Using Sequence-Predicted Contacts to Guide Template-free Protein Structure Prediction

Template-free protein structure prediction seeks three-dimensional structures that organize the serially-bonded amino acids in ways that lower interatomic energy. It is now well understood that energy functions are unreliable guides towards biologically-active structures. This realization raises questions on the proper role and utilization of energy functions. Recent work suggests employing complementary information in the form of amino-acid contacts. Here, we advance this line of work and leverage multi-objective optimization to investigate a variety of combinations of interatomic energy and contact-based scoring. Evaluation on diverse datasets demonstrates the superiority of combining contact information with energy functions in a multi-objective optimization setting for template-free protein structure prediction.

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