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A Graphical Workflow Modeler for Docking Process in Drug Discovery

A Graphical Workflow Modeler for Docking Process in Drug Discovery

Qiang Wang, Yunming Ye, Kunqian Yu, Joshua Zhexue Huang
Copyright: © 2009 |Pages: 15
ISBN13: 9781605663746|ISBN10: 1605663743|EISBN13: 9781605663753
DOI: 10.4018/978-1-60566-374-6.ch015
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MLA

Wang, Qiang, et al. "A Graphical Workflow Modeler for Docking Process in Drug Discovery." Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare, edited by Mario Cannataro, IGI Global, 2009, pp. 292-306. https://doi.org/10.4018/978-1-60566-374-6.ch015

APA

Wang, Q., Ye, Y., Yu, K., & Huang, J. Z. (2009). A Graphical Workflow Modeler for Docking Process in Drug Discovery. In M. Cannataro (Ed.), Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare (pp. 292-306). IGI Global. https://doi.org/10.4018/978-1-60566-374-6.ch015

Chicago

Wang, Qiang, et al. "A Graphical Workflow Modeler for Docking Process in Drug Discovery." In Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare, edited by Mario Cannataro, 292-306. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-374-6.ch015

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Abstract

A drug discovery process is aimed to find from a large set of molecules the candidate leads that have strong interaction with the target proteins. The process of drug discovery is characterized by its complexity in data and computation. A useful tool to simplify the handling of intensive data and complex algorithms is necessary for domain scientists to build proper drug discovery procedures, carry through the data intensive computation tasks and produce fruitful results. This chapter presents a graphical workflow modeler for domain scientists to perform drug discovery tasks on high performance grid computing grid platforms. A client/server system is described as the platform for implementation of the graphical workflow modeler. A case study on drug discovery for avian influenza virus is given to demonstrate the use of this tool in drug discovery research.

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