Using iCn3D and the World Wide Web for structure-based collaborative research: Analyzing molecular interactions at the root of COVID-19

  1. Philippe Youkharibache
  2. Raul Cachau
  3. Tom Madej
  4. Jiyao Wang

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

The COVID-19 pandemic took us ill-prepared and tackling the many challenges it poses in a timely manner requires world-wide collaboration. Our ability to study the SARS-COV-2 virus and its interactions with its human host in molecular terms efficiently and collaboratively becomes indispensable and mission-critical in the race to develop vaccines, drugs, and neutralizing antibodies. There is already a significant corpus of 3D structures related to SARS and MERS coronaviruses, and the rapid generation of new structures demands the use of efficient tools to expedite the sharing of structural analyses and molecular designs and convey them in their native 3D context in sync with sequence data and annotations. We developed iCn3D (pronounced “I see in 3D”) 1 to take full advantage of web technologies and allow scientists of different backgrounds to perform and share sequence-structure analyses over the Internet and engage in collaborations through a simple mechanism of exchanging “lifelong” web links (URLs). This approach solves the very old problem of “sharing of molecular scenes” in a reliable and convenient manner. iCn3D links are sharable over the Internet and make data and entire analyses findable, accessible, and reproducible, with various levels of interoperability. Links and underlying data are FAIR 2 and can be embedded in preprints and papers, bringing a 3D live and interactive dimension to a world of text and static images used in current publications, eliminating at the same time the need for arcane supplemental materials. This paper exemplifies iCn3D capabilities in visualization, analysis, and sharing of COVID-19 related structures, sequence variability, and molecular interactions.

Article activity feed

  1. Version published to 10.1101/2020.07.01.182964v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.07.01.182964: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We will review here the most relevant elements. 2. Structural Analysis: 3. Collaborating, Data Sharing, and Publishing:
    Publishing
    suggested: (NPG publishing format, RRID:SCR_000201)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.07.01.182964v1 on bioRxiv