Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets

查看全文 作　　者：Huiqin [1]He;Benquan [1]Liu;Hongyi [1]Luo;Tingting [1]Zhang;Jingwei [2]Jiang

机构地区：[1]Jiangsu Key Lab of Drug Screening,China Pharmaceutical University,Nanjing,China;[2]Institute of Pharmacologic Science,China Pharmaceutical University,Nanjing,China

出　　处：《Stroke & Vascular Neurology》索引2020年第5卷第4期,共7页

基　　金：supported by NSFC(No.81872892 and No.2018ZX09735001-004);“Double First-Class”University project(No.CPU2018GY20 and No.CPU2018GY38). 摘　　要：The discovery of targeted drugs heavily relies on three-dimensional(3D)structures of target proteins.When the 3D structure of a protein target is unknown,it is very difficult to design its corresponding targeted drugs.Although the 3D structures of some proteins(the so-called undruggable targets)are known,their targeted drugs are still absent.As increasing crystal/cryogenicelectron microscopy structures are deposited in Protein Data Bank,it is much more possible to discover the targeted drugs.Moreover,it is also highly probable to turn previous undruggable targets into druggable ones when we identify their hidden allosteric sites.In this review,we focus on the currently available advanced methods for the discovery of novel compounds targeting proteins without 3D structure and how to turn undruggable targets into druggable ones. 关键词：STRUCTURE OVERCOME DRUGS

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Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets

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