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A protein is usually classified into one of the following four structural classes: all α, all β, (a + B) and α/β. In this paper, based on the maximum correlation-coefficient principle, a new formulation is proposed for predicting the structural class of a protein according to its amino acid composition. Calculations have been made for a development set of proteins from which the amino acid compositions for the standard structural classes were derived, and an independent set of proteins which are outside the development set. The former can test the self consistency of a method and the latter can test its extrapolating effectiveness. In both cases, the results showed that the new method gave a considerably higher rate of correct prediction than any of the previous methods, implying that a significant improvement has been achieved by implementing the maximum-correlation-coefficient principle in the new method. [ABSTRACT FROM AUTHOR]

We have analyzed the amino acid distribution in seven nuclearly encoded and five mitochondrially encoded inner membrane proteins with experimentally well characterized topologies. The mitochondrially encoded proteins conform to the ‘positive inside’ rule, i.e. they have many more positively charged residues in their non-translocated as compared to translocated domains. However, most of the nuclearly encoded proteins do not show such a bias but instead have a surprisingly skewed distribution of Glu residues with an almost ten times higher frequency in the intermembrane space than in the matrix domains. These findings suggest that some, but possibly not all, nuclearly encoded inner membrane proteins may insert into the membrane by a mechanism that does not depend on the distribution of positively charged amino acids. [ABSTRACT FROM AUTHOR]