Author

Alessio Lodola

University of ParmaORCID 0000-0002-8675-1002Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Approach:simulation· 2 Approach:statistical model· 2 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Adrian John MulhollandiD· 2 shared A. Sofia F. OliveiraiD· 1 shared Callum D. OweniD· 1 shared Christopher John SchofieldiD· 1 shared Claire M. Strain-DamerelliD· 1 shared David R. GlowackiiD· 1 shared Deborah K. ShoemarkiD· 1 shared E. SalahiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBiochemistry

Adrian John MulhollandORCID

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2 papers

Recent·Most cited

Cancer-associated mutations reconfigure dynamical responses in EGFR kinase

Lorenzo Tulli, Alessio Lodola, Adrian John Mulholland, A. Sofia F. Oliveira

This study uses D-NEMD simulations to show how cancer mutations in EGFR alter allosteric communication networks and signal propagation within the kinase domain.

bioRxiv · Oct 9, 2026 · PreprintBiochemistry

Discovery of SARS-CoV-2 Mpro Peptide Inhibitors from Modelling Substrate and Ligand Binding

H. T. Henry Chan, Marc A. Moesser, Rebecca K. Walters, Tika R. Malla, Rebecca M. Twidale, Tobias John, Helen M. Deeks, Tristan Johnston-Wood, Victor A. Mikhailov, Richard Barry Sessions, William Dawson, E. Salah, Petra Lukacik, Claire M. Strain-Damerell, Callum D. Owen, , Garrett M. Morris

The paper models SARS-CoV-2 Mpro substrate and ligand binding to identify new inhibitor opportunities through computational analysis of binding interactions.

Chemical Science · Jan 1, 2021Peer-reviewedBioinformatics