This is a brief review of the computational modeling of protein-ligand interactions using a recently developed fully polarizable continuum model(FPCM)and rational drug design.Computational modeling has become a powerf...This is a brief review of the computational modeling of protein-ligand interactions using a recently developed fully polarizable continuum model(FPCM)and rational drug design.Computational modeling has become a powerful tool in understanding detailed protein-ligand interactions at molecular level and in rational drug design.To study the binding of a protein with multiple molecular species of a ligand,one must accurately determine both the relative free energies of all of the molecular species in solution and the corresponding microscopic binding free energies for all of the molecular species binding with the protein.In this paper,we aim to provide a brief overview of the recent development in computational modeling of the solvent effects on the detailed protein-ligand interactions involving multiple molecular species of a ligand related to rational drug design.In particular,we first briefly discuss the main challenges in computational modeling of the detailed protein-ligand interactions involving the multiple molecular species and then focus on the FPCM model and its applications.The FPCM method allows accurate determination of the solvent effects in the first-principles quantum mechanism(QM)calculations on molecules in solution.The combined use of the FPCM-based QM calculations and other computational modeling and simulations enables us to accurately account for a protein binding with multiple molecular species of a ligand in solution.Based on the computational modeling of the detailed protein-ligand interactions,possible new drugs may be designed rationally as either small-molecule ligands of the protein or engineered proteins that bind/metabolize the ligand.The computational drug design has successfully led to discovery and development of promising drugs.展开更多
目的:设计质子泵抑制剂(PPI)医嘱点评软件,促进临床合理用药。方法:根据某"三甲"医院(以下简称"样本医院")住院患者PP(I以PPI注射剂为例)使用情况设计医嘱点评软件的点评流程,在此基础上,与计算机工程师协作开发住...目的:设计质子泵抑制剂(PPI)医嘱点评软件,促进临床合理用药。方法:根据某"三甲"医院(以下简称"样本医院")住院患者PP(I以PPI注射剂为例)使用情况设计医嘱点评软件的点评流程,在此基础上,与计算机工程师协作开发住院患者PPI医嘱点评软件;以不合理用药检出率及人均耗时为指标,对比软件点评和人工点评的效果,并利用软件事前点评样本医院2018年2月静脉用药调配中心PPI注射剂摆药医嘱及回顾性点评2015年1月-2017年12月期间住院患者PPI注射剂不合理用药情况(均包括不合理的治疗用药、预防用药及无指征用药)。结果:设计的PPI医嘱点评软件包括用户和任务(定时点评)、系统设置、确认审核(对软件自动点评的结果进行复核)、报告导出4个模块。与人工点评相比,软件点评的不合理用药检出率(69.50%vs. 77.00%)无显著差异(P>0.05),人均耗时(9.25 min vs. 1.50 min)显著缩短(P<0.05);在事前点评应用中,不合理治疗用药27条(2.23%)、不合理预防用药318条(26.24%)、无指征用药602条(49.67%);在回顾性点评应用中,不合理治疗用药4 884条(2.68%)、不合理预防用药50 399条(27.67%)、无指征用药85 106条(46.72%)。结论:PPI医嘱点评软件的应用缩短了药师点评时间,提高了点评效率,促进了PPI临床合理用药。展开更多
基金supported by the National Science Foundation(grant CHE-1111761)the National Institutes of Health(grants R01 DA032910,R01 DA013930,R01 DA025100,R01 DA021416,and RC1 MH088480)+1 种基金Alzheimer’s Drug Discovery Foundation(ADDA)Institute for the Study of Aging(ISOA).
文摘This is a brief review of the computational modeling of protein-ligand interactions using a recently developed fully polarizable continuum model(FPCM)and rational drug design.Computational modeling has become a powerful tool in understanding detailed protein-ligand interactions at molecular level and in rational drug design.To study the binding of a protein with multiple molecular species of a ligand,one must accurately determine both the relative free energies of all of the molecular species in solution and the corresponding microscopic binding free energies for all of the molecular species binding with the protein.In this paper,we aim to provide a brief overview of the recent development in computational modeling of the solvent effects on the detailed protein-ligand interactions involving multiple molecular species of a ligand related to rational drug design.In particular,we first briefly discuss the main challenges in computational modeling of the detailed protein-ligand interactions involving the multiple molecular species and then focus on the FPCM model and its applications.The FPCM method allows accurate determination of the solvent effects in the first-principles quantum mechanism(QM)calculations on molecules in solution.The combined use of the FPCM-based QM calculations and other computational modeling and simulations enables us to accurately account for a protein binding with multiple molecular species of a ligand in solution.Based on the computational modeling of the detailed protein-ligand interactions,possible new drugs may be designed rationally as either small-molecule ligands of the protein or engineered proteins that bind/metabolize the ligand.The computational drug design has successfully led to discovery and development of promising drugs.
文摘目的:设计质子泵抑制剂(PPI)医嘱点评软件,促进临床合理用药。方法:根据某"三甲"医院(以下简称"样本医院")住院患者PP(I以PPI注射剂为例)使用情况设计医嘱点评软件的点评流程,在此基础上,与计算机工程师协作开发住院患者PPI医嘱点评软件;以不合理用药检出率及人均耗时为指标,对比软件点评和人工点评的效果,并利用软件事前点评样本医院2018年2月静脉用药调配中心PPI注射剂摆药医嘱及回顾性点评2015年1月-2017年12月期间住院患者PPI注射剂不合理用药情况(均包括不合理的治疗用药、预防用药及无指征用药)。结果:设计的PPI医嘱点评软件包括用户和任务(定时点评)、系统设置、确认审核(对软件自动点评的结果进行复核)、报告导出4个模块。与人工点评相比,软件点评的不合理用药检出率(69.50%vs. 77.00%)无显著差异(P>0.05),人均耗时(9.25 min vs. 1.50 min)显著缩短(P<0.05);在事前点评应用中,不合理治疗用药27条(2.23%)、不合理预防用药318条(26.24%)、无指征用药602条(49.67%);在回顾性点评应用中,不合理治疗用药4 884条(2.68%)、不合理预防用药50 399条(27.67%)、无指征用药85 106条(46.72%)。结论:PPI医嘱点评软件的应用缩短了药师点评时间,提高了点评效率,促进了PPI临床合理用药。
