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A new computational model for protein folding based on atomic solvation.


ABSTRACT: A new model for calculating the solvation energy of proteins is developed and tested for its ability to identify the native conformation as the global energy minimum among a group of thousands of computationally generated compact non-native conformations for a series of globular proteins. In the model (called the WZS model), solvation preferences for a set of 17 chemically derived molecular fragments of the 20 amino acids are learned by a training algorithm based on maximizing the solvation energy difference between native and non-native conformations for a training set of proteins. The performance of the WZS model confirms the success of this learning approach; the WZS model misrecognizes (as more stable than native) only 7 of 8,200 non-native structures. Possible applications of this model to the prediction of protein structure from sequence are discussed.

SUBMITTER: Wang Y 

PROVIDER: S-EPMC2143174 | biostudies-other | 1995 Jul

REPOSITORIES: biostudies-other

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A new computational model for protein folding based on atomic solvation.

Wang Y Y   Zhang H H   Scott R A RA  

Protein science : a publication of the Protein Society 19950701 7


A new model for calculating the solvation energy of proteins is developed and tested for its ability to identify the native conformation as the global energy minimum among a group of thousands of computationally generated compact non-native conformations for a series of globular proteins. In the model (called the WZS model), solvation preferences for a set of 17 chemically derived molecular fragments of the 20 amino acids are learned by a training algorithm based on maximizing the solvation ener  ...[more]

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