Xu / Liang | Computational Methods for Protein Structure Prediction and Modeling | E-Book | sack.de
E-Book

E-Book, Englisch, 322 Seiten, eBook

Reihe: Biological and Medical Physics, Biomedical Engineering

Xu / Liang Computational Methods for Protein Structure Prediction and Modeling

Volume 2: Structure Prediction
2007
ISBN: 978-0-387-68825-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

Volume 2: Structure Prediction

E-Book, Englisch, 322 Seiten, eBook

Reihe: Biological and Medical Physics, Biomedical Engineering

ISBN: 978-0-387-68825-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark



Volume Two of this two-volume sequence presents a comprehensive overview of protein structure prediction methods and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.

Dr. Ying Xu is Regents-GRA Eminent Scholar and Professor at the University of Georgia.  Dr. Dong Xu is the Director of the Digital Biology Laboratory at the University of Missouri-Columbia.  Dr. Jie Liang is the Director for the Center for Bioinformatics at the University of Illinois at Chicago.

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Protein Structure Prediction by Protein Threading.- De Novo Protein Structure Prediction.- Structure Prediction of Membrane Proteins.- Structure Prediction of Protein Complexes.- Structure-Based Drug Design.- Protein Structure Prediction as a Systems Problem.- Resources and Infrastructure for Structural Bioinformatics.


"16 Structure-BasedDrug Design (S. 135-136)

Kunbin Qu and NatasjaBrooijrnans

16.1 Introduction to Modern Drug Discovery

To cure or contain a disease is to selectively eliminate or restrain the disorder caused by the pathogen, the human body, or both, and at the same time to minimize damage to the healthy parts. The quest of drug discovery is to identify the causes of the phenotype of the disease, and to interfere with the abnormal gene or gene product in such a manner that the disease is cured. Selectivity for just the aberrant gene products remains the critical point throughout the modem drug discovery process. Since ancient times, people have been using medicinal products, obtained from plant, animal, and mineral sources, to treat diseases. Some ofthese treatments were effective, but many of them had strong side effects. Starting in the late nineteenth century, modern drug discovery has become an interdisciplinary effort between chemistry, pharmacology, and biology.

The phenomena ofdifferent binding affinities of dyes for biological tissues observed by Paul Ehrlich led to the hypothesis of the "chemoreceptor," which would exist distinctively in different organisms and disease tissues. Ehrlich then hypothesized that therapeutic effects can be achieved based on their differences (Drews, 2000). Shortly after Ehrlichs stipulation, the enzyme activity theory from Emil Fischer led to the "lock-and-key" concept, which provided an opening for structure-based drug design (SBDD): the key can be specifically designed when the lock, i.e., the target structure, is known (Fischer, 1894). In the 1950s this was modified by Koshland to the "induced fit" theory, where the lock and the key have to undergo conformational changes to fit optimally (Koshland, 1958).

Generally the best-fitting conformers are not the lowest-energy conformers (Foote and Milstein, 1994). Wecan divide drugs into two major therapeutic categories: chemotherapeutics, historically the bread-and-butter of pharmaceutical companies, and protein therapeutics, an avenue originally taken by the biotechnology industry. More recently, other methods have emerged as promising avenues to disrupt a particular disease process. Gene therapy aims to correct the disease process by restoring, modifying, or enhancing cellular functions through the introduction ofa functional gene into a target cell (Anderson, 1992).

Small-interfering RNAs (siRNAs) are incorporated into an RNA-induced silencing complex that targets and cleaves mRNA complementary to the siRNAs, and thus leads to the knockdown of the targeted mRNA (Fire et aI., 1998). Recent rapid progress in RNA synthesis and structure determination also made RNA itself an attractive target since RNA is involved in all stages of cell life, due to its key sequence motifs and also its intricate three-dimensional folds (Hermann and Westhof, 1998). Nevertheless, protein therapeutics and chemotherapeutics remain the dominant methods in current pharmaceutical research and development, due to their relatively high success rate, the abundant scientific knowledge, and the well-established acceptance ofproteins and small molecules as drugs. In this chapter, we will focus on how SBDD facilitates the discovery and development of protein therapeutics and small chemical therapeutics, by optimizing the key for the lock."


Dr. Ying Xu is Regents-GRA Eminent Scholar and Professor at the University of Georgia. Dr. Dong Xu is the Director of the Digital Biology Laboratory at the University of Missouri-Columbia. Dr. Jie Liang is the Director for the Center for Bioinformatics at the University of Illinois at Chicago.



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