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Yusuf Hamied Department of Chemistry

 

Professor Michele Vendruscolo

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

Transient interactions between the fuzzy coat and the cross-β core of brain-derived Aβ42 filaments
M Vendruscolo, M Milanesi, F Brotzakis
(2024)
(doi: 10.21203/rs.3.rs-3847495/v1)
Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity
RI Horne, J Wilson-Godber, A González Díaz, ZF Brotzakis, S Seal, RC Gregory, A Possenti, S Chia, M Vendruscolo
– J Chem Inf Model
(2024)
64,
590
(doi: 10.1021/acs.jcim.3c01777)
Transient interactions between the fuzzy coat and the cross-β core of brain-derived Aβ42 filaments
M Milanesi, F Brotzakis, M Vendruscolo
(2024)
(doi: 10.1101/2024.01.08.574772)
Aggregation of the Amyloid-β Peptide (Aβ40) within Condensates Generated through Liquid-Liquid Phase Separation
O Morris, Z Toprakcioglu, A Röntgen, M Cali, T Knowles, M Vendruscolo
(2023)
(doi: 10.1101/2023.12.23.573169)
Nanoscale profiling of evolving intermolecular interactions in ageing FUS condensates
A Miller, Z Toprakcioglu, S Qamar, P St. George-Hyslop, S Ruggeri, T Knowles, M Vendruscolo
(2023)
(doi: 10.1101/2023.12.21.572955)
Bayesian Optimization in the Latent Space of a Variational Autoencoder for the Generation of Selective FLT3 Inhibitors.
R Chandra, RI Horne, M Vendruscolo
– Journal of chemical theory and computation
(2023)
20,
469
(doi: 10.1021/acs.jctc.3c01224)
RASP: Optimal single fluorescent puncta detection in complex cellular backgrounds
B Fu, EE Brock, R Andrews, JC Breiter, R Tian, CE Toomey, J Lachica, T Lashley, M Ryten, NW Wood, M Vendruscolo, S Gandhi, LE Weiss, JS Beckwith, SF Lee
(2023)
(doi: 10.1101/2023.12.18.572148)
Sequence-based drug design using transformers
S Zhang, D Huo, R Horne, Y Qi, SP Ojeda, A Yan, M Vendruscolo
(2023)
(doi: 10.1101/2023.11.27.568880)
CryoENsemble - a Bayesian approach for reweighting biomolecular structural ensembles using heterogeneous cryo-EM maps
T Włodarski, J Streit, A Mitropoulou, L Cabrita, M Vendruscolo, J Christodoulou
(2023)
(doi: 10.1101/2023.11.21.567999)
Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
M Oeller, RJD Kang, HL Bolt, AL Gomes Dos Santos, AL Weinmann, A Nikitidis, P Zlatoidsky, W Su, W Czechtizky, L De Maria, P Sormanni, M Vendruscolo
– Nature Communications
(2023)
14,
7475
(doi: 10.1038/s41467-023-42940-w)
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Telephone number

01223 763873

Email address

mv245@cam.ac.uk

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