Ligand- and Structure-Based Drug Design and Optimization using KNIME

被引:13
|
作者
Mazanetz, Michael P. [1 ,2 ]
Goode, Charlotte H. F. [2 ]
Chudyk, Ewa, I [3 ]
机构
[1] NovaData Solut Ltd, POB 639, Abingdon On Thames OX14 9JD, Oxon, England
[2] Univ Aberdeen, Dept Chem, Meston Bldg, Aberdeen AB24 3UE, Scotland
[3] Vertex Pharmaceut Europe Ltd, Modeling & Informat, 86-88 Jubilee Ave,Milton Pk, Abingdon On Thames, England
关键词
Hit expansion; virtual screening; predictive toxicology; ligand optimisation; data mining; KNIME; ADME modelling; big data; workflows; computer-aided drug design; WEB SERVICE INFRASTRUCTURE; DEVELOPMENT KIT CDK; SOURCE [!text type='JAVA']JAVA[!/text] LIBRARY; APPROVED DRUGS; HOMOLOGY MODEL; DATABASE; IDENTIFICATION; CHEMISTRY; INFORMATION; FRAGMENT;
D O I
10.2174/0929867326666190409141016
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In recent years there has been a paradigm shift in how data is being used to progress early drug discovery campaigns from hit identification to candidate selection. Significant developments in data mining methods and the accessibility of tools for research scientists have been instrumental in reducing drug discovery timelines and in increasing the likelihood of a chemical entity achieving drug development milestones. KNIME, the Konstanz Information Miner, is a leading open source data analytics platform and has supported drug discovery endeavours for over a decade. KNIME pro-vides a rich palette of tools supported by an extensive community of contributors to enable ligand and structure-based drug design. This review will examine recent developments within the KNIME platform to support small-molecule drug design and provide a perspective on the challenges and future developments within this field.
引用
收藏
页码:6458 / 6479
页数:22
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