Protein folding using contact maps

Abstract

We present the development of the idea to use dynamics in the space of contact maps as a computational approach to the protein folding problem. We first introduce two important technical ingredients, the reconstruction of a three dimensional conformation from a contact map and the Monte Carlo dynamics in contact map space. We then discuss two approximations to the free energy of the contact maps and a method to derive energy parameters based on perceptron learning. Finally we present results, first for predictions based on threading and then for energy minimization of crambin and of a set of 6 immunoglobulins. The main result is that we proved that the two simple approximations we studied for the free energy are not suitable for protein folding. Perspectives are discussed in the last section.

29 pages, 10 figures

References in corpus (5)

• A New Monte Carlo Algorithm for Protein Folding
• Folding, Design and Determination of Interaction Potentials Using Off-Lattice Dynamics of Model Heteropolymers
• Protein design in a lattice model of hydrophobic and polar amino acids
• Statistical Properties of Contact Maps
• Stability Threshold as a Selection Principle for Protein Design

Cited by in corpus (8)

• Protein threading by learning
• The Origin of the Designability of Protein Structures
• Determination of optimal effective interactions between amino acids in globular proteins
• Thermodynamics of protein folding: a random matrix formulation
• Periodicity-dependent stiffness of periodic hydrophilic-hydrophobic hetero-polymers
• Hydrogen Bonds, Hydrophobicity Forces and the Character of the Collapse Transition
• Selecting fast folding proteins by their rate of convergence
• Energetic frustrations in protein folding at residue resolution: a simulation study of homologous immunoglobulin-like \b{eta}-sandwich proteins