Statistical Contact Potentials in Protein Coarse-Grained Modeling: From Pair to Multi-body Potentials
- Sumudu P. Leelananda,
- Yaping Feng,
- Pawel Gniewek,
- Andrzej Kloczkowski,
- Robert L. Jernigan
- … show all 5 hide
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Abstract
The basic concepts of coarse-graining protein structures led to the introduction of empirical statistical potentials in protein computations. We review the history of the development of statistical contact potentials in computational biology and discuss the common features and differences between various pair contact potentials. Potentials derived from the statistics of non-bonded contacts in protein structures from the Protein Data Bank (PDB) are compared with potentials developed for threading purposes based on the optimization of the selection of the native structures among decoys. The energy of transfer of amino acids from water to a protein environment is discussed in detail. We suggest that a next generation of statistical contact potentials should include the effects of residue packing in proteins to improve predictions of protein native three-dimensional structures. We review existing multi-body potentials that have been proposed in the literature, including our own recent four-body potentials. We show how these are related to amino acid substitution matrices.
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Within this Chapter
- Introduction
- History of Development of Knowledge-Based Potentials
- Distant-Independent Potential Functions
- Distance-Dependent Potential Functions
- Geometric Potential Functions
- Multi-body Potentials
- Optimization Method
- Comparative Analysis of Statistical Protein Contact Potentials to Infer Ideal Amino Acid Interaction Forms
- Statistical Force Fields for Coarse-Grained Protein Models
- Applications of Knowledge-Based Potential Functions
- Future Developments
- References
- References
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References (109)
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About this Chapter
- Title
- Statistical Contact Potentials in Protein Coarse-Grained Modeling: From Pair to Multi-body Potentials
- Book Title
- Multiscale Approaches to Protein Modeling
- Book Subtitle
- Structure Prediction, Dynamics, Thermodynamics and Macromolecular Assemblies
- Pages
- pp 127-157
- Copyright
- 2011
- DOI
- 10.1007/978-1-4419-6889-0_6
- Print ISBN
- 978-1-4419-6888-3
- Online ISBN
- 978-1-4419-6889-0
- Publisher
- Springer New York
- Copyright Holder
- Springer Science+Business Media, LLC
- Additional Links
- Topics
- eBook Packages
- Editors
-
-
Andrzej Kolinski
(ID1)
-
Andrzej Kolinski
- Editor Affiliations
-
- ID1. Dept. Chemistry, University of Warsaw
- Authors
-
-
Sumudu P. Leelananda
(1)
(2)
-
Yaping Feng
(1)
(2)
-
Pawel Gniewek
(2)
(3)
-
Andrzej Kloczkowski
(1)
(2)
-
Robert L. Jernigan
(1)
(2)
-
Sumudu P. Leelananda
- Author Affiliations
-
- 1. Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, IA, USA
- 2. L.H.Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA, USA
- 3. Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
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