TY - JOUR
T1 - IScore
T2 - A novel graph kernel-based function for scoring protein-protein docking models
AU - Geng, Cunliang
AU - Jung, Yong
AU - Renaud, Nicolas
AU - Honavar, Vasant
AU - Bonvin, Alexandre M.J.J.
AU - Xue, Li C.
N1 - Funding Information:
This work was supported in part by the European H2020 e-Infrastructure grant BioExcel (grant no. 675728). C.G. acknowledges financial support from the China Scholarship Council (grant no. 201406220132). L.X. acknowledges financial support from the Netherlands Organisation for Scientific Research (Veni grant 722.014.005) and an Accelerating Scientific Discovery (ASDI) grant from the Netherlands eScience Center (grant no. 027016G04). The work of V.H. was supported in part by the National Center for Advancing Translational Sciences, National Institutes of Health through the grant UL1 TR000127 and TR002014, by the National Science Foundation, through the grants 1518732, 1640834 and 1636795, the Pennsylvania State University’s Institute for Cyberscience and the Center for Big Data Analytics and Discovery Informatics, the Edward Frymoyer Endowed Professorship in Information Sciences and Technology at Pennsylvania State University and the Sudha Murty Distinguished Visiting Chair in Neurocomputing and Data Science funded by the Pratiksha Trust at the Indian Institute of Science. YJ was supported in part by a research assistantship funded by the Center for Big Data Analytics and Discovery Informatics at Pennsylvania State University.
Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Motivation: 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. Results: 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 datasets: (i) Docking software-specific models and (ii) 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.
AB - Motivation: 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. Results: 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 datasets: (i) Docking software-specific models and (ii) 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.
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U2 - 10.1093/bioinformatics/btz496
DO - 10.1093/bioinformatics/btz496
M3 - Article
C2 - 31199455
AN - SCOPUS:85076630747
VL - 36
SP - 112
EP - 121
JO - Bioinformatics
JF - Bioinformatics
SN - 1367-4803
IS - 1
ER -