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Yusuf Hamied Department of Chemistry

 

Professor of Biophysics

Our research

In the last 15 years our research has been focused on the development of methods of characterising the structure, dynamics and interactions of proteins in previously inaccessible states. These methods are based on the use of experimental data, in particular from nuclear magnetic resonance spectroscopy, as structural restraints in molecular dynamics simulations. Through this approach it is possible to obtain information about a variety of protein conformations, as for example those populated during the folding process, and about protein interactions in complex environments, including those generating aggregate species that are associated with neurodegenerative disorders such as Alzheimer's and Parkinson's diseases.

Application to neurodegenerative diseases

More recently, these studies have led us to investigate the physico-chemical principles of proteins homeostasis and their application to the development of therapeutic strategies against neurodegenerative diseases. Starting from the observation that proteins are expressed in the cell at levels close to their solubility limits, we are developing approaches to prevent or delay misfolding disorders based on the enhancement of our quality control mechanisms against protein aggregation.

Watch Professor Vendruscolo discuss his research

Take a tour of the Una Finlay Laboratory in the Centre for Misfolding Diseases

Publications

Endogenous metabolites rescue a C. elegans model of Alzheimer's disease by triggering a heat shock response
P Joshi, M Perni, R Limbocker, B Mannini, S Casford, S Chia, J Labbadia, C Dobson, M Vendruscolo
– FEBS OPEN BIO
(2019)
9,
225
Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation
JM Kirkpatrick, EK Sacramento, M Mazzetto, S Di Sanzo, C Caterino, A Bartolome, M Sanguanini, N Papaevgeniou, M Lefaki, D Childs, E Terzibasi-Tozzini, N Romanov, M Baumgart, W Huber, N Chondrogianni, M Vendruscolo, A Cellerino, A Ori
– MOLECULAR & CELLULAR PROTEOMICS
(2019)
18,
S35
In vitro and in silico Activity of Iridoids Against Leishmania amazonensis.
MH Vendruscolo, GM das Neves, LP Kagami, LC Rodrigues Junior, ML Nunes Diehl, SCB Gnoatto, SA de Loreto Bordignon, PRT Romão, VL Eifler-Lima, GL von Poser
– Curr Drug Discov Technol
(2019)
16,
173
RNA Granules Hitchhike on Lysosomes for Long-Distance Transport, Using Annexin A11 as a Molecular Tether
Y-C Liao, M Fernandopulle, G Wang, H Choi, L Hao, CM Drerup, S Qamar, J Nixon-Abell, Y Shen, W Meadows, M Vendruscolo, T Knowles, M Nelson, M Czekalska, G Musteikyte, R Patel, C Stephens, A Pasolli, L Forrest, PS George-Hyslop, J Lippincott-Schwartz, ME Ward
(2019)
Stabilization and Characterization of Cytotoxic Aβ40 Oligomers Isolated from an Aggregation Reaction in the Presence of Zinc Ions
B Mannini, J Habchi, S Chia, FS Ruggeri, M Perni, TPJ Knowles, CM Dobson, M Vendruscolo
– ACS Chemical Neuroscience
(2018)
9,
2959
A tau homeostasis signature is linked with the cellular and regional vulnerability of excitatory neurons to tau pathology
H Fu, A Possenti, R Freer, Y Nakano, NC Hernandez Villegas, M Tang, PVM Cauhy, BA Lassus, S Chen, SL Fowler, HY Figueroa, ED Huey, GVW Johnson, M Vendruscolo, KE Duff
– Nature Neuroscience
(2018)
22,
47
Identifying A- and P-site locations on ribosome-protected mRNA fragments using Integer Programming
N Ahmed, P Sormanni, P Ciryam, M Vendruscolo, C Dobson, E O’Brien
(2018)
490755
Determination of Structural Ensembles of Proteins: Restraining vs Reweighting.
R Rangan, M Bonomi, GT Heller, A Cesari, G Bussi, M Vendruscolo
– Journal of chemical theory and computation
(2018)
14,
6632
Bayesian Weighing of Electron Cryo-Microscopy Data for Integrative Structural Modeling
M Bonomi, S Hanot, CH Greenberg, A Sali, M Nilges, M Vendruscolo, R Pellarin
– Structure
(2018)
27,
175
Automated Behavioral Analysis of Large C. Elegans Populations Using a Wide Field-of-view Tracking Platform
M Perni, S Casford, FA Aprile, EA Nollen, TPJ Knowles, M Vendruscolo, CM Dobson
– Journal of Visualized Experiments
(2018)
2018,
ARTN e58643
(doi: 10.3791/58643)
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Research Interest Groups

Telephone number

01223 763873

Email address

mv245@cam.ac.uk