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Coarse Grained Modeling and Approaches to Protein Folding

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The theoretical prediction of protein structures has become a field of increasing importance in both biology and physics. Reliable prediction methods in fact, would spare time consuming experimental X-ray and NMR techniques and they would represent a challenge for computational protein modeling as well. The well known limitations of all-atom models call for the development of coarse-grained protein descriptions including a minimal number of protein-like features, while being capable of mimicking the essence of protein folding mechanisms. In this paper we review the most important classes of coarse-grained protein models in order of increasing complexity, starting from (over simplified) binary models, to models with one or two reaction centers per residue. We discuss how, despite their simplification, coarse-grained models constitute a viable approach to structure prediction and they shed light on many aspects of protein-folding problem.





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Keywords: Protein folding; coarse-graining; effective potentials; protein modelling; united atom

Document Type: Research Article

Publication date: September 1, 2010

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  • Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a wide range of the integration of biology with computer and information science.

    The journal focuses on reviews on advances in computational molecular/structural biology, encompassing areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Developments in these fields have direct implications on key issues related to health care, medicine, genetic disorders, development of agricultural products, renewable energy, environmental protection, etc.

    Current Bioinformatics is an essential journal for all academic and industrial researchers who want expert knowledge on all major advances in bioinformatics.
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