Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints
作者: Jie LiuMinyi SuZhihai LiuJie LiYan LiRenxiao Wang
作者单位: 1State Key Laboratory of Bioorganic and Natural Products Chemistry, Collaborative Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences
2State Key Laborator
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Nature Journal
DOI: 10.1186/s12859-017-1750-5
关键词: Protein-ligand binding affinityScoring functionInteraction fingerprintsStructure-based drug design
原始语种摘要: In structure-based drug design, binding affinity prediction remains as a challenging goal for current scoring functions. Development of target-biased scoring functions provides a new possibility for tackling this problem, but this approach is also associated with certain technical difficulties. We previously reported the Knowledge-Guided Scoring (KGS) method as an alternative approach ( BMC Bioinformatics , 2010, 11, 193–208). The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding data of an appropriate reference complex, so the error in binding affinity prediction can be reduced effectively.
全文获取路径: Springer Nature  (合作)
影响因子:3.024 (2012)

  • affinity 亲和力
  • protein 蛋白质
  • ligand 配合体
  • scoring 擦伤
  • binding 装订
  • remains 残渣
  • effectively 有效地
  • current 
  • complex 超群
  • prediction 预报