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bioRxiv · 10.1101/2020.07.01.182964

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

Youkharibache, P.·Cachau, R. E.·Wang, J.·Madej, T.
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Abstract

ABSTRACTThe 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.Competing Interest StatementThe authors have declared no competing interest.View Full Text

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Youkharibache, P., Cachau, R. E., Wang, J., Madej, T.. 2020-07-02. Using iCn3D and the World Wide Web for structure-based collaborative research: Analyzing molecular interactions at the root of COVID-19. https://doi.org/10.1101/2020.07.01.182964

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