Molecular Materials Informatics, 1900 St. Jacques #302, Montreal H3J 2S1, Quebec, Canada.
SRI International, 333 Ravenswood Avenue, Menlo Park 94025, CA, USA.
J Cheminform. 2014 Aug 4;6:38. doi: 10.1186/s13321-014-0038-2. eCollection 2014.
We recently developed a freely available mobile app (TB Mobile) for both iOS and Android platforms that displays Mycobacterium tuberculosis (Mtb) active molecule structures and their targets with links to associated data. The app was developed to make target information available to as large an audience as possible.
We now report a major update of the iOS version of the app. This includes enhancements that use an implementation of ECFP_6 fingerprints that we have made open source. Using these fingerprints, the user can propose compounds with possible anti-TB activity, and view the compounds within a cluster landscape. Proposed compounds can also be compared to existing target data, using a näive Bayesian scoring system to rank probable targets. We have curated an additional 60 new compounds and their targets for Mtb and added these to the original set of 745 compounds. We have also curated 20 further compounds (many without targets in TB Mobile) to evaluate this version of the app with 805 compounds and associated targets.
TB Mobile can now manage a small collection of compounds that can be imported from external sources, or exported by various means such as email or app-to-app inter-process communication. This means that TB Mobile can be used as a node within a growing ecosystem of mobile apps for cheminformatics. It can also cluster compounds and use internal algorithms to help identify potential targets based on molecular similarity. TB Mobile represents a valuable dataset, data-visualization aid and target prediction tool.
我们最近开发了一个适用于 iOS 和 Android 平台的免费移动应用程序（TB 移动应用程序），该应用程序可显示结核分枝杆菌（Mtb）活性分子结构及其与相关数据链接的靶标。该应用程序旨在将目标信息提供给尽可能多的受众。
我们现在报告该应用程序的 iOS 版本的重大更新。这包括使用我们开源的 ECFP_6 指纹实现的增强功能。使用这些指纹，用户可以提出具有潜在抗结核活性的化合物，并在聚类景观中查看这些化合物。还可以使用朴素贝叶斯评分系统将提出的化合物与现有目标数据进行比较，以对可能的目标进行排名。我们已经为 Mtb 编辑了另外 60 种新的化合物及其靶标，并将其添加到最初的 745 种化合物集中。我们还编辑了另外 20 种化合物（许多在 TB 移动应用程序中没有靶标），以使用 805 种化合物及其相关靶标评估该版本的应用程序。
TB 移动应用程序现在可以管理一小部分可以从外部来源导入或通过各种方式（如电子邮件或应用程序间进程通信）导出的化合物。这意味着 TB 移动应用程序可以用作化学信息学中不断发展的移动应用程序生态系统中的一个节点。它还可以对化合物进行聚类，并使用内部算法根据分子相似性帮助识别潜在的靶标。TB 移动应用程序代表了一个有价值的数据集、数据可视化辅助工具和靶标预测工具。
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