Bayesian Statistical Studies of the Ramachandran Distribution

Pertsemlidis Alexander, Zelinka Jan, Fondon John W., Henderson R. Keith and Otwinowski Zbyszek
Additional contact information
Pertsemlidis Alexander: UT Southwestern Medical Center
Zelinka Jan: UT Southwestern Medical Center
Fondon John W.: UT Southwestern Medical Center
Henderson R. Keith: UT Southwestern Medical Center
Otwinowski Zbyszek: UT Southwestern Medical Center

Statistical Applications in Genetics and Molecular Biology, 2005, vol. 4, issue 1, 18

Abstract: We describe a method for the generation of knowledge-based potentials and apply it to the observed torsional angles of known protein structures. The potential is derived using Bayesian reasoning, and is useful as a prior for further such reasoning in the presence of additional data. The potential takes the form of a probability density function, which is described by a small number of coefficients with the number of necessary coefficients determined by tests based on statistical significance and entropy. We demonstrate the methods in deriving one such potential corresponding to two dimensions, the Ramachandran plot. In contrast to traditional histogram-based methods, the function is continuous and differentiable. These properties allow us to use the function as a force term in the energy minimization of appropriately described structures. The method can easily be extended to other observable angles and higher dimensions, or to include sequence dependence and should find applications in structure determination and validation.

Keywords: knowledge-based modeling; maximum likelihood; structure refinement; torsional angles (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (3)

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DOI: 10.2202/1544-6115.1165

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