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


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


Emanuele Scalone


PhD Student


Roja Shampuri


MS Student

Federico Ballabio


MS Student

Shadi Asadian Ghahfarokhi


MS Student

Scientific Programmes


Protein Dynamics

Protein Misfolding and Aggregation

hERG potassium channels' enhancers



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.


Structural and functional characterization of hERG potassium channels' enhancers (Telethon GGP19134)


The goal of this research is to test the hypothesis that small molecules that enhance the rapid component of the delayed rectifier current IKr in cardiac cells are able to rescue the phenotype in three severe variants of Long QT Syndrome (LQTS) caused by loss of function mutations in the HERG gene that encodes for the KV11.1 potassium channels that conducts IKr current (LQT2). We will apply state of the art technology to understand the relationship between structure and function and identify the binding pose of the compounds exploiting the recently resolved cryo-EM structure of the HERG channel in the open state. We will model the structure of the closed state of the channel and provide insight to our collaborators on how to improve the design of the compounds. Thanks to Telethon foundation and in collaboration with Silvia Priori at Maugeri and Giovanni Lentini at the University of Bari we will be able to perform a through assessment of a selection of the most powerful molecules previously reported in the literature and of novel molecules developed within this project. We will therefore test six compounds in: 1) human induced pluripotent stem cells (hiPSC)-derived cardiac myocytes from carriers of different pathogenic mutations, 2) guinea-pig models of LQT2 and LQT3 and 3) in a knock-in swine model of LQT8 that we have recently developed.




Last update 09/09/20

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.