摘要
基于片段的药物设计(Fragment-Based Drug Design,FBDD)是药物研发的主流方法之一。如何高效从海量药物大数据中筛选出具有相似分子片段的药物小分子成为生物化学研究领域的挑战性问题。针对目前人工筛选耗时长、效率低、药物筛选周期长等问题,提出一种基于2D模型的药物小分子筛选方法(SMS-2D)。利用计算机自动化筛选出与目标分子片段具有相似片段的药物小分子。实验结果表明:SMS-2D方法能高效地筛选出包含与分子片段具有相似片段的小分子。
Fragment-based drug design(FBDD)is one of the mainstream methods of drug development.How to efficiently screen drug small molecules with a similar molecular fragments from massive drug large data is a challenging problem.The current manual methods have the problems of time consuming,low efficiency,long drug screening period,etc.To solve these problems,a drug small molecule screening method based on 2D model(SMS-2D)is proposed.It can screen drug small molecules with similar fragments to target molecular fragments by computer automation.The experimental evaluation on different data sets shows that the SMS-2D algorithm can efficiently filter drug small molecules containing a similar molecular structure to the molecular fragment from drug small molecules large data sets.
作者
徐其凤
冯林
余游
罗桂林
Xu Qifeng;Feng Lin;Yu You;Luo Guilin(College of Computer Science,Sichuan Normal University,Chengdu 610101,Sichuan,China;State Key Laboratory of Biotherapy,Sichuan University,Chengdu 610041,Sichuan,China)
出处
《计算机应用与软件》
北大核心
2021年第4期58-63,100,共7页
Computer Applications and Software
基金
国家科技支撑计划项目(2014BAH11F01,2014BAH11F02)。
关键词
小分子筛选
药物研发
药物大数据
FBDD
SDF
Small molecules filter
Drug development
Drug large data
Fragment-based drug design(FBDD)
SDF
作者简介
徐其凤,硕士生,主研领域:深度学习发;冯林,博士;余游,硕士生;罗桂林,硕士生。
