title: Optimal potentials for predicting inter-helical packing in transmembrane proteins.
abstract: A set of pairwise contact potentials between amino acid residues in transmembrane helices was determined from the known native structure of the transmembrane protein (TMP) bacteriorhodopsin by the method of perceptron learning, using Monte Carlo dynamics to generate suitable "decoy" structures. The procedure of finding these decoys is simpler than for globular proteins, since it is reasonable to assume that helices behave as independent, stable objects and, therefore, the search in the conformational space is greatly reduced. With the learnt potentials, the association of the helices in bacteriorhodopsin was successfully simulated. The folding of a second TMP (the helix-dimer glycophorin A) was then accomplished with only a refinement of the potentials from a small number of decoys.
mesh_terms: D000596:Amino Acids / Q000737:chemistry; D001436:Bacteriorhodopsins / Q000737:chemistry; D006021:Glycophorins / Q000737:chemistry; D008565:Membrane Proteins / Q000737:chemistry*; D008958:Models, Molecular; D008962:Models, Theoretical; D009010:Monte Carlo Method; D016571:Neural Networks, Computer; D017510:Protein Folding; D017433:Protein Structure, Secondary
chemical_list: D000596:Amino Acids; D006021:Glycophorins; D008565:Membrane Proteins; D001436:Bacteriorhodopsins