Protein model refinement using an optimized physics-based all-atom force field.

Protein model refinement using an optimized physics-based all-atom force field. Research Abstract Details 

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Protein model refinement using an optimized physics-based all-atom force field. Abstract Text:

One of the greatest challenges in protein structure prediction is the refinement of low-resolution predicted models to high-resolution structures that are close to the native state. Although contemporary structure prediction methods can assemble the correct topology for a large fraction of protein domains, such approximate models are often not of the resolution required for many important applications, including studies of reaction mechanisms and virtual ligand screening. Thus, the development of a method that could bring those structures closer to the native state is of great importance. We recently optimized the relative weights of the components of the Amber ff03 potential on a large set of decoy structures to create a funnel-shaped energy landscape with the native structure at the global minimum. Such an energy function might be able to drive proteins toward their native structure. In this work, for a test set of 47 proteins, with 100 decoy structures per protein that have a range of structural similarities to the native state, we demonstrate that our optimized potential can drive protein models closer to their native structure. Comparing the lowest-energy structure from each trajectory with the starting decoy, structural improvement is seen for 70% of the models on average. The ability to do such systematic structural refinements by using a physics-based all-atom potential represents a promising approach to high-resolution structure prediction.

Protein model refinement using an optimized physics-based all-atom force field. Publishing Authors By Initials

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Protein model refinement using an optimized physics-based all-atom force field. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Proceedings of the National Academy of Sciences of

VOLUME: 105

Page Numbers: 8268-73

Journal Abbreviation: Proc. Natl. Acad. Sci. U.S.A.

ISSN: 1091-6490

DAY: 11

MONTH: 06

YEAR: 2008

Protein model refinement using an optimized physics-based all-atom force field. Information

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LANGUAGE: eng

NlmUniqueID: 7505876

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Grant and Affiliation Information for Protein model refinement using an optimized physics-based all-atom force field.

AFFILIATION: Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 250 14th Street NW, Atlanta, GA 30318, USA.

Country: United States

AGENCY: United States NCRR

GRANT: RR-12255

ACRONYM: RR

MEDLINETA: Proc Natl Acad Sci U S A

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