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Bioinformatics. 2019 Jun 14. pii: btz496. doi: 10.1093/bioinformatics/btz496. [Epub ahead of print]

iScore: A novel graph kernel-based function for scoring protein-protein docking models.

Geng C1, Jung Y2,3,4, Renaud N5, Honavar V2,3,6,7,4,8,9, Bonvin AMJJ1, Xue LC1.

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Bijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands.
Bioinformatics & Genomics Graduate Program, Pennsylvania State University, University Park, PA, USA.
Artificial Intelligence Research Laboratory, Pennsylvania State University, University Park, PA, USA.
Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA.
Netherlands eScience Center, Science Park 140 1098 XG Amsterdam, the Netherlands.
Center for Big Data Analytics and Discovery Informatics, Pennsylvania State University, University Park, PA, USA.
Institute for Cyberscience, Pennsylvania State University, University Park, PA, USA.
Clinical and Translational Sciences Institute, Pennsylvania State University, University Park, PA, USA.
College of Information Sciences & Technology, Pennsylvania State University, University Park, PA, USA.



Protein complexes play critical roles in many aspects of biological functions. Three-dimensional (3D) structures of protein complexes are critical for gaining insights into structural bases of interactions and their roles in the biomolecular pathways that orchestrate key cellular processes. Because of the expense and effort associated with experimental determinations of 3D protein complex structures, computational docking has evolved as a valuable tool to predict 3D structures of biomolecular complexes. Despite recent progress, reliably distinguishing near-native docking conformations from a large number of candidate conformations, the so-called scoring problem, remains a major challenge.


Here we present iScore, a novel approach to scoring docked conformations that combines HADDOCK energy terms with a score obtained using a graph representation of the protein-protein interfaces and a measure of evolutionary conservation. It achieves a scoring performance competitive with, or superior to, that of state-of-the-art scoring functions on two independent data sets: 1) Docking software-specific models and 2) the CAPRI score set generated by a wide variety of docking approaches (i.e., docking software-non-specific). iScore ranks among the top scoring approaches on the CAPRI score set (13 targets) when compared with the 37 scoring groups in CAPRI. The results demonstrate the utility of combining evolutionary, topological, and energetic information for scoring docked conformations. This work represents the first successful demonstration of graph kernels to protein interfaces for effective discrimination of near-native and non-native conformations of protein complexes.


The iScore code is freely available from Github: (DOI:10.5281/zenodo.2630567).


Supplementary data are available at Bioinformatics online.

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