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Annual Reports in Computational Chemistry, Vol 4

  • ID: 1757013
  • Book
  • December 2008
  • 272 Pages
  • Elsevier Science and Technology
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Annual Reports in Computational Chemistry is a new periodical providing timely and critical reviews of important topics in computational chemistry as applied to all chemical disciplines. Topics covered include quantum chemistry, molecular mechanics, force fields, chemical education, and applications in academic and industrial settings. Each volume is organized into (thematic) sections with contributions written by experts. Focusing on the most recent literature and advances in the field, each article covers a specific topic of importance to computational chemists. Annual Reports in Computational Chemistry is a "must" for researchers and students wishing to stay up-to-date on current developments in computational chemistry.

* Broad coverage of computational chemistry and up-to-date information
* Topics covered include bioinformatics, drug discovery, protein NMR, simulation methodologies, and applications in academic and industrial settings
* Each chapter reviews the most recent literature on a specific topic of interest to computational chemists

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Section 1: Bioinformatics (Section Editor: Wei Wang)
1. Structural Perspectives on Protein Evolution
Eric Franzosa and Yu Xia
2. Predicting Selectivity and Druggability in Drug Discovery
Alan C. Cheng

Section 2: Biological Modeling (Section Editor: Nathan Barker)
3. Machine Learning for Protein Structure and Function Prediction
Robert Ezra Langlois and Hui Lu
4. Modeling Protein-Protein and Protein-Nucleic Acid Interactions: Structure, Thermodynamics, and Kinetics
Huan-Xiang Zhou, Sanbo Qin and Harianto Tjong
5. Analysing Protein NMR pH-titration Curves
Jens Erik Nielsen
6. Implicit Solvent Simulations of Biomolecules in Cellular Environments
Michael Feig, Seiichiro Tanizaki, and Maryam Sayadi

Section 3: Simulation Methodologies (Section Editor: Carlos Simmerling)
7. Implicit Solvent Models in Molecular Dynamics Simulations: A Brief Overview
Alexey Onufriev
8. Comparing MD Simulations and NMR Relaxation Parameters
Vance Wong and David A. Case
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Wheeler, Ralph A.
Spellmeyer, David
David Spellmeyer, PhD is an Advisor to startup and early venture companies providing technical and scientific guidance on overcoming technological, scientific and business development challenges. He brings broad business and technical expertise from companies both large (IBM, DuPont) and small (Chiron, CombiChem, Signature BioScience, Nodality). David has been involved in the development of advanced functional assays such as Nodality's Single Cell Network Profiling (SCNP) and Signature's label-free molecular and cellular screening systems. He has extensive experience in the management and analysis of high dimensional data (combinatorial chemistry and SCNP). He has worked closely with business development teams in establishing over 20 non-dilutive strategic corporate partnerships, 4 mergers and acquisitions, several rounds of venture financing, and two joint ventures. David received his Ph.D. in theoretical organic chemistry from UCLA. He completed his post-doctoral training in pharmaceutical chemistry at UCSF, where he remains an active Adjunct Associate Professor.
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