Medicinal Computational Chemistry. Coordinator: Recanatini

Our research is focused on the application and development of various in silico tools, mainly based on computational chemistry/biology and network science, with the aim of rationalizing and predicting the properties and characteristics of molecular systems of pharmaceutical interest.

Research themes 

- Application and development of simulation methods based on Molecular Dynamics: our research group has a consolidated experience in the use of advanced simulation methods, both atomistic and multiscale, and enhanced sampling.
- Docking and Virtual-Screening Studies: our research group routinely uses Docking and Virtual Screening methods to accelerate the process of identifying and developing bioactive molecules.
- Analysis of interaction networks for the study and identification of new targets and new biologically active compounds: a new line of research is focused on the use of Network Science for the prediction of ligand-target associations and the study of target systems

Lab Members

Maurizio Recanatini: group Coordinator. Write to Maurizio Recanatini, or visit his page.
Andrea Cavalli. Write to Andrea Cavalli, or visit his page.
Matteo Masetti. Write to Matteo Masetti, or visit his page.
Riccardo Ocello. Write to Riccardo Ocello.

Federico Falchi
Chiara Cabrelle
Luca Menestrina

Stefano Bosio

Internship projects:

2 x year

Significant publications

  • Menestrina L, Cabrelle C, Recanatini M. (2021) "COVIDrugNet: a network-based web tool to investigate the drugs currently in clinical trial to contrast COVID-19." Sci Rep. 11:19426. doi: 10.1038/s41598-021-98812-0
  • Ocello R, Furini S, Lugli F, Recanatini M, Domene C, Masetti M. (2020) "Conduction and Gating Properties of the TRAAK Channel from Molecular Dynamics Simulations with Different Force Fields." J Chem Inf Model. 60:6532-6543. doi: 10.1021/acs.jcim.0c01179
  • Recanatini M, Cabrelle C. (2020) "Drug Research Meets Network Science: Where Are We?" J Med Chem. 63:8653-8666. doi: 10.1021/acs.jmedchem.9b01989
  • Bernetti M, Masetti M, Recanatini M, Amaro RE, Cavalli A. (2020) "An Integrated Markov State Model and Path Metadynamics Approach To Characterize Drug Binding Processes." J Chem Theory Comput. 15:5689-5702. doi: 10.1021/acs.jctc.9b00450
  • Masetti M, Berti C, Ocello R, Di Martino GP, Recanatini M, Fiegna C, Cavalli A. (2016) "Multiscale Simulations of a Two-Pore Potassium Channel." J Chem Theory Comput. 12:5681-5687. doi: 10.1021/acs.jctc.6b00972