engleski

Predicting Membrane Protein Secondary Structure: Preference Functions Method for Finding Optimal Conformational Parameters

An automated iterative method is developed for predicting secondary conformation in membrane proteins. The initial set of parameters are a- helix preferences and associated conformational preference functions extracted from the data set of known soluble protein structures. The secondary structure segments are assigned to each of 14 tested membrane proteins by using the prediction method, which evaluates and compares preference functions in the tested protein. A new set of parameters are then calculated which is based on the predicted protein structure from the previous iterative cycle. The method takes advantage of the similarities in local sequence patterns found in the tested proteins. Residues in membrane proteins are predicted with 84% accuracy and with the correlation coefficient for the a- helix structure equal to 0.68, which is a considerably better performance than that of neural network programs or Garnier-Robson’s algorithm.

photosynthetic reaction center ; rhodopseudomonas-viridis ; transport proteins ; alpha-helices ; resolution ; sequence ; bacteriorhodopsin ; drosophila ; rhodopsin ; homology

nije evidentirano