Literature DB >> 7919786

Protein structure--based drug design.

P J Whittle1, T L Blundell.   

Abstract

Design cycles will undoubtedly play an increasingly important role in drug discovery in the coming years, as the amount of structural information on protein targets continues to rise. However, the traditional method of drug discovery, based upon random screening and systematic modification of leads by medicinal chemistry techniques, will probably not be abandoned completely because it has a potentially important advantage over more structure-based methods--namely, leads identified in this way are unlikely to show a close resemblance to the natural ligand or substrate. They may, therefore, have advantages in terms of patent novelty, selectivity, or pharmacokinetic profile. However, such leads could then serve as the basis for structure-based, rational modification programs, in which their interactions with target receptors are defined (as we have described) and improved molecules are designed. A final important point to be made about structure-based design in drug discovery is that, while it can be of great use in the initial process of identifying ligands with improved affinity and selectivity in vitro, it can usually say very little about other essential aspects of the drug discovery process, e.g. the need to achieve an adequate pharmacokinetic profile and low toxicity in vivo. This observation reminds us that drug design is a multidisciplinary process, involving molecular biologists, biochemists, pharmacologists, organic chemists, crystallographers, and others. In order to be effective, therefore, structure-based design must be properly integrated into the overall discovery effort.

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Year:  1994        PMID: 7919786     DOI: 10.1146/annurev.bb.23.060194.002025

Source DB:  PubMed          Journal:  Annu Rev Biophys Biomol Struct        ISSN: 1056-8700


  19 in total

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3.  Molecular basis for specificity in the druggable kinome: sequence-based analysis.

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4.  Toward Mycobacterium tuberculosis DXR inhibitor design: homology modeling and molecular dynamics simulations.

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Review 5.  Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery.

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-03-29       Impact factor: 6.237

Review 6.  Symmetry, stability, and dynamics of multidomain and multicomponent protein systems.

Authors:  T L Blundell; N Srinivasan
Journal:  Proc Natl Acad Sci U S A       Date:  1996-12-10       Impact factor: 11.205

7.  PRO_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology.

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8.  Quantum mechanical pairwise decomposition analysis of protein kinase B inhibitors: validating a new tool for guiding drug design.

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9.  Development of simple fitness landscapes for peptides by artificial neural filter systems.

Authors:  G Schneider; J Schuchhardt; P Wrede
Journal:  Biol Cybern       Date:  1995-08       Impact factor: 2.086

10.  Exploring CYP1A1 as anticancer target: homology modeling and in silico inhibitor design.

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