Annual Reports in Computational Chemistry

Edited by

  • Ralph Wheeler, Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh, PA, USA
  • David Spellmeyer, Nodality, Inc., CA, USA

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.
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Researchers and students interested in computational chemistry


Book information

  • Published: November 2008
  • Imprint: ELSEVIER
  • ISBN: 978-0-444-53250-3

Table of Contents

Section 1: Bioinformatics (Section Editor: Wei Wang)1. Structural Perspectives on Protein EvolutionEric Franzosa and Yu Xia1. Introduction2. Determinants of Evolutionary Rate3. Theoretical Advances4. Empirical Results: Single Proteins5. Empirical Results: Higher Order Properties6. SummationAcknowledgementsReferences2. Predicting Selectivity and Druggability in Drug DiscoveryAlan C. Cheng1. Introduction2. Selectivity3. Druggability4. ConclusionReferencesSection 2: Biological Modeling (Section Editor: Nathan Barker)3. Machine Learning for Protein Structure and Function PredictionRobert Ezra Langlois and Hui Lu1. Introduction2. Machine Learning Problem Formulations3. Applications in Protein Structure and Function Modeling4. Discussion and Future OutlookAcknowledgementsReferences4. Modeling Protein-Protein and Protein-Nucleic Acid Interactions: Structure, Thermodynamics, and KineticsHuan-Xiang Zhou, Sanbo Qin and Harianto Tjong1. Introduction2. Building Structural Models3. Prediction of Binding Affinities4. Prediction of Binding Rates5. Dynamics within Native Complexes and During Complex Formation6. Summary PointsReferences5. Analysing Protein NMR pH-titration Curves Jens Erik Nielsen1. Introduction2. Fitting Protein Titration Curves3. Conclusion and OutlookReferences6. Implicit Solvent Simulations of Biomolecules in Cellular Environments Michael Feig, Seiichiro Tanizaki and Maryam Sayadi1. Introduction2. Theory3. Applications and Challenges4. Summary and OutlookAcknowledgementsReferencesSection 3: Simulation Methodologies (Section Editor: Carlos Simmerling)7. Implicit Solvent Models in Molecular Dynamics Simulations: A Brief OverviewAlexey Onufriev1. Introduction2. Implicit Solvent Framework3. Conclusions and OutlookAcknowledgmentsReferences8. Comparing MD Simulations and NMR Relaxation ParametersVance Wong and David A. Case1. Introduction2. Internal Motions and Flexibility3. Overall Tumbling and Rotational Diffusion4. ConclusionsAcknowledgementsReferences