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Development and application of ligan...

Khashan, Raed Saeed.

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Development and application of ligand-based and structure-based computational drug discovery tools based on frequent subgraph mining of chemical structures.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Development and application of ligand-based and structure-based computational drug discovery tools based on frequent subgraph mining of chemical structures./
作者:	Khashan, Raed Saeed.
面頁冊數:	148 p.
附註:	Adviser: Alexander Tropsha.
Contained By:	Dissertation Abstracts International68-06B.
標題:	Biology, Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3272685
ISBN:	9780549123736

Development and application of ligand-based and structure-based computational drug discovery tools based on frequent subgraph mining of chemical structures.
Khashan, Raed Saeed.

Development and application of ligand-based and structure-based computational drug discovery tools based on frequent subgraph mining of chemical structures. - 148 p.

Adviser: Alexander Tropsha.

Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2007.

Recent development in subgraph mining tools resulted in faster and more efficient algorithms that facilitate exploring the information encoded in data that can be represented by graphs. In this dissertation, we apply the graph mining technique to design ligand-based and structure-based computational drug discovery tools. For ligand-based drug design, molecules in a dataset will be represented by graphs, and subgraph mining tools will be used to find the frequent subgraphs (chemical fragments) that occur in at least a certain percentage of the ligands in the dataset. These chemical fragments will be used as molecular descriptors for the quantitative structure-activity relationship (QSAR) studies. They will also be used for identifying the pharmacophores responsible for the activity as well as the toxicophores responsible for the toxicity of a datasets of molecules. For the structure-based drug design, interacting atoms at the interface of a set of protein-ligand complexes will be represented by graphs. Frequent subgraphs identified will define the patterns of chemical interactions at the interface, which will be used to pose-score docked complexes to identify the correct docking pose.

ISBN: 9780549123736Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Development and application of ligand-based and structure-based computational drug discovery tools based on frequent subgraph mining of chemical structures.
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