東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Protein three-dimensional structure:...

Pappas, Georgios Joannis, Jr.

Linked to FindBook

Google Book

Amazon

博客來

Protein three-dimensional structure: Theoretical and computational aspects of structure prediction based on the amino acid sequence.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Protein three-dimensional structure: Theoretical and computational aspects of structure prediction based on the amino acid sequence./
Author:	Pappas, Georgios Joannis, Jr.
Description:	199 p.
Notes:	Source: Dissertation Abstracts International, Volume: 60-09, Section: B, page: 4466.
Contained By:	Dissertation Abstracts International60-09B.
Subject:	Biophysics, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=9944960
ISBN:	0599468327

Protein three-dimensional structure: Theoretical and computational aspects of structure prediction based on the amino acid sequence.
Pappas, Georgios Joannis, Jr.

Protein three-dimensional structure: Theoretical and computational aspects of structure prediction based on the amino acid sequence. - 199 p.

Source: Dissertation Abstracts International, Volume: 60-09, Section: B, page: 4466.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.

Ever since the pioneering experiments of Anfinsen demonstrating experimentally that protein sequence is a necessary and sufficient determinant of its three dimensional structure, there have been innumerable efforts at predicting the three dimensional structure from sequence. Almost all of these approaches hinge on learning rules and paradigms from known three-dimensional structures. It is popularly believed that the solution lies in deciphering the rules for secondary structure. We examine this hypothesis by systematically testing 16 secondary structure prediction methods that span all of the existing methodology. We demonstrate that the prediction is far less accurate than reported originally and the accuracy levels are too small to be of value for precise predictions. Given the large repository of protein sequences, we posed the question if rules for secondary structure are better described by multiple sequence alignments. Indeed the predictions improve, but not adequately for implementation in structure predictions.

ISBN: 0599468327Subjects--Topical Terms:

1019105
Biophysics, General.

Protein three-dimensional structure: Theoretical and computational aspects of structure prediction based on the amino acid sequence.
LDR:03052nmm 2200277 4500 001 1856408
005 20040701122242.5
008 130614s1999 eng d
020 $a 0599468327
035 $a (UnM)AAI9944960
035 $a AAI9944960
040 $a UnM $c UnM
100 1 $a Pappas, Georgios Joannis, Jr. $3 1944188
245 1 0 $a Protein three-dimensional structure: Theoretical and computational aspects of structure prediction based on the amino acid sequence.
300 $a 199 p.
500 $a Source: Dissertation Abstracts International, Volume: 60-09, Section: B, page: 4466.
500 $a Adviser: Shankar Subramaniam.
502 $a Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.
520 $a Ever since the pioneering experiments of Anfinsen demonstrating experimentally that protein sequence is a necessary and sufficient determinant of its three dimensional structure, there have been innumerable efforts at predicting the three dimensional structure from sequence. Almost all of these approaches hinge on learning rules and paradigms from known three-dimensional structures. It is popularly believed that the solution lies in deciphering the rules for secondary structure. We examine this hypothesis by systematically testing 16 secondary structure prediction methods that span all of the existing methodology. We demonstrate that the prediction is far less accurate than reported originally and the accuracy levels are too small to be of value for precise predictions. Given the large repository of protein sequences, we posed the question if rules for secondary structure are better described by multiple sequence alignments. Indeed the predictions improve, but not adequately for implementation in structure predictions.
520 $a Given that the repertoire of secondary structure classifications is limited, we asked if there is a limited set, even if large, of structural features that describe the protein three-dimensional structure adequately. Towards this end, we created libraries of peptide fragments of sizes 7 to 13 respectively and clustered them based on structural similarity. Analysis of these clustered fragments show that these adequately describe the protein structure space. In order to use this paradigm for ab initio structure prediction, we examined sequence-structure relationships in these clusters. It turns out that while structural characterization is nearly complete, the mapping from sequence to structure is not unique and no significant correlations exist between the sequences in a given structural cluster. Examination of numerous protein structures using sequence-structure correlations show that there are regions in proteins which show a degree of correlation. These are perhaps the folding motifs in proteins and this warrants further examination.
590 $a School code: 0090.
650 4 $a Biophysics, General. $3 1019105
690 $a 0786
710 2 0 $a University of Illinois at Urbana-Champaign. $3 626646
773 0 $t Dissertation Abstracts International $g 60-09B.
790 1 0 $a Subramaniam, Shankar, $e advisor
790 $a 0090
791 $a Ph.D.
792 $a 1999
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoeng/servlet/advanced?query=9944960