Annual Reports in Computational Chemistry
- 1st Edition, Volume 1 - March 21, 2005
- Imprint: Elsevier Science
- Editor: David Spellmeyer
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 4 - 5 1 9 1 6 - 0
- Paperback ISBN:9 7 8 - 0 - 4 4 4 - 5 4 7 6 0 - 6
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 4 6 0 3 0 - 7
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 discip… Read more
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Request a sales quoteAnnual 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
* 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
* 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.
Quantum Mechanical Methods (T.D. Crawford).
1. An Introduction to the State-of-the-Art in Quantum Chemistry (F. Jensen).
2. Time-Dependent Density Functional Theory in Quantum Chemistry (F. Furche, K. Burke).
3. Computational Thermochemistry: A Brief Overview of Quantum Mechanical Approaches (J.M.L. Martin).
4. Bond Breaking in Quantum Chemistry (C.D. Sherrill).
Molecular Modelling Methods (C. Simmerling).
5. A Review of the TIP4P, TIP4P-Ew, TIP5P, and TIP5P-E Water Models (T.J. Dick, J.D. Madura).
6. Molecular Modeling and Atomistic Simulation of Nucleic Acids (T.E. Cheatham, III).
7. Empirical Force Fields for Proteins: Current Status and Future Directions (A.D. MacKerell, Jr.).
8. Non-Equilibrium Approaches to Free Energy Calculations (A.E. Roitberg).
9. Calculating Binding Free Energy in Protein-ligand Interaction (K. Raha, K.M. Merz, Jr.).
Advances in QSAR/QSPR (Y. Martin).
10. Computational Prediction of ADMET Properties: Recent Developments and Future Challenges (D.E. Clark).
1. An Introduction to the State-of-the-Art in Quantum Chemistry (F. Jensen).
2. Time-Dependent Density Functional Theory in Quantum Chemistry (F. Furche, K. Burke).
3. Computational Thermochemistry: A Brief Overview of Quantum Mechanical Approaches (J.M.L. Martin).
4. Bond Breaking in Quantum Chemistry (C.D. Sherrill).
Molecular Modelling Methods (C. Simmerling).
5. A Review of the TIP4P, TIP4P-Ew, TIP5P, and TIP5P-E Water Models (T.J. Dick, J.D. Madura).
6. Molecular Modeling and Atomistic Simulation of Nucleic Acids (T.E. Cheatham, III).
7. Empirical Force Fields for Proteins: Current Status and Future Directions (A.D. MacKerell, Jr.).
8. Non-Equilibrium Approaches to Free Energy Calculations (A.E. Roitberg).
9. Calculating Binding Free Energy in Protein-ligand Interaction (K. Raha, K.M. Merz, Jr.).
Advances in QSAR/QSPR (Y. Martin).
10. Computational Prediction of ADMET Properties: Recent Developments and Future Challenges (D.E. Clark).
Applications of Computational Methods (H. Carlson).
11. Filtering in Drug Discovery (C.A. Lipinski).
12. Structure-Based Lead Optimization (D. Joseph-McCarthy).
13. Targeting the Kinome with Computational Chemistry (M.L. Lamb).
Chemical Education (T. Zielinski).
14. Status of Research-based Experiences for First-and Second-Year Undergraduate Students (J.D. Evanseck, S.M. Firestine).
15. Crossing the Line: Stochastic Models in the Chemistry Classroom (M.M. Francl).
16. Simulation of chemical Concepts, Systems and Processes using Symbolic Computation Engines: from Computer-Assisted Problem-Solving Approach to Advanced Tools for Research (J. Rittenhouse, M. Scarlete).
Emerging Science (R. Wheeler).
17. The Challenges in Developing Molecular-Simulations of Fluid Properties for Industrial Applications (R.D. Mountain, A.C. Chaka).
18. Computationally Assisted Protein Design (S. Park, J.G. Saven).
- Edition: 1
- Volume: 1
- Published: March 21, 2005
- Imprint: Elsevier Science
- Language: English
- Hardback ISBN: 9780444519160
- Paperback ISBN: 9780444547606
- eBook ISBN: 9780080460307
DS
David Spellmeyer
David Spellmeyer is a Biotechnology Executive and Entrepreneur with over 30 years of broad experience in the life sciences industry. He is Principal at Interlaken Associates where he works closely with both early-stage companies and venture capital firms to build and lead strong pre-clinical R&D scientific teams focused on establishing scientific proof-of-concept for novel innovations. David is also an adjunct Associate Professor of Pharmaceutical Chemistry at the University of California San Francisco (UCSF). He has been actively involved in the entrepreneurship and innovation ecosystem supporting founders, students, post-docs, and faculty, serving as a mentor in programs at UCSF, California Life Sciences Institute’s FAST programs, California State University’s CSUPERB, UC Davis MentorNet, and as a reviewer for NIH SBIR/STTR Study Sections. David has recently served as CSO at Circle Pharma, an Executive-in-Residence at Pandect Biosciences, head of Quality for a diagnostics company, and an executive advisor for several startups. Prior to building Interlaken Associates, he held positions at DuPont Pharma (BMS), Chiron (Novartis), Signature BioScience, Nodality, and IBM Research. David works very closely with business development teams and has completed over 20 non-dilutive strategic corporate partnerships, several mergers, acquisitions, and joint ventures and participated in several rounds of venture financing. He received his BS in computer science and chemistry from Purdue University and his PhD in theoretical organic chemistry from UCLA and completed his post-doctoral training in pharmaceutical chemistry at UCSF.
Affiliations and expertise
Department of Pharmaceutical Chemistry, School of Pharmacy, University of California San Francisco, San Francisco, CA, USA