ACS Publications. Most Trusted. Most Cited. Most Read
AceCloud: Molecular Dynamics Simulations in the Cloud
My Activity

Figure 1Loading Img
    Application Note

    AceCloud: Molecular Dynamics Simulations in the Cloud
    Click to copy article linkArticle link copied!

    View Author Information
    Acellera, Barcelona Biomedical Research Park (PRBB), C/Dr. Aiguader 88, 08003 Barcelona, Spain
    Computational Biophysics Laboratory (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C/Dr. Aiguader 88, 08003 Barcelona, Spain
    § Institució Catalana de Recerca i Estudis Avançats, Passeig Lluis Companys 23, 08010 Barcelona, Spain
    *E-mail: [email protected] (M.J.H.).
    *E-mail: [email protected] (G.D.F.).
    Other Access Options

    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2015, 55, 5, 909–914
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jcim.5b00086
    Published April 7, 2015
    Copyright © 2015 American Chemical Society

    Abstract

    Click to copy section linkSection link copied!
    Abstract Image

    We present AceCloud, an on-demand service for molecular dynamics simulations. AceCloud is designed to facilitate the secure execution of large ensembles of simulations on an external cloud computing service (currently Amazon Web Services). The AceCloud client, integrated into the ACEMD molecular dynamics package, provides an easy-to-use interface that abstracts all aspects of interaction with the cloud services. This gives the user the experience that all simulations are running on their local machine, minimizing the learning curve typically associated with the transition to using high performance computing services.

    Copyright © 2015 American Chemical Society

    Read this article

    To access this article, please review the available access options below.

    Get instant access

    Purchase Access

    Read this article for 48 hours. Check out below using your ACS ID or as a guest.

    Recommended

    Access through Your Institution

    You may have access to this article through your institution.

    Your institution does not have access to this content. Add or change your institution or let them know you’d like them to include access.

    Cited By

    Click to copy section linkSection link copied!

    This article is cited by 17 publications.

    1. Carsten Kutzner, Christian Kniep, Austin Cherian, Ludvig Nordstrom, Helmut Grubmüller, Bert L. de Groot, Vytautas Gapsys. GROMACS in the Cloud: A Global Supercomputer to Speed Up Alchemical Drug Design. Journal of Chemical Information and Modeling 2022, 62 (7) , 1691-1711. https://doi.org/10.1021/acs.jcim.2c00044
    2. S. Doerr, M. J. Harvey, Frank Noé, and G. De Fabritiis . HTMD: High-Throughput Molecular Dynamics for Molecular Discovery. Journal of Chemical Theory and Computation 2016, 12 (4) , 1845-1852. https://doi.org/10.1021/acs.jctc.6b00049
    3. Vaishali M. Patil, Satya P. Gupta, Neeraj Masand, Krishnan Balasubramanian. Experimental and computational models to understand protein-ligand, metal-ligand and metal-DNA interactions pertinent to targeted cancer and other therapies. European Journal of Medicinal Chemistry Reports 2024, 10 , 100133. https://doi.org/10.1016/j.ejmcr.2024.100133
    4. Anna M. Herz, Tahsin Kellici, Inaki Morao, Julien Michel. Alchemical Free Energy Workflows for the Computation of Protein-Ligand Binding Affinities. 2024, 241-264. https://doi.org/10.1007/978-1-0716-3449-3_11
    5. Juveriya Israr, Sahabjada Siddiqui, Sankalp Misra, Indrajeet Singh, Ajay Kumar. Bioinformatics in Pathway Identification, Design, Modelling, and Simulation. 2024, 181-198. https://doi.org/10.1007/978-981-99-8401-5_9
    6. Rizwan Qureshi, Bin Zou, Tanvir Alam, Jia Wu, Victor Lee, Hong Yan. Computational Methods for the Analysis and Prediction of EGFR-mutated Lung Cancer Drug Resistance: Recent Advances in Drug Design, Challenges and Future Prospects. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2022, 8 , 1-1. https://doi.org/10.1109/TCBB.2022.3141697
    7. Ajitha Mohan, Suparna Banerjee, Kanagaraj Sekar. Role of Advanced Computing in the Drug Discovery Process. 2021, 59-90. https://doi.org/10.1007/978-981-15-8936-2_4
    8. Katja Faelber, Lea Dietrich, Jeffrey K. Noel, Florian Wollweber, Anna-Katharina Pfitzner, Alexander Mühleip, Ricardo Sánchez, Misha Kudryashev, Nicolas Chiaruttini, Hauke Lilie, Jeanette Schlegel, Eva Rosenbaum, Manuel Hessenberger, Claudia Matthaeus, Séverine Kunz, Alexander von der Malsburg, Frank Noé, Aurélien Roux, Martin van der Laan, Werner Kühlbrandt, Oliver Daumke. Structure and assembly of the mitochondrial membrane remodelling GTPase Mgm1. Nature 2019, 571 (7765) , 429-433. https://doi.org/10.1038/s41586-019-1372-3
    9. Antonio Jesús Banegas-Luna, Baldomero Imbernón, Antonio Llanes Castro, Alfonso Pérez-Garrido, José Pedro Cerón-Carrasco, Sandra Gesing, Ivan Merelli, Daniele D’Agostino, Horacio Pérez-Sánchez. Advances in distributed computing with modern drug discovery. Expert Opinion on Drug Discovery 2019, 14 (1) , 9-22. https://doi.org/10.1080/17460441.2019.1552936
    10. Abdurrahman Olğaç, Aslı Türe, Simla Olğaç, Steffen Möller. Cloud-Based High Throughput Virtual Screening in Novel Drug Discovery. 2019, 250-278. https://doi.org/10.1007/978-3-030-16272-6_9
    11. Veronica Salmaso, Stefano Moro. Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview. Frontiers in Pharmacology 2018, 9 https://doi.org/10.3389/fphar.2018.00923
    12. M. Aldeghi, P.C. Biggin. Advances in Molecular Simulation. 2017, 14-33. https://doi.org/10.1016/B978-0-12-409547-2.12343-1
    13. Thomas Hart, Lei Xie. Providing data science support for systems pharmacology and its implications to drug discovery. Expert Opinion on Drug Discovery 2016, 11 (3) , 241-256. https://doi.org/10.1517/17460441.2016.1135126
    14. Vladimir Sobeslav, Petra Maresova, Ondrej Krejcar, Tanos C.C. Franca, Kamil Kuca. Use of cloud computing in biomedicine. Journal of Biomolecular Structure and Dynamics 2016, 1 , 1-10. https://doi.org/10.1080/07391102.2015.1127182
    15. Philip C. Biggin, Matteo Aldeghi, Michael J. Bodkin, Alexander Heifetz. Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties. 2016, 161-181. https://doi.org/10.1007/978-3-319-35072-1_12
    16. Yi Li, Jihong Yu. Genetic engineering of inorganic functional modular materials. Chemical Science 2016, 7 (6) , 3472-3481. https://doi.org/10.1039/C6SC00123H
    17. Xiangqiang Xu, Gabriel Dunham, Xinghui Zhao, David Chiu, Jie Xu. Modeling Parallel Molecular Simulations on Amazon EC2. 2015, 97-100. https://doi.org/10.1109/CCBD.2015.50

    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2015, 55, 5, 909–914
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jcim.5b00086
    Published April 7, 2015
    Copyright © 2015 American Chemical Society

    Article Views

    1246

    Altmetric

    -

    Citations

    Learn about these metrics

    Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

    Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

    The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.