Recent years have seen progress in druggability simulations, that is, molecular dynamics simulations of target proteins in solutions containing drug-like probe molecules to characterize their drug-binding abilities, if any. An important consecutive step is to analyze the trajectories to construct pharmacophore models (PMs) to use for virtual screening of libraries of small molecules. While considerable success has been observed in this type of computer-aided drug discovery, a systematic tool encompassing multiple steps from druggability simulations to pharmacophore modeling, to identifying hits by virtual screening of libraries of compounds, has been lacking. We address this need here by developing a new tool, Pharmmaker, building on the DruGUI module of our ProDy application programming interface. Pharmmaker is composed of a suite of steps: (Step 1) identification of high affinity residues for each probe molecule type; (Step 2) selecting high affinity residues and hot spots in the vicinity of sites identified by DruGUI; (Step 3) ranking of the interactions between high affinity residues and specific probes; (Step 4) obtaining probe binding poses and corresponding protein conformations by collecting top-ranked snapshots; and (Step 5) using those snapshots for constructing PMs. The PMs are then used as filters for identifying hits in structure-based virtual screening. Pharmmaker, accessible online at http://prody.csb.pitt.edu/pharmmaker, can be used in conjunction with other tools available in ProDy.

中文翻译：

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Pharmmaker：基于可药物模拟的药效基团建模和命中识别。

近年来，在药物模拟中，即在含有药物样探针分子的溶液中对目标蛋白进行分子动力学模拟以表征其药物结合能力的过程中，已经取得了进展。一个重要的连续步骤是分析轨迹，以构建药效基团模型（PMs），用于虚拟筛选小分子文库。尽管已经在这种计算机辅助药物发现中获得了相当大的成功，但仍缺乏一种系统的工具，该工具涵盖了从可药物性模拟到药效基团建模的多个步骤，以及通过虚拟筛选化合物库来鉴定命中物的方法。我们在此方面通过在ProDy应用程序编程接口的DruGUI模块上构建新工具Pharmmaker来满足这一需求。Pharmmaker由一系列步骤组成：（步骤1）鉴定每种探针分子类型的高亲和力残基；（步骤2）在DruGUI识别的位点附近选择高亲和力残基和热点；（步骤3）对高亲和力残基与特异性探针之间的相互作用进行排名；（步骤4）通过收集排名靠前的快照来获得探针结合姿势和相应的蛋白质构象；（第5步）使用这些快照来构建PM。然后将PM用作筛选器，以在基于结构的虚拟筛选中识别命中。可在http://prody.csb.pitt.edu/pharmmaker上在线访问的Pharmmaker，可以与ProDy中提供的其他工具结合使用。（步骤3）对高亲和力残基与特异性探针之间的相互作用进行排名；（步骤4）通过收集排名靠前的快照来获得探针结合姿势和相应的蛋白质构象；（第5步）使用这些快照来构建PM。然后将PM用作筛选器，以在基于结构的虚拟筛选中识别命中。可在http://prody.csb.pitt.edu/pharmmaker上在线访问的Pharmmaker，可以与ProDy中提供的其他工具结合使用。（步骤3）对高亲和力残基与特异性探针之间的相互作用进行排名；（步骤4）通过收集排名靠前的快照来获得探针结合姿势和相应的蛋白质构象；（第5步）使用这些快照来构建PM。然后将PM用作筛选器，以在基于结构的虚拟筛选中识别命中。可在http://prody.csb.pitt.edu/pharmmaker上在线访问的Pharmmaker，可以与ProDy中提供的其他工具结合使用。