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Protein threading by learning

Iksoo Chang·Marek Cieplak·Ruxandra I. Dima·Amos Maritan·Jayanth R. Banavar
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Abstract

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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Iksoo Chang, Marek Cieplak, Ruxandra I. Dima, Amos Maritan, Jayanth R. Banavar. 2001-10-10. Protein threading by learning. https://doi.org/10.1073/pnas.241133698

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