Performance of ZDOCK and ZRANK in CAPRI Rounds 13 - 19

By Howook Hwang, Thom Vreven, Brian G. Pierce, Jui-Hung Hung, Zhiping Weng. 2010

84 citations recorded by the source corpus.

We report the performance of the ZDOCK and ZRANK algorithms in CAPRI rounds 13–19 and introduce a novel measure atom contact frequency (ACF). To compute ACF, we identify the residues that most often make contact with the binding partner in the complete set of ZDOCK predictions for each target. We used ACF to predict the interface of the proteins, which, in combination with the biological data available in the literature, is a valuable addition to our docking pipeline. Furthermore, we incorporated a straightforward and efficient clustering algorithm with two purposes: (1) to determine clusters of similar docking poses (corresponding to energy funnels) and (2) to remove redundancies from the final set of predictions. With these new developments, we achieved at least one acceptable prediction for targets 29 and 36, at least one medium‐quality prediction for targets 41 and 42, and at least one high‐quality prediction for targets 37 and 40; thus, we succeeded for six out of a total of 12 targets. Proteins 2010. © 2010 Wiley‐Liss, Inc.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

DockQ: A Quality Measure for Protein-Protein Docking Models (2016, methodology): “This set contained 56,015 docking models for 118 targets from the protein-protein docking Benchmark 4.0 [17], constructed using SwarmDock [18] gra-ciously provided by the authors of Moal et al [13].”
ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers (2014, background): “For example, based on CAPRI ‘Acceptable’ criteria, the success rates of ZDOCK 3.0.2 on Docking Benchmark 4.0 (Hwang et al. , 2010b) are 12 and 51%, for the top 1 and 50 predictions, respectively, versus rates of 10 and 57% reported for the SwarmDock Server, which takes up to 36h per docking run…”
Accelerating Protein Docking in ZDOCK Using an Advanced 3D Convolution Library (2011, methodology): “0 showed vast improvements in its predictive ability versus the previous version when tested on a protein-protein docking benchmark [11], and has led to highly successful performance in the blind protein docking experiment, CAPRI [12,13].”
Contacts-based prediction of binding affinity in protein–protein complexes (2015, methodology): “The atom contact frequency in a set of predictions, a similar concept, has also been included in the ZRANK docking pipeline ( Hwang et al., 2010 ).”
CPORT: A Consensus Interface Predictor and Its Performance in Prediction-Driven Docking with HADDOCK (2011, unknown): “Very recently, the same result was found by Hwang et al. [20] and also from an analysis of CAPRI predictions [21].”