Computational Structural Biology Lab

 

In the Computational Structural Biology lab we use computer simulations to study bio-molecular processes. We apply and develop integrative structural and dynamical biology methods where we combine experimental data, bio-informatics data and physicochemical knowledge to provide multi-resolution models of biomolecules in motion.

 

We try to understand how the conformational dynamics of biological molecules can modulate biological processes. We study the role played by conformational disorder in protein function and disfunction; the mechanisms underlying conformational changes and their role in signalling processes; the mechanisms of  protein folding and misfolding and their link with protein degradation and aggregation and the mechanisms of protein-NA recognition and interaction. By using computer modelling we aim at finding general rules for these mechanisms and use them to design and propose experiments to modulate specific biological processes.

 

Carlo Camilloni, PhD

 

Associate Professor

carlo.camilloni@unimi.it

 

CV, GoogleScholar, Lab site

Selected Publications

Bonomi, M., Heller, G. T., Camilloni, C., & Vendruscolo, M. (2017). Principles of protein structural ensemble determination. Current Opinion in Structural Biology. [PubMed: 28063280]

 

 

Hultqvist, G., Aberg, E., Camilloni, C., Sundell, G. N., Andersson, E., Dogan, J., et al. (2017). Emergence and evolution of an interaction between intrinsically disordered proteins. eLife. [PubMed: 28398197]

 

Camilloni, C., Sala, B. M., Sormanni, P., Porcari, R., Corazza, A., De Rosa, M., et al. (2016). Rational design of mutations that change the aggregation rate of a protein while maintaining its native structure and stability. Scientific Reports. [PubMed: 27150430]

 

Cabrita, L. D., Cassaignau, A. M. E., Launay, H. M. M., Waudby, C. A., Wlodarski, T., Camilloni, C., et al. (2016). A structural ensemble of a ribosome-nascent chain complex during cotranslational protein folding. Nature Structural & Molecular Biology. [PubMed: 26926436]

 

Camilloni, C., Sahakyan, A. B., Holliday, M. J., Isern, N. G., Zhang, F., Eisenmesser, E. Z., & Vendruscolo, M. (2014). Cyclophilin A catalyzes proline isomerization by an electrostatic handle mechanism. Proceedings of the National Academy of Sciences of the United States of America. [PubMed: 24982184]

Current Group

Cristina Paissoni

 

Postdoctoral Researcher

cristina.paissoni@unimi.it

 

Emanuele Scalone

 

PhD Student

emanuele.scalone@unimi.it

 

Roja Shampuri

 

MS Student

Federico Ballabio

 

MS Student

Scientific Programmes

ISDB

Protein Dynamics and Molecular Recognition

Protein Folding, Misfolding and Aggregation

ISDB

 

Modelling the structure and dynamics of biomolecular systems requires the integration of multiple sources of knowledge. Experiments can generally provide accurate structural information and lower resolution indication about the dynamics of a system. Molecular simulations can provide high-resolution dynamics with limitations in its accuracy. We develop theoretical and computational tools to integrate experimental information in molecular dynamics simulations thus enabling high-resolution characterization of both structure and dynamics.

 

Protein Dynamics and Molecular Recognition

 

Proteins move, fluctuate around their native ground state and exchange among low populated excited states. Such substates can be exploited to facilitate the binding between proteins, proteins and nucleic acids or other molecules. This behaviour is particularly evident in the case of disordered proteins that by lacking a specific tertiary structure exchange continuously among a large number of weakly populated states. We use molecular modelling to characterise protein dynamics and correlate it with functional and thermodynamic features.  We are currently studying  the role of dynamics in the inflammatory processes mediated by linear-poly-ubiquitination, the role of dynamics in protein-RNA binding, the role of disorder in protein recognition and binding.

 

Protein Folding, Misfolding and Aggregation

 

How protein fold and how they fail are key questions to shed light on protein aggregation. We are interested in shedding light on the determinants of successful folding as well as of aberrant aggregation of folded and intrinsically disordered proteins. We are currently studying systemic amyloidosis from light chain antibodies, beta-2-microglobulin and type-2 diabetes. Furthermore we always try push the boundaries for the use of MD simulations in understanding protein folding.

 

Last update 07/12/19

The Structural Biology Group comprises members from both the DBS-UNIMI and the IBF-CNR. The content herein is not regulated by the University of Milan.