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Claudio Mirabello

Principal Research Engineer, Docent

Publications

2025

Yury Zgadzay, Claudio Mirabello, George Wanes, Tomas Panek, Prashant Chauhan, Bjorn Nystedt, Alena Zikova, Paul C. Whitford, Ondrej Gahura, Alexey Amunts (2025) Mettl15-Mettl17 modulates the transition from early to late pre-mitoribosome Structure, Vol. 33, p. 1904-1915 (Article in journal) Continue to DOI

2024

Nessim Raouraoua, Claudio Mirabello, Thibaut Very, Christophe Blanchet, Björn Wallner, Marc F. Lensink, Guillaume Brysbaert (2024) MassiveFold: unveiling AlphaFold's hidden potential with optimized and parallelized massive sampling NATURE COMPUTATIONAL SCIENCE, Vol. 4, p. 824-828 (Article in journal) Continue to DOI
Claudio Mirabello, Björn Wallner (2024) DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules Bioinformatics, Vol. 40, Article btae586 (Article in journal) Continue to DOI
Inga Petersen, Ana Godec, Farahnaz Ranjbarian, Anders Hofer, Claudio Mirabello, Greta Hultqvist (2024) A charged tail on anti-a-Synuclein antibodies does not enhance their affinity to a-Synuclein fibrils PLOS ONE, Vol. 19, Article e0308521 (Article in journal) Continue to DOI
Johan Wallerstein, Xiao Han, Maria Levkovets, Dmitry Lesovoy, Daniel Malmodin, Claudio Mirabello, Bjoern Wallner, Renhua Sun, Tatyana Sandalova, Peter Agback, Goran Karlsson, Adnane Achour, Tatiana Agback, Vladislav Orekhov (2024) Insights into mechanisms of MALT1 allostery from NMR and AlphaFold dynamic analyses Communications Biology, Vol. 7, Article 868 (Article in journal) Continue to DOI

News

Two men in white lab coats with a computer in a lab.

Improving Alphafold to predict very large proteins

The AI tool Alphafold has been improved so that it can now predict the shape of very large and complex protein structures. Linköping University researchers have also succeeded in integrating experimental data into the tool.

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