New PDF release: Annual Reports in Computational Chemistry, Vol. 4

By Ralph A. Wheeler, David C. Spellmeyer

ISBN-10: 0444532501

ISBN-13: 9780444532503

Annual experiences in Computational Chemistry is a brand new periodical delivering well timed and significant experiences of significant themes in computational chemistry as utilized to all chemical disciplines. subject matters coated comprise quantum chemistry, molecular mechanics, strength fields, chemical schooling, and purposes in educational and business settings. each one quantity is geared up into (thematic) sections with contributions written by means of specialists. concentrating on the latest literature and advances within the box, each one article covers a selected subject of value to computational chemists. Annual experiences in Computational Chemistry is a "must" for researchers and scholars wishing to stick updated on present advancements in computational chemistry.

* wide assurance of computational chemistry and up to date info
* subject matters lined comprise bioinformatics, drug discovery, protein NMR, simulation methodologies, and purposes in educational and business settings
* each one bankruptcy reports the newest literature on a selected subject of curiosity to computational chemists

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Extra resources for Annual Reports in Computational Chemistry, Vol. 4

Sample text

2006, 46, 1124–33. 23. , Boyer, S. Ligand-based approach to in silico pharmacology: Nuclear receptor profiling. J. Chem. Inf. Model. 2006, 46, 2725–36. 24. A. Enzyme classification by ligand binding. Proteins 2004, 57, 711–24. 25. R. NCBI Reference Sequence (RefSeq): A curated nonredundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2007, 35, D61–5. 26. M. CLUSTAL: A package for performing multiple sequence alignment on a microcomputer. Gene 1988, 73, 237–44. Predicting Selectivity and Druggability in Drug Discovery 35 27.

Proportion of solvent-exposed amino acids in a protein and rate of protein evolution. Mol. Biol. Evol. 2007, 24(4), 1005–11. 52. , Chothia, C. The selection of acceptable protein mutations. Proc. Natl. Acad. Sci. USA 2007, 104(24), 10080–5. 53. T. Systematically assessing the influence of 3-dimensional structural context on the molecular evolution of mammalian proteomes. Mol. Biol. Evol. 2006, 23(11), 2131–3. 54. Zuckerkandl, E. Evolutionary processes and evolutionary noise at the molecular level.

Target assessment for antiparasitic drug discovery. Trends Parasitol. 2007, 23, 589–95. 4. , Williams-Jones, B. High-throughput electronic biology: Mining information for drug discovery. Nature Rev. Drug. Discov. 2007, 6, 220–30. 5. , Ullrich, A. Strategies to overcome resistance to targeted protein kinase inhibitors. Nature Rev. Drug Disc. 2004, 3, 1001–10. 6. M. Features of selective kinase inhibitors. Chem. Biol. 2005, 12, 621–37. 7. H. Rapid computational identification of the targets of protein kinase inhibitors.

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Annual Reports in Computational Chemistry, Vol. 4 by Ralph A. Wheeler, David C. Spellmeyer


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