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Alessandro Di Domizio

Alessandro Di Domizio. I am an algorithm and software developer devoted to the development of innovative in silico technologies for drug R&D, with a special focus on protein-ligand molecular recognition phenomena. 

I graduated in Chemical Sciences (‘Computational Physical Chemistry’) in 2006 from the University of Milan, Italy, and in 2009 I obtained a PhD in Chemical Sciences (‘Computational Physical Chemistry’) from the University of Milano-Bicocca, Italy. I subsequently collaborated with the University of Milano-Bicocca and the University of Milan, Italy, working on projects concerning molecular recognition phenomena. From 2011 to 2013 I worked as a postdoc researcher at the ‘Institute of Chemistry of Molecular Recognition, National Research Council of Italy’. 

Over the last few years, in parallel to my teaching activity as an adjunct professor at the University of Milan, Italy (Master Degree Course in: ‘In silico methods in Toxicology’ and ‘Statistics’), I have founded SPILLOproject (, a research and consulting firm that provides unique and innovative drug R&D services focused on the in silico proteome-wide scale identification of drug target and off-target proteins. This technology has been successfully applied to many challenging problems and the results obtained have been experimentally validated and published in peer-reviewed scientific journals.

OpenTox 2022 Virtual Conference

SPILLO-PBSS: discovering target proteins of xenobiotics through 3D identification of their  (hidden) binding sites and experimental validations.  

Authors: Alessandro Di Domizio 1,* (Speaker), Alessandro Contini 2 


1. SPILLOproject, 20037 Paderno Dugnano, MI, Italy ( 2. Dipartimento Di Scienze Farmaceutiche, Università degli Studi di Milano, 20133 Milano, Italy 

The property of a drug to interact with multiple molecular targets is usually a major drawback  both in the drug development process, where off-target interactions often lead to safety-related  failures, and in medicine, where therapeutic agents often lead to side effects that can cause  dose limitation or even treatment discontinuation.  

SPILLOproject [1] developed innovative in silico technologies focused on the identification of  target and off-target proteins of any small molecule on a proteome-wide scale. Among them, the  SPILLO potential binding sites searcher (SPILLO-PBSS) software [2] is based on an innovative  structure-based approach with unique capabilities in identifying (often previously unknown)  binding sites, which can be detected even when hidden or completely closed, and therefore not  identifiable by traditional approaches (e.g., molecular docking simulations, QSAR, etc.). 

SPILLO-PBSS has been successfully applied to many challenging pharmacological problems,  such as providing biomolecular interpretations of some serious adverse effects of drugs (e.g.,  bortezomib, finasteride, paroxetine) on the market for many years. 

The top-ranked off-targets emerged from the systematic and unbiased analysis of the whole  available (from the RCSB Protein Data bank) structural proteome of Homo sapiens and other  organisms (i.e., Mus musculus and Rattus norvegicus) were well consistent with the reported  adverse effects of such drugs.  

Furthermore, the direct knowledge of the binding sites provided by the software has also allowed  further in-depth in silico studies through molecular dynamics (MD) simulations associated with  Nwat-MMGBSA analyses [3][4], to get more accurate and precise information on both stability  of the interactions and binding modes of the drugs within the newly discovered off-target  proteins. 

The results obtained so far have been experimentally confirmed in vitro, in vivo and/or by NMR  binding studies [5][6][7], highlighting the great potential of SPILLO-PBSS and its manifold  applications in the drug R&D, including (among others): i) identification of main targets; ii)  identification of off-targets responsible for adverse effects; iii) drug  rescue/repositioning/repurposing; iv) rational design of animal testing, in compliance with the  guidelines provided by the 3R principles. 


[1] SPILLOproject website: 

[2] SPILLO-PBSS: Detecting Hidden Binding Sites within Protein 3D-Structures Through a Flexible  Structure-Based Approach. J. Comput. Chem. (2014); DOI: 10.1002/jcc.23714 

[3] Improved Computation of Protein–Protein Relative Binding Energies with the Nwat-MMGBSA