Protein threading by learning

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

doi:10.1073/pnas.241133698

Protein threading by learning

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

Department of Brain Sciences

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

Abstract

By 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.

Original language	English
Pages (from-to)	14350-14355
Number of pages	6
Journal	Proceedings of the National Academy of Sciences of the United States of America
Volume	98
Issue number	25
DOIs	https://doi.org/10.1073/pnas.241133698
State	Published - 4 Dec 2001

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AU - Dima, Ruxandra I.

AU - Maritan, Amos

AU - Banavar, Jayanth R.

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U2 - 10.1073/pnas.241133698

DO - 10.1073/pnas.241133698

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Protein threading by learning

Abstract

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