The overall objective of our research is to understand the principles governing protein homeostasis - the ability of cells to generate and regulate the levels of proteins in terms of conformations, interactions, concentrations and cellular localisation.

By adopting the strategy of analysing the origins of specific diseases to inform us about normal biology, we have set up an interdisciplinary programme that involves bringing together methods and concepts from chemistry, physics, engineering, genetics and medicine. We are using a combination of in vitro, in silico and in vivo approaches to study protein homeostasis through the analysis of the effects that result from its alteration in a select group of specific proteins, from either amino acid mutations, or changes in concentration and solubility, or the interactions with other molecules. This programme is generating new insights into the mechanism through which physical and chemical sciences can address biological questions in order to understand the normal behaviour of living systems. In addition it is increasing our understanding of the nature and consequences of the failure to maintain homeostasis, which is associated with such phenomena as ageing and neurodegenerative disorders.


Statistical mechanics of the denatured state of a protein using replica-averaged metadynamics. J. Am. Chem. Soc. 136, 8982-8991 (2014).

The characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process.

Widespread aggregation and neurodegenerative diseases are associated with supersaturated proteins. Cell Reports 5, 781-790 (2013).

The maintenance of protein solubility is a fundamental aspect of cellular homeostasis because protein aggregation is associated with a wide variety of human diseases. Numerous proteins unrelated in sequence and structure, however, can misfold and aggregate, and widespread aggregation can occur in living systems under stress or aging. A crucial question in this context is why only certain proteins appear to aggregate readily in vivo, whereas others do not. We identify here the proteins most vulnerable to aggregation as those whose cellular concentrations are high relative to their solubilities. We find that these supersaturated proteins represent a metastable subproteome involved in pathological aggregation during stress and aging and are overrepresented in biochemical processes associated with neurodegenerative disorders. Consequently, such cellular processes become dysfunctional when the ability to keep intrinsically supersaturated proteins soluble is compromised. Thus, the simultaneous analysis of abundance and solubility can rationalize the diverse cellular pathologies linked to neurodegenerative diseases and aging.


d2D: Determination of secondary structure populations in disordered states of proteins using NMR chemical shifts.

C. Camilloni, A. De Simone, W. Vranken and M. Vendruscolo. Biochemistry 51, 2224-2231 (2012).


Zagg+CamP: Prediction of the aggregation propensity of proteins from their folded states.

G. G. Tartaglia, A. P. Pawar, S. Campioni, F. Chiti, C. M. Dobson and M. Vendruscolo. J. Mol. Biol. 380, 425-436 (2008)


Networks in Cell Biology

M. Buchanan, G. Caldarelli, P. De Los Rios, F. Rao and M. Vendruscolo (Eds). Cambridge University Press, Cambridge (2010).