東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Computational de novo protein design...

Princeton University.

FindBook

Google Book

Amazon

博客來

Computational de novo protein design with flexible templates .

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational de novo protein design with flexible templates ./
作者:	Fung, Ho Ki.
面頁冊數:	264 p.
附註:	Adviser: Christodoulos A. Floudas.
Contained By:	Dissertation Abstracts International69-12B.
標題:	Biology, Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3338679
ISBN:	9780549933953

Computational de novo protein design with flexible templates .
Fung, Ho Ki.

Computational de novo protein design with flexible templates . - 264 p.

Adviser: Christodoulos A. Floudas.

Thesis (Ph.D.)--Princeton University, 2008.

The thesis also outlines an independent chapter which presents a novel mixed integer nonlinear programming model on designing a biosensor of receptors for optimally recognizing a known set of ligands.

ISBN: 9780549933953Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Computational de novo protein design with flexible templates .
LDR:03955nmm 2200325 a 45 001 875441
005 20100826
008 100826s2008 ||||||||||||||||| ||eng d
020 $a 9780549933953
035 $a (UMI)AAI3338679
035 $a AAI3338679
040 $a UMI $c UMI
100 1 $a Fung, Ho Ki. $3 1044705
245 1 0 $a Computational de novo protein design with flexible templates .
300 $a 264 p.
500 $a Adviser: Christodoulos A. Floudas.
500 $a Source: Dissertation Abstracts International, Volume: 69-12, Section: B, page: 7659.
502 $a Thesis (Ph.D.)--Princeton University, 2008.
520 $a The thesis also outlines an independent chapter which presents a novel mixed integer nonlinear programming model on designing a biosensor of receptors for optimally recognizing a known set of ligands.
520 $a De novo peptide or protein design starts with a flexible three-dimensional protein backbone template and involves the search for all amino acid sequences that will fold into such a template. The sequences will vary in their abilities to perform the same function as that of the mother sequence. In the usual case, we are interested in the sequences that have higher activities than the native protein. The problem is of paramount importance to protein engineering and peptide and protein drug discovery.
520 $a The de novo design problem can be posed as two questions: (i) "How should a flexible design backbone template be defined?"; and (ii) "How can the sequence search on such a flexible design template be performed efficiently to design proteins of practical sizes?". To answer the first question, all current approaches for constructing a flexible design template are studied. It is concluded that the best method is through a continuum backbone and continuous ranges of dihedral angles. In such a truly flexible design template, all inter-atomic distances and bond angles are semi-infinite sets bounded between upper and lower bounds.
520 $a Regarding the second question, work is done based on improving the original de novo design framework proposed by Klepeis et al. (2003)(Klepeis et al., 2004). This framework designs proteins through two stages: (i) a sequence selection stage which predicts low energy sequences compatible with the target fold using a novel mixed-integer programming model; and (ii) a fold validation stage which calculates the probability of each sequence from the previous stage to fold into the flexible design template, using a global optimization approach under a full-atomistic force field. Computational efficiency of the framework is improved by formulating a different optimization model for the sequence selection stage, and performing an approximate method for fold validation via a protocol for NMR structure refinement instead of the rigorous but computationally expensive global optimzation approach. To incorporate backbone flexibility more explicitly into sequence selection, two new integer programming models are also developed to handle flexible design templates with multiple structures.
520 $a The new framework is applied to five de novo designs: (i) de novo design of compstatin variants; (ii) full-sequence design of human beta-defensin-2; (iii) design of inhibitors to HIV-1 gp 41 and gp 120; (iv) redesign of the carboxy-terminus of complement 3a; and (v) design of antagonists to complement 5a receptor. These examples demonstrate how the issues of defining a flexible design template, deriving a mutation set, imposing useful constraints to improve the quality of the solutions, and performing analysis of the predicted sequences can be solved when using the framework.
590 $a School code: 0181.
650 4 $a Biology, Bioinformatics. $3 1018415
650 4 $a Engineering, Chemical. $3 1018531
690 $a 0542
690 $a 0715
710 2 $a Princeton University. $3 645579
773 0 $t Dissertation Abstracts International $g 69-12B.
790 $a 0181
790 1 0 $a Floudas, Christodoulos A., $e advisor
791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3338679