药物发现
计算机科学
生物信息学
利用
更安全的
管道(软件)
数据科学
过程(计算)
钥匙(锁)
多学科方法
任务(项目管理)
业务流程发现
计算生物学
风险分析(工程)
生物信息学
医学
工程类
生物
在制品
系统工程
计算机安全
生物化学
运营管理
社会科学
业务流程建模
程序设计语言
社会学
操作系统
基因
业务流程
标识
DOI:10.1016/j.pharmthera.2017.02.034
摘要
Drug discovery is a multidisciplinary and multivariate optimization endeavor. As such, in silico screening tools have gained considerable importance to archive, analyze and exploit the vast and ever-increasing amount of experimental data generated throughout the process. The current review will focus on the computer-aided prediction of the numerous properties that need to be controlled during the discovery of a preliminary hit and its promotion to a viable clinical candidate. It does not pretend to the almost impossible task of an exhaustive report but will highlight a few key points that need to be collectively addressed both by chemists and biologists to fuel the drug discovery pipeline with innovative and safe drug candidates.
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