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New molecular docking and sequence a...

Buzko, Oleksandr Viktorovich.

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New molecular docking and sequence analysis tools for protein kinase studies.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	New molecular docking and sequence analysis tools for protein kinase studies./
作者:	Buzko, Oleksandr Viktorovich.
面頁冊數:	251 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3834.
Contained By:	Dissertation Abstracts International64-08B.
標題:	Chemistry, Pharmaceutical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3101033

New molecular docking and sequence analysis tools for protein kinase studies.
Buzko, Oleksandr Viktorovich.

New molecular docking and sequence analysis tools for protein kinase studies. - 251 p.

Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3834.

Thesis (Ph.D.)--Princeton University, 2003.

Protein kinases comprise one of the largest families of enzymes involved in controlling signaling events in the cell. This pivotal role of protein kinases attracted significant attention due to a promise of new therapies based on signal and cell-cycle control. However, in order to map signaling interactions in the cell, composition and ordering of each pathway must be determined. This can be accomplished by labeling direct substrates of the kinase of interest or by specifically inhibiting it and observing the resulting phenotype. Our lab has developed a chemical genetic approach to address this challenge. It involves a mutation of the kinase of interest and a complementary structural change in a general inhibitor scaffold to produce a highly specific inhibitor. Complementary ATP analogs are created by introducing a bulky substituent into the parent ATP molecule.Subjects--Topical Terms:

550957
Chemistry, Pharmaceutical.

New molecular docking and sequence analysis tools for protein kinase studies.
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245 1 0 $a New molecular docking and sequence analysis tools for protein kinase studies.
300 $a 251 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-08, Section: B, page: 3834.
500 $a Adviser: Kevan M. Shokat.
502 $a Thesis (Ph.D.)--Princeton University, 2003.
520 $a Protein kinases comprise one of the largest families of enzymes involved in controlling signaling events in the cell. This pivotal role of protein kinases attracted significant attention due to a promise of new therapies based on signal and cell-cycle control. However, in order to map signaling interactions in the cell, composition and ordering of each pathway must be determined. This can be accomplished by labeling direct substrates of the kinase of interest or by specifically inhibiting it and observing the resulting phenotype. Our lab has developed a chemical genetic approach to address this challenge. It involves a mutation of the kinase of interest and a complementary structural change in a general inhibitor scaffold to produce a highly specific inhibitor. Complementary ATP analogs are created by introducing a bulky substituent into the parent ATP molecule.
520 $a In order to facilitate the development of specific inhibitors/ATP analogs, methods of computational modeling of ligand binding have been applied. Here I describe a number of improvements made to a molecular docking algorithm. Introduction of additional atom types along with explicit treatment of hydrogen bonding significantly increased accuracy of docking simulations. In addition, scoring grids were changed to include information about hydrophobicity of binding sites, thus, allowing for accurate docking of hydrophobic ligands.
520 $a The methodology of complementary fit has been successfully extended to a number of protein kinases. However, the crystal structures of the kinases of interest are frequently unavailable, which leaves sequence alignments as the only source of information. In order to provide reliable predictions of the mutation sites, only closely related sequences must be included in the alignments.
520 $a In order to provide a source of organized sequence information, we established the Kinase Sequence Database focused on the protein kinase superfamily. In order to group raw kinase sequences into families, I developed a recursive clustering algorithm, which combines fast BLAST scan with sensitivity of a hidden Markov model profile search. In addition to clustering, a master alignment of the entire database has been created. It allows user to arbitrarily define sets of sequences on and perform statistical analyses, such as assessment of sequence conservation, search for sequences matching a particular pattern or comparison of sets of sequences.
520 $a Analysis of the database content also led to discovery of a family of plant kinases, which featured an alanine at the site of sensitizing mutations where the vast majority of protein kinases had amino acids with large side chains. Study of their primary sequence led to a hypothesis regarding their possible function, as well as provided an additional confirmation of increased variability of this position.
520 $a Abundance of inhibition information from a number of projects has led us to a hypothesis that primary amino acid sequence could be linked to the binding preferences of the protein. In order to substantiate this hypothesis, I carried out calculations based on inhibition data for a large number of protein kinases and performed statistical analysis using software tools developed for this purpose. Here I present the results of this work, along with conclusions and recommendations for the future use of the proposed approach.
590 $a School code: 0181.
650 4 $a Chemistry, Pharmaceutical. $3 550957
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710 2 0 $a Princeton University. $3 645579
773 0 $t Dissertation Abstracts International $g 64-08B.
790 1 0 $a Shokat, Kevan M., $e advisor
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791 $a Ph.D.
792 $a 2003
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