Abstract
Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.
Highlights
The COVID-19 pandemic has spurred a wealth of new structural biology data related to the severe acute respiratory syndrome coronavirus SARS-CoV-2 and its interactions with other macromolecules involved in the development and spread of the disease (Baker, 2020; Domling & Gao, 2020)
We illustrate our point with recent COVID-19 structural and modelling data examples
A particular aim is to treat the sharing of visual experiences with the so-called FAIR principles to render them Findable, Accessible, Interoperable and Reusable (Wilkinson et al, 2016)
Summary
The COVID-19 pandemic has spurred a wealth of new structural biology data related to the severe acute respiratory syndrome coronavirus SARS-CoV-2 and its interactions with other macromolecules involved in the development and spread of the disease (Baker, 2020; Domling & Gao, 2020) Such structural data are transparent to experts in the field, but require adequate visualization to become accessible to a broader audience. A particular aim is to treat the sharing of visual experiences with the so-called FAIR principles to render them Findable, Accessible, Interoperable and Reusable (Wilkinson et al, 2016) These principles should be applied for the underlying raw chemical (Blanke et al, 2020), structural and modelling data, and it has been pointed out that this is generally the case in crystallography (Helliwell, 2019). This target is challenging by itself, as common FAIR-based sharing platforms do not provide a category that is well adapted to visual experiences
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