Article

Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method

Proteins Structure Function and Bioinformatics, Wiley, ISSN 0887-3585

Volume 82, 2, 2014

DOI:10.1002/prot.24386, Dimensions: pub.1032949051, PMID: 23934827,

Affiliations

Organisations

  1. (1) University of Copenhagen, grid.5254.6, KU
  2. (2) Technical University of Denmark, grid.5170.3, DTU
  3. (3) University of Leeds, grid.9909.9
  4. (4) University of Oxford, grid.4991.5

Countries

Denmark

United Kingdom

Continents

Europe

Description

We propose a method to formulate probabilistic models of protein structure in atomic detail, for a given amino acid sequence, based on Bayesian principles, while retaining a close link to physics. We start from two previously developed probabilistic models of protein structure on a local length scale, which concern the dihedral angles in main chain and side chains, respectively. Conceptually, this constitutes a probabilistic and continuous alternative to the use of discrete fragment and rotamer libraries. The local model is combined with a nonlocal model that involves a small number of energy terms according to a physical force field, and some information on the overall secondary structure content. In this initial study we focus on the formulation of the joint model and the evaluation of the use of an energy vector as a descriptor of a protein's nonlocal structure; hence, we derive the parameters of the nonlocal model from the native structure without loss of generality. The local and nonlocal models are combined using the reference ratio method, which is a well-justified probabilistic construction. For evaluation, we use the resulting joint models to predict the structure of four proteins. The results indicate that the proposed method and the probabilistic models show considerable promise for probabilistic protein structure prediction and related applications.

Funders

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NORA University Profiles

University of Copenhagen

Technical University of Denmark

Danish Open Access Indicator

2014: Unused

Research area: Science & Technology

Danish Bibliometrics Indicator

2014: Level 1

Research area: Science & Technology

Dimensions Citation Indicators

Times Cited: 6

Relative Citation ratio (RCR): 0.2