Reisdorf William C, Chhugani Neha, Sanseau Philippe, Agarwal Pankaj
a Computational Biology, Target Sciences , GlaxoSmithKline R&D , King of Prussia , PA , USA.
b Jacobs School of Engineering , University of California San Diego , Belle Mead , NJ , USA.
Expert Opin Drug Discov. 2017 Jul;12(7):687-693. doi: 10.1080/17460441.2017.1329296. Epub 2017 May 23.
Discovering, developing and validating new disease treatments is a challenging and time-consuming endeavor. Successful drug discovery hinges on selecting the best drug targets with relevance to human disease and evidence that modulating them will be beneficial for patients. Open data initiatives are increasingly placing such knowledge into the public domain. Areas covered: In this review, the authors discuss emerging resources such as Open Targets which integrate key information to prioritize target-disease connections. Researchers can use it, along with other resources, to select potential new therapeutic targets to initiate drug discovery projects. They also discuss public resources such as DrugBank and ChEMBL that offer potential tools to interrogate these targets. Expert opinion: In our opinion, publically available resources are democratizing and connecting information, enabling disease experts to access and prioritize targets of interest in ways that were not possible a few years ago. Moreover, there are several modalities in addition to small molecule perturbation to modulate a target's activity. Drug discovery scientists can now utilize these new resources to simultaneously evaluate a much larger number of targets than previously possible.
发现、开发和验证新的疾病治疗方法是一项具有挑战性且耗时的工作。成功的药物发现取决于选择与人类疾病相关的最佳药物靶点，以及调节这些靶点对患者有益的证据。开放数据倡议正越来越多地将此类知识置于公共领域。涵盖领域：在本综述中，作者讨论了诸如Open Targets等新兴资源，这些资源整合关键信息以对靶点-疾病关联进行优先级排序。研究人员可以将其与其他资源一起用于选择潜在的新治疗靶点，以启动药物发现项目。他们还讨论了诸如DrugBank和ChEMBL等公共资源，这些资源提供了探究这些靶点的潜在工具。专家意见：我们认为，公开可用的资源正在使信息民主化并建立联系，使疾病专家能够以几年前不可能的方式获取感兴趣的靶点并对其进行优先级排序。此外，除了小分子扰动之外，还有几种调节靶点活性的方式。药物发现科学家现在可以利用这些新资源同时评估比以前更多的靶点。
