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A beta-complex statistical four body contact potential combined with a hydrogen bond statistical potential recognizes the correct native structure from protein decoy sets

Authors

  • Gilberto Sánchez-González,

    1. Facultad de Ciencias, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos, México
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  • Jae-Kwan Kim,

    1. Voronoi Diagram Research Center, Department of Industrial Engineering, Hanyang University, Seoul, Korea
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  • Deok-Soo Kim,

    1. Voronoi Diagram Research Center, Department of Industrial Engineering, Hanyang University, Seoul, Korea
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  • Ramón Garduño-Juárez

    Corresponding author
    1. Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, México, México
    • Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Av. Universidad S/N, Cuernavaca, Morelos, México
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Correspondence to: Ramón Garduño-Juárez, Ph. D., Av. Universidad S/N, Col. Chamilpa, 62250 Cuernavaca, Morelos, México. E-mail: ramon@fis.unam.mx

ABSTRACT

We present a new four-body knowledge-based potential for recognizing the native state of proteins from their misfolded states. This potential was extracted from a large set of protein structures determined by X-ray crystallography using BetaMol, a software based on the recent theory of the beta-complex (β-complex) and quasi-triangulation of the Voronoi diagram of spheres. This geometric construct reflects the size difference among atoms in their full Euclidean metric; property not accounted for in a typical 3D Delaunay triangulation. The ability of this potential to identify the native conformation over a large set of decoys was evaluated. Experiments show that this potential outperforms a potential constructed with a classical Delaunay triangulation in decoy discrimination tests. The addition of a statistical hydrogen bond potential to our four-body potential allows a significant improvement in the decoy discrimination, in such a way that we are able to predict successfully the native structure in 90% of cases. Proteins 2013; 81:1420–1433. © 2013 Wiley Periodicals, Inc.

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