About

Attilio Vittorio Vargiu earned his degree in Physics from the University of Cagliari, Italy, in 2003. He then pursued his doctoral studies at the International School of Advanced Studies (SISSA/ISAS) in Trieste, Italy, obtaining a Ph.D. in Statistical and Biological Physics in 2008. Following his Ph.D., he conducted post-doctoral research at various institutions, including the University of Cagliari, the Jacobs University of Bremen (Germany), and the University of California at Berkeley (USA). Between 2013 and 2017, Attilio held the position of Assistant Professor (untenured) in Applied Physics at the University of Cagliari. Subsequently, he undertook another post-doctoral fellowship at the Department of Chemistry of the Utrecht University in the Netherlands, lasting until 2019. In 2019, he returned to the University of Cagliari as a tenured Assistant Professor in Applied Physics. Since 2022, Attilio has been serving as an Associate Professor in the same University.

Research interests

Attilio’s research focuses on the computational simulation of biological macromolecules, peptides, small molecules, membranes, and their assemblies. His work leverages an array of sophisticated computational techniques, including quantum-based methods, all-atom and coarse-grained modeling, enhanced-sampling and machine-learning approaches. Primary areas of research include developing accurate methodologies and protocols for predicting complex protein-ligand structures, investigating bacterial antibiotic resistance mediated by multidrug transporters, and studying the self-assembly of chiral peptides with potential applications in technology and biomedicine.

Working with BioExcel

Attilio is a long-standing friend of the BioExcel network, having co-organized and spoken at the annual BioExcel Summer School on Biomolecular simulations (hosted at the Science and Technology Park of Sardinia) since 2016. He regularly employs GROMACS and HADDOCK software in various projects, predominantly within the framework of gEDES – a computational tool developed in his laboratory designed to enhance the accuracy of ligand-protein structure predictions. In perspective, Attilio plans to leverage the capabilities offered by pmx and biobb to further improve both the usability and predictive accuracy of gEDES.

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