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MEGADOCK-on-Colab: an easy-to-use protein-protein docking tool on Google Colaboratory

##article.authors##

DOI:

https://doi.org/10.51094/jxiv.374

キーワード:

protein-protein docking、 protein-protein interaction、 MEGADOCK、 Google Colaboratory

抄録

Motivation: Since the advent of ColabFold, numerous software packages have been provided with Google Colaboratory-compatible ipynb files, allowing users to effortlessly test and reproduce results without the need for local installation or configuration. MEGADOCK, a protein-protein docking tool, is particularly well-suited for Google Colaboratory due to its lightweight computations and GPU acceleration capabilities. To increase accessibility and promote widespread use, it is crucial to provide a computing environment compatible with Google Colaboratory.

Results: In this study, we report the development of a Google Colaboratory environment for running our protein-protein docking software, MEGADOCK. We provide a comprehensive ipynb file, including the compilation of MEGADOCK with the FFTW library installation on Colaboratory, the introduction of related tools using PyPI/apt, and the execution and visualization of docking structures. This streamlined environment enables users to visualize docking structures with just one click.

Availability: The code is available under a CC-BY NC 4.0 license from https://github.com/ohuelab/MEGADOCK-on-Colab.

利益相反に関する開示

none declared

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引用文献

Aoyama,K., Watanabe,H., Ohue, M., Akiyama, Y. (2020) Multiple HPC envi-ronments-aware container image configuration workflow for large-scale all-to-all protein-protein docking calculations. In Proc SCFA2020, LNCS, 12082, 23–39.

Cock,P.J., Antao,T., Chang,J.T., et al. (2009). Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics, 25(11), 1422–1423.

Corso,G., Stärk,H., Jing,B., et al. (2022) DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. In Proc ICLR2013, https://openreview.net/forum?id=kKF8_K-mBbS.

Jumper,J., Evans,R., Pritzel,A., et al. (2021) Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583–589.

Mirdita,M., Schütze,K., Moriwaki,Y., et al. (2022) ColabFold: making protein folding accessible to all. Nat Methods, 19(6), 679–682.

Nguyen,H., Case,D.A., Rose,A.S. (2018) NGLview-interactive molecular graphics for Jupyter notebooks. Bioinformatics, 34(7), 1241–1242.

Ohue,M., Shimoda,T., Suzuki,S., et al. (2014) MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercom-puters. Bioinformatics, 30(22), 3281–3283.

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投稿日時: 2023-05-02 16:15:49 UTC

公開日時: 2023-05-08 12:36:49 UTC
研究分野
情報科学