Pinto Gaspar P, Vavra Ondrej, Filipovic Jiri, Stourac Jan, Bednar David, Damborsky Jiri
Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, Brno, Czechia.
International Centre for Clinical Research, St. Anne's University Hospital Brno, Brno, Czechia.
Front Chem. 2019 Oct 29;7:709. doi: 10.3389/fchem.2019.00709. eCollection 2019.
Protein tunnels and channels are attractive targets for drug design. Drug molecules that block the access of substrates or release of products can be efficient modulators of biological activity. Here, we demonstrate the applicability of a newly developed software tool CaverDock for screening databases of drugs against pharmacologically relevant targets. First, we evaluated the effect of rigid and flexible side chains on sets of substrates and inhibitors of seven different proteins. In order to assess the accuracy of our software, we compared the results obtained from CaverDock calculation with experimental data previously collected with heat shock protein 90α. Finally, we tested the virtual screening capabilities of CaverDock with a set of oncological and anti-inflammatory FDA-approved drugs with two molecular targets-cytochrome P450 17A1 and leukotriene A4 hydrolase/aminopeptidase. Calculation of rigid trajectories using four processors took on average 53 min per molecule with 90% successfully calculated cases. The screening identified functional tunnels based on the profile of potential energies of binding and unbinding trajectories. We concluded that CaverDock is a sufficiently fast, robust, and accurate tool for screening binding/unbinding processes of pharmacologically important targets with buried functional sites. The standalone version of CaverDock is available freely at https://loschmidt.chemi.muni.cz/caverdock/ and the web version at https://loschmidt.chemi.muni.cz/caverweb/.
蛋白质通道是药物设计的诱人靶点。能够阻断底物进入或产物释放的药物分子可以成为生物活性的有效调节剂。在此，我们展示了新开发的软件工具CaverDock在针对药理学相关靶点筛选药物数据库方面的适用性。首先，我们评估了刚性和柔性侧链对七种不同蛋白质的底物和抑制剂集合的影响。为了评估我们软件的准确性，我们将CaverDock计算得到的结果与之前用热休克蛋白90α收集的实验数据进行了比较。最后，我们用一组经美国食品药品监督管理局批准的肿瘤学和抗炎药物对CaverDock的虚拟筛选能力进行了测试，这些药物有两个分子靶点——细胞色素P450 17A1和白三烯A4水解酶/氨肽酶。使用四个处理器计算刚性轨迹，每个分子平均耗时53分钟，成功计算的案例占90%。筛选基于结合和解离轨迹的势能分布识别出了功能性通道。我们得出结论，CaverDock是一种足够快速、稳健且准确的工具，可用于筛选具有埋藏功能位点的药理学重要靶点的结合/解离过程。CaverDock的独立版本可在https://loschmidt.chemi.muni.cz/caverdock/免费获取，网络版本可在https://loschmidt.chemi.muni.cz/caverweb/获取。
