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Computational solvent mapping of pro...

Silberstein, Michael.

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Computational solvent mapping of proteins for binding-site identification and characterization.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Computational solvent mapping of proteins for binding-site identification and characterization./
作者:	Silberstein, Michael.
面頁冊數:	223 p.
附註:	Adviser: Sandor Vajda.
Contained By:	Dissertation Abstracts International67-12B.
標題:	Biology, Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3246630

Computational solvent mapping of proteins for binding-site identification and characterization.
Silberstein, Michael.

Computational solvent mapping of proteins for binding-site identification and characterization. - 223 p.

Adviser: Sandor Vajda.

Thesis (Ph.D.)--Boston University, 2007.

Computational solvent mapping samples a protein surface for regions of favorable electrostatics, desolvation, and surface complementarity in order to predict, identify, and characterize protein binding sites. Using as probes small organic molecules containing a wide range of functional groups, mapping reveals regions on the protein surface where multiple probe types cluster that often correspond to ligand binding site(s). Additionally, the specific interactions made by the protein with the various probes resemble those occurring between the protein and its natural ligand(s).Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Computational solvent mapping of proteins for binding-site identification and characterization.
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100 1 $a Silberstein, Michael. $3 1270995
245 1 0 $a Computational solvent mapping of proteins for binding-site identification and characterization.
300 $a 223 p.
500 $a Adviser: Sandor Vajda.
500 $a Source: Dissertation Abstracts International, Volume: 67-12, Section: B, page: 6813.
502 $a Thesis (Ph.D.)--Boston University, 2007.
520 $a Computational solvent mapping samples a protein surface for regions of favorable electrostatics, desolvation, and surface complementarity in order to predict, identify, and characterize protein binding sites. Using as probes small organic molecules containing a wide range of functional groups, mapping reveals regions on the protein surface where multiple probe types cluster that often correspond to ligand binding site(s). Additionally, the specific interactions made by the protein with the various probes resemble those occurring between the protein and its natural ligand(s).
520 $a In this dissertation, I apply this methodology to a number of well-characterized proteins, including thermolysin, elastase, haloalkane dehalogenase, protein tyrosine phosphatase 1B, transaldolase, and other glycolytic and proteolytic enzymes in order to validate the method and to investigate numerous structural and biochemical questions pertaining to these proteins. The first part of this work assesses the computational mapping methodology with respect to its ability to correctly simulate the results of experimentally-derived solvent mapping studies and to identify and characterize protein binding sites in both ligand-bound and apostructures. The second part addresses mechanistic and structural questions using mapping to probe protein-ligand affinity and specificity, substrate-access and binding mechanisms, and allosteric interactions and conformational changes. The results demonstrate the versatility of this algorithm in locating and characterizing binding sites as well as investigating the various biochemical properties that underlie molecular recognition.
590 $a School code: 0017.
650 4 $a Biology, Bioinformatics. $3 1018415
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710 2 $a Boston University. $3 1017454
773 0 $t Dissertation Abstracts International $g 67-12B.
790 $a 0017
790 1 0 $a Vajda, Sandor, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3246630