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Aquaria: simplifying discovery and insight from protein structures

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Figure 1: Aquaria page for human tumor suppressor protein p53.


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We thank C. Hammang and V.P. Satagopam for helpful discussions. This work was supported by CSIRO's OCE Science Leader program and its Computational and Simulation Sciences platform, as well as the Alexander von Humboldt Foundation. We gratefully acknowledge the support of Amazon AWS in hosting the Aquaria server and in making PSSH2 available as a public data set.

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Authors and Affiliations



S.I.O. and A.S. jointly conceived of the project. S.I.O. oversaw the project and wrote the manuscript with contributions from A.S. and K.S.S. Software implementation was led by K.S.S. with contributions from S.I.O., C.S., V.H., N.P., F.A.B. and J.H. Interface design was led by C.S. with contributions from S.I.O. The development of PSSH2, the database underlying Aquaria, was led by A.S. with contributions from M.K., B.W., M.R. and B.R.

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Correspondence to Seán I O'Donoghue.

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The authors declare no competing financial interests.

Supplementary information

Supplementary texts and figures

Supplementary Figures 1–3 and Supplementary Methods (PDF 603 kb)

Supplementary Video 1

An introduction to using Aquaria (MP4 47683 kb)

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O'Donoghue, S., Sabir, K., Kalemanov, M. et al. Aquaria: simplifying discovery and insight from protein structures. Nat Methods 12, 98–99 (2015).

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