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.

Key Features

* 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


Researchers and students interested in computational chemistry

Table of Contents

Section 1: Bioinformatics (Section Editor: Wei Wang) 1. Structural Perspectives on Protein Evolution Eric Franzosa and Yu Xia 1. Introduction 2. Determinants of Evolutionary Rate 3. Theoretical Advances 4. Empirical Results: Single Proteins 5. Empirical Results: Higher Order Properties 6. Summation Acknowledgements References 2. Predicting Selectivity and Druggability in Drug Discovery Alan C. Cheng 1. Introduction 2. Selectivity 3. Druggability 4. Conclusion References Section 2: Biological Modeling (Section Editor: Nathan Barker) 3. Machine Learning for Protein Structure and Function Prediction Robert Ezra Langlois and Hui Lu 1. Introduction 2. Machine Learning Problem Formulations 3. Applications in Protein Structure and Function Modeling 4. Discussion and Future Outlook Acknowledgements References 4. Modeling Protein-Protein and Protein-Nucleic Acid Interactions: Structure, Thermodynamics, and Kinetics Huan-Xiang Zhou, Sanbo Qin and Harianto Tjong 1. Introduction 2. Building Structural Models 3. Prediction of Binding Affinities 4. Prediction of Binding Rates 5. Dynamics within Native Complexes and During Complex Formation 6. Summary Points References 5. Analysing Protein NMR pH-titration Curves Jens Erik Nielsen 1. Introduction 2. Fitting Protein Titration Curves 3. Conc


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© 2008
Elsevier Science
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About the editors

Ralph Wheeler

Affiliations and Expertise

Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh, PA, USA

David Spellmeyer

Affiliations and Expertise

Nodality, Inc., CA, USA