Protein threading by learning

Physics – Condensed Matter – Soft Condensed Matter

Scientific paper

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14 pages, 4 figures. Accepted to Proc. Nat. Aca. Sci

Scientific paper

10.1073/pnas.241133698

Using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins. These parameters provide a quantitative measure of the propensities of amino acids to be buried or exposed and to be in a given secondary structure and are a good starting point for solving both the threading and design problems.

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