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Challenges and opportunities of automated protein-protein docking: HDOCK server versus human predictions in CAPRI Rounds 38-46.

Research paper by Yumeng Y Yan, Jiahua J He, Yuyu Y Feng, Peicong P Lin, Huanyu H Tao, Sheng-You SY Huang

Indexed on: 31 Jan '20Published on: 30 Jan '20Published in: Proteins: Structure, Function, and Bioinformatics



Abstract

Protein-protein docking plays an important role in the computational prediction of the complex structure between two proteins. For years, a variety of docking algorithms have been developed, as witnessed by the Critical Assessment of PRediction Interactions (CAPRI) experiments. However, despite their successes, many docking algorithms often require a series of manual operations like modeling structures from sequences, incorporating biological information, and selecting final models. The difficulties in these manual steps have significantly limited the applications of protein-protein docking, as most of the users in the community are non-experts in docking. Therefore, automated docking like a web server, which can give a comparable performance to human docking protocol, is pressingly needed. As such, we have participated in the blind CAPRI experiments for Rounds 38-45 and CASP13-CAPRI challenge for Round 46 with both our HDOCK automated docking web server and human docking protocol. It was shown that our HDOCK server achieved an 'acceptable' or higher CAPRI-rated model in the top 10 submitted predictions for 65.5% and 59.1% of the targets in the docking experiments of CAPRI and CASP13-CAPRI, respectively, which are comparable to 66.7% and 54.5% for human docking protocol. Similar trends can also be observed in the scoring experiments. These results validated our HDOCK server as an efficient automated docking protocol for non-expert users. Challenges and opportunities of automated docking are also discussed. This article is protected by copyright. All rights reserved. © 2020 Wiley Periodicals, Inc.