Protein dönme açılarını tahmin etmek için bilgi tabanlı yöntem

The three dimensional structure of a protein can be identified in terms of its torsion angles. These torsion angles can be considered as the degrees of freedom of a protein. In this study, a method grouping these torsion angles in different rotational isomeric states and estimating their probabilities is developed. Specifically, the probabilities of the various torsion angle states in Ramachandran maps is proposed and the accuracy of the method is examined using a knowledge based approach. Statistical independence and dependence of the states of different residues along the peptide chain are analyzed. The Flory isolated pair hypothesis, near neighbor correlations, context effects and long-range correlations are discussed. In the knowledge based approach, two different protein libraries i) coil library ii) full libarary are constructed and information from both these libraries is used. Results showed that amino acids have propensities for some rotational isomeric states that favor the choice of the native state torsion angles and they are context dependent, preferring different torsion states determined by the amino acid sequence of the protein. Context dependency is also related to chameleon sequences and the effect of chameleon sequences is also integrated into the method.