Annual Reports in Computational Chemistry

Annual Reports in Computational Chemistry

1st Edition - October 10, 2006

Write a review

  • Editor: David Spellmeyer
  • eBook ISBN: 9780080465425

Purchase options

Purchase options
DRM-free (PDF)
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order


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
* The topics covered include quantum chemistry, molecular mechanics, force fields, chemical education, and applications in academic and industrial settings
* Each chapter reviews the most recent literature on a specific topic of interest to computational chemists


For researchers and students interested in computational chemistry.

Table of Contents

  • Section 1: Chemical Education (T. Zielinski)

    1. Real World Kinetics via Simulations (F.A. Houle, W.D. Hinsberg).

    Section 2: Quantum Mechanical Methods (T.D. Crawford).

    2. Explicitly Correlated Approaches for Electronic Structure Computations (E.F. Valeev).

    3. Hybrid Methods: ONIOM (QM:MM) and QM/MM
    (T. Vreven, K. Morokuma).

    4. On the Selection of Domains and Pairs in Local Correlation Treatments (H.-J. Werner, K. Pflüger).

    Section 3: Molecular Modeling Methods (C. Simmerling).

    5. Simulations of Temperature and Pressure Unfolding Peptides and Proteins with Replica Exchange Molecular Dynamics (A.E. Garcia et al.).

    6. Hybrid Explicit/Implicit Solvation Methods (A. Okur, C. Simmerling).

    Section 4: Advances in QSAR/QSPR (Y. Martin).

    7. Variable Selection QSAR and Model Validation
    (A. Tropsha).

    8. Machine Learning in Computational Chemistry
    (B.B. Goldman, W.P. Walters).

    9. Molecular Similarity: Advances in Methods, Applications, and Validations in Virtual Screening and QSAR (A. Bender et al.).

    Section 5: Applications of Computational Methods (H. Carlson, J. Madura).

    10. Cytochrome P450 Enzymes: Computational Approaches to Substrate Prediction (A. Verras et al.).

    11. Recent Advances in Design of Small-Molecule Ligands to Target Protein-Protein Interactions (Chao-Yie Yang, Shaomeng Wang).

    12. Accelerating Conformational Transitions in Biomolecular Simulations (D. Hamelberg, J.A. McCammon).

    13. Principal Component Analysis: A Review of its Application on Molecular Dynamics Data
    (S.A. Mueller Stein et al.).

    14. Solvent Effects on Organic Reactions from QM/MM Simulations (O. Acevedo, W.L. Jorgensen).

    15. Structure-Based Design of New Anti-Bacterial Agents (Haihong Ni, J. Wendoloski).

    16. Recent Evaluations of High Throughput Docking Methods for Pharmaceutical Lead Finding - Consensus and Caveats (W.D. Cornell).

Product details

  • No. of pages: 346
  • Language: English
  • Copyright: © Elsevier Science 2006
  • Published: October 10, 2006
  • Imprint: Elsevier Science
  • eBook ISBN: 9780080465425

About the Editor

David Spellmeyer

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.

Affiliations and Expertise

Nodality, Inc., CA, USA

Ratings and Reviews

Write a review

There are currently no reviews for "Annual Reports in Computational Chemistry"