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Toward Quantitative Protein Structure Prediction

  • Teresa Head-Gordon
Chapter

Abstract

We review a constrained optimization strategy known as the antlion method for the purpose of protein structure prediction. This method involves the use of neural network predictions of secondary and tertiary structure to systematically deform a protein energy hypersurface to retain only a single minimum near to the native structure. Successful constrained optimization as applied to protein folding relies on (1) an understanding of the chemistry that distinguishes the native minimum from other metastable structures, (2) the incorporation of such information as robust constraints on the energy function to isolate the native structure minimum, and (3) progress toward providing a quantitative representation of the potential or free energy function. We provide a discussion of completed work by us that begins to affect these three problem areas as we move toward our goal of quantitative protein structure prediction.

Keywords

Boolean Function Penalty Function Hide Neuron Protein Structure Prediction Nonbonded Interaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Birkhäuser Boston 1994

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  • Teresa Head-Gordon

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