Padmanabhan Group – Molecular and systems medicine

Our group uses a combination of computational and quantitative experimentation techniques including:

• Cell cultures: Primary mouse neurons and non-neuronal cells such as neuroblastoma cells
• Animal models: Mouse models of Alzheimer’s disease
• Super-resolution microscopy techniques: sptPALM, uPAINT and dSTORM
• Biochemical methods: Western blotting, PCR, and ELISA
• Mathematical modelling: Quantitative systems pharmacology, pharmacokinetics, pharmacometrics, viral dynamics, hidden Markov modelling, and systems biology and network modelling

Group Leader

• Dr Pranesh Padmanabhan

Students

• Mr Jonathan Lee

• The potential of ultrasound and antibodies for Alzheimer’s disease therapy (4 March 2024)
• NHMRC awards $43 million in four new grants (18 December 2023)
• Should we be using mice to study Alzheimer’s disease? (31 May 2023)
• Tau hot spots open new avenues of discovery into dementia (13 September 2022)
• New mathematical model predicts the effectiveness of COVID-19 vaccines (15 March 2022)
• Mathematical model created by Queensland researcher set to speed up development of future COVID-19 vaccines (15 March 2022)
• How drug combinations could help fight COVID-19 (16 December 2020)

View full list of publications on eSpace

Selected publications

• Single‐molecule imaging reveals Tau trapping at nanometer‐sized dynamic hot spots near the plasma membrane that persists after microtubule perturbation and cholesterol depletion

Padmanabhan, Pranesh, Kneynsberg, Andrew, Cruz, Esteban, Amor, Rumelo, Sibarita, Jean‐Baptiste and Götz, Jürgen (2022). Single‐molecule imaging reveals Tau trapping at nanometer‐sized dynamic hot spots near the plasma membrane that persists after microtubule perturbation and cholesterol depletion. The EMBO Journal, 41 (19) e111265, 1-16. doi: 10.15252/embj.2022111265

• Modeling how antibody responses may determine the efficacy of COVID-19 vaccines

  Padmanabhan, Pranesh, Desikan, Rajat and Dixit, Narendra M. (2022). Modeling how antibody responses may determine the efficacy of COVID-19 vaccines. Nature Computational Science, 2 (2), 123-131. doi: 10.1038/s43588-022-00198-0

• Super-resolution microscopy: a closer look at synaptic dysfunction in Alzheimer disease

  Padmanabhan, Pranesh, Kneynsberg, Andrew and Götz, Jürgen (2021). Super-resolution microscopy: a closer look at synaptic dysfunction in Alzheimer disease. Nature Reviews Neuroscience, 22 (12), 723-740. doi: 10.1038/s41583-021-00531-y

• Targeting TMPRSS2 and Cathepsin B/L together may be synergistic against SARS-CoV-2 infection

  Padmanabhan, Pranesh, Desikan, Rajat and Dixit, Narendra M. (2020). Targeting TMPRSS2 and Cathepsin B/L together may be synergistic against SARS-CoV-2 infection. PLoS Computational Biology, 16 (12) e1008461, e1008461. doi: 10.1371/journal.pcbi.1008461

• Frontotemporal dementia mutant Tau promotes aberrant Fyn nanoclustering in hippocampal dendritic spines

  Padmanabhan, Pranesh, Martínez-Mármol, Ramón, Xia, Di, Götz, Jürgen and Meunier, Frédéric A. (2019). Frontotemporal dementia mutant Tau promotes aberrant Fyn nanoclustering in hippocampal dendritic spines. eLife, 8 e45040. doi: 10.7554/elife.45040

• Axon growth regulation by a bistable molecular switch

  Padmanabhan, Pranesh and Goodhill, Geoffrey J. (2018). Axon growth regulation by a bistable molecular switch. Proceedings of the Royal Society of London B: Biological Sciences, 285 (1877) 20172618, 20172618. doi: 10.1098/rspb.2017.2618

• Inhibitors of hepatitis C virus entry may be potent ingredients of optimal drug combinations

  Padmanabhan, Pranesh and Dixit, Narendra M. (2017). Inhibitors of hepatitis C virus entry may be potent ingredients of optimal drug combinations. Proceedings of the National Academy of Sciences, 114 (23), E4524-E4526. doi: 10.1073/pnas.1704531114

• Emergent properties of the interferon-signalling network may underlie the success of hepatitis C treatment

  Padmanabhan, Pranesh, Garaigorta, Urtzi and Dixit, Narendra M. (2014). Emergent properties of the interferon-signalling network may underlie the success of hepatitis C treatment. Nature Communications, 5 (1) 3872, 1-9. doi: 10.1038/ncomms4872

• Mathematical model of viral kinetics in vitro estimates the number of E2-CD81 complexes necessary for hepatitis C virus entry

  Padmanabhan, Pranesh and Dixit, Narendra M. (2011). Mathematical model of viral kinetics in vitro estimates the number of E2-CD81 complexes necessary for hepatitis C virus entry. PLoS Computational Biology, 7 (12) e1002307, e1002307-e1002307. doi: 10.1371/journal.pcbi.1002307