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Pharmacophore fingerprint analysis o...

Yang, Zheng.

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Pharmacophore fingerprint analysis of small molecules and proteins for virtual high throughput screening.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pharmacophore fingerprint analysis of small molecules and proteins for virtual high throughput screening./
Author:	Yang, Zheng.
Description:	277 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3292.
Contained By:	Dissertation Abstracts International64-07B.
Subject:	Chemistry, Pharmaceutical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3098771

Pharmacophore fingerprint analysis of small molecules and proteins for virtual high throughput screening.
Yang, Zheng.

Pharmacophore fingerprint analysis of small molecules and proteins for virtual high throughput screening. - 277 p.

Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3292.

Thesis (Ph.D.)--University of California, Santa Cruz, 2003.

We explored the application of 3-point pharmacophore fingerprints for characterizing small molecules and proteins for protein-based virtual high-throughput screening. Virtual high-throughput screening is a new approach attracting increasing levels of interest in pharmaceutical industry as a productive and cost-effective technology in the search for novel lead molecules.Subjects--Topical Terms:

550957
Chemistry, Pharmaceutical.

Pharmacophore fingerprint analysis of small molecules and proteins for virtual high throughput screening.
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035 $a (UnM)AAI3098771
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100 1 $a Yang, Zheng. $3 1531263
245 1 0 $a Pharmacophore fingerprint analysis of small molecules and proteins for virtual high throughput screening.
300 $a 277 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3292.
500 $a Chair: Ilan Benjamin.
502 $a Thesis (Ph.D.)--University of California, Santa Cruz, 2003.
520 $a We explored the application of 3-point pharmacophore fingerprints for characterizing small molecules and proteins for protein-based virtual high-throughput screening. Virtual high-throughput screening is a new approach attracting increasing levels of interest in pharmaceutical industry as a productive and cost-effective technology in the search for novel lead molecules.
520 $a We characterized the chemical and spatial properties of small molecules and proteins by the flexible small molecule fingerprints and active site sitepoint fingerprints, respectively. We developed the conformation generator CONGEN/MACROMODEL for fast and automatic conformational search for the flexible small molecule fingerprint generation. For proteins, Matt Evans developed the active site sitepoint fingerprints to represent active sites in "ligand space."
520 $a Using the MySQL database management system, we built a drug-targeted protein and ligand database based on the 3D structures from the Protein Data Bank, and the MDDR drug molecule database from the MDL Drug Data Report. The database is used to build virtual screening models for all activity classes, and also for cluster analysis of proteins and small molecules.
520 $a We found our 3D fingerprints are useful in clustering small molecules and proteins into biological classes using agglomerative hierarchical clustering methods. In terms of adjusted Rand index, the average linkage, complete linkage, and Ward's methods are better than single linkage and centroid methods. Detailed inspection of results show that the cluster analysis based on our fingerprints is an effective way to partition small molecules and proteins into activity classes.
520 $a In the virtual screening study, we compared protein class sitepoint fingerprints generated from the proteins in the database against flexible small molecule fingerprints in the MDDR database. The protein class consensus sitepoint fingerprints and consensus sitepoint-small molecule fingerprints are much better than random selection, and the enrichment rates are higher than those from protein class individual, intersection, and union sitepoint fingerprints.
590 $a School code: 0036.
650 4 $a Chemistry, Pharmaceutical. $3 550957
650 4 $a Chemistry, Organic. $3 516206
650 4 $a Computer Science. $3 626642
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710 2 0 $a University of California, Santa Cruz. $3 1018764
773 0 $t Dissertation Abstracts International $g 64-07B.
790 1 0 $a Benjamin, Ilan, $e advisor
790 $a 0036
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3098771