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Bioinformatics. 2019 Aug 8. pii: btz623. doi: 10.1093/bioinformatics/btz623. [Epub ahead of print]

Integrating ab initio and template-based algorithms for protein-protein complex structure prediction.

Author information

Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.



Template-based and template-free methods have both been widely used in predicting the structures of protein-protein complexes. Template-based modeling is effective when a reliable template is available, while template-free methods are required for predicting the binding modes or interfaces that have not been previously observed. Our goal is to combine the two methods to improve computational protein-protein complex structure prediction.


Here we present a method to identify and combine high-confidence predictions of a template-based method (SPRING) with a template-free method (ZDOCK). Cross-validated using the protein-protein docking benchmark version 5.0, our method (ZING) achieved a success rate of 68.2%, outperforming SPRING and ZDOCK, with success rates of 52.1% and 35.9% respectively, when the top 10 predictions were considered per test case. In conclusion, a statistics-based method that evaluates and integrates predictions from template-based and template-free methods is more successful than either method independently.


ZING is available for download as a Github repository (


Supplementary data are available at Bioinformatics online.

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