characteristics between twocompletely dissimilar binding sites, colchicine site in Tubulin and ATP binding site inABL kinase. Importantly, these characteristics can’t be revealed by conventionalsequence or structural similarity analysis.
引文
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