Literature DB >> 15279552

Structural bioinformatics and its impact to biomedical science.

Kuo-Chen Chou1.   

Abstract

During the last two decades, the number of sequence-known proteins has increased rapidly. In contrast, the corresponding increment for structure-known proteins is much slower. The unbalanced situation has critically limited our ability to understand the molecular mechanism of proteins and conduct structure-based drug design by timely using the updated information of newly found sequences. Therefore, it is highly desired to develop an automated method for fast deriving the 3D (3-dimensional) structure of a protein from its sequence. Under such a circumstance, the structural bioinformatics was emerging naturally as the time required. In this review, three main strategies developed in structural bioinformatics, i.e., pure energetic approach, heuristic approach, and homology modeling approach, as well as their underlying principles, are briefly introduced. Meanwhile, a series of demonstrations are presented to show how the structural bioinformatics has been applied to timely derive the 3D structures of some functionally important proteins, helping to understand their action mechanisms and stimulating the course of drug discovery. Also, the limitation of these approaches and the future challenges of structural bioinformatics are briefly addressed.

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Year:  2004        PMID: 15279552     DOI: 10.2174/0929867043364667

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  94 in total

1.  Predicting Protein Model Quality from Sequence Alignments by Support Vector Machines.

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Journal:  J Proteomics Bioinform       Date:  2013-11-04

2.  Using fourier spectrum analysis and pseudo amino acid composition for prediction of membrane protein types.

Authors:  Hui Liu; Jie Yang; Meng Wang; Li Xue; Kuo-Chen Chou
Journal:  Protein J       Date:  2005-08       Impact factor: 2.371

3.  Determination of mutation patterns in human ornithine transcarbamylase precursor.

Authors:  Shaomin Yan; Guang Wu
Journal:  J Clin Monit Comput       Date:  2009-02-10       Impact factor: 2.502

4.  Isolation and characterization of a biosurfactant producing strain, Brevibacilis brevis HOB1.

Authors:  Namir I A Haddad; Ji Wang; Bozhong Mu
Journal:  J Ind Microbiol Biotechnol       Date:  2008-09-12       Impact factor: 3.346

5.  Connecting mutant phenylalanine hydroxylase with phenylketonuria.

Authors:  Shaomin Yan; Guang Wu
Journal:  J Clin Monit Comput       Date:  2008-09-05       Impact factor: 2.502

6.  Multi label learning for prediction of human protein subcellular localizations.

Authors:  Lin Zhu; Jie Yang; Hong-Bin Shen
Journal:  Protein J       Date:  2009-12       Impact factor: 2.371

7.  In vitro transcriptomic prediction of hepatotoxicity for early drug discovery.

Authors:  Feng Cheng; Dan Theodorescu; Ira G Schulman; Jae K Lee
Journal:  J Theor Biol       Date:  2011-08-27       Impact factor: 2.691

8.  Modelling the molecular mechanism of protein-protein interactions and their inhibition: CypD-p53 case study.

Authors:  S M Fayaz; G K Rajanikant
Journal:  Mol Divers       Date:  2015-07-14       Impact factor: 2.943

9.  Study of peptide fingerprints of parasite proteins and drug-DNA interactions with Markov-Mean-Energy invariants of biopolymer molecular-dynamic lattice networks.

Authors:  Lázaro Guillermo Pérez-Montoto; María Auxiliadora Dea-Ayuela; Francisco J Prado-Prado; Francisco Bolas-Fernández; Florencio M Ubeira; Humberto González-Díaz
Journal:  Polymer (Guildf)       Date:  2009-06-03       Impact factor: 4.430

10.  Protein domain boundary predictions: a structural biology perspective.

Authors:  Svetlana Kirillova; Suresh Kumar; Oliviero Carugo
Journal:  Open Biochem J       Date:  2009-01-21
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