Glicksberg Benjamin S, Li Li, Chen Rong, Dudley Joel, Chen Bin
Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
Department of Genetics and Genomic Sciences, Institute of Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Methods Mol Biol. 2019;1939:91-118. doi: 10.1007/978-1-4939-9089-4_6.
The surge of public disease and drug-related data availability has facilitated the application of computational methodologies to transform drug discovery. In the current chapter, we outline and detail the various resources and tools one can leverage in order to perform such analyses. We further describe in depth the in silico workflows of two recent studies that have identified possible novel indications of existing drugs. Lastly, we delve into the caveats and considerations of this process to enable other researchers to perform rigorous computational drug discovery experiments of their own.
公共疾病和药物相关数据可用性的激增推动了计算方法在药物发现中的应用。在本章中，我们概述并详细介绍了可用于进行此类分析的各种资源和工具。我们还深入描述了两项近期研究的计算机模拟工作流程，这些研究确定了现有药物可能的新适应症。最后，我们深入探讨了这一过程中的注意事项，以使其他研究人员能够开展自己严谨的计算机辅助药物发现实验。
