Success Story: The most advanced center of competence aimed at fighting the coronavirus by combining the best supercomputing resources, and AI up to clinical validation.

NCC presenting the success story

The real exploitation of HPC platform such as Marconi100 (CINECA) and HPC5 (ENI) allowed to apply Computational-Aided Drug Design technologies during Phase 1 of the project, leading to the fast virtual identification of known drugs (repurposing). After the experimental validations, the most promising one, the Raloxifene, is in clinical trials in three EU countries. Given the ongoing health emergency, we have pushed the best hardware and software technologies to the extreme, performing, in the Phase 2, the largest virtual screening experiment ever carried out. More than 70 billion molecules will be simulated on the 15 active interaction sites of the virus for a total of more than a thousand billion interactions evaluated in just 60 hours. This will be possible thanks to the simultaneous availability of the computing power (81 petaflops: millions of billions of operations per second) of Eni’s HPC5, the most powerful industrial supercomputer in the world, of CINECA’s Marconi100, and the virtual screening software accelerated by the Politecnico di Milano and Cineca, and the Exscalate molecular library from Dompé.

This result confirms the real possibility of exploiting HPC platforms in cases of pandemics. Also, during the project precious web platforms to support the global research community with bioinformatics and simulation tools were deployed, including MEDIATE – MolEcular DockIng AT home ( – will give free access to the largest database available today on the Sars-CoV-2 Virus both from a structural (three-dimensional structures) and functional (proteins interacting with human cells) point of view. In, the viral mutations retrieved using genomic data from public repositories (i.e. GISAID, EMBL COVID-19 data portal) are mapped and analysed in their 3D structural context to investigate their impact in terms of host-immune interaction, ligand/substrate/drug binding sites and SDPs; The other web portal is, that aims to provide the scientific community with structural information on emerging variants involving the protein sequence of the Sars-CoV-2 Spike protein; The other impressive release will be, a website that include MD trajectories retrieved worldwide and analysis tools to better understand the dynamic behaviour of viral proteins. 


Exscalate4CoV, using a unique combination of high performance computing power and AI with biological processing, brings together 18 partners and further 15 associated members. This includes supercomputing centres in Italy, Spain and Germany, large research centres, pharmaceutical companies and biological institutes from across Europe. The platform has around 120 Petaflops computing power, allowing research into the behaviors of molecules with the aim of identifying an effective treatment against coronavirus. The project’s chemical library is constantly growing thanks to agreements with newly associated pharmaceutical companies.

The consortium has virtually tested 400 000 molecules using its supercomputers. 7 000 molecules were preselected and further tested “in vitro”. Raloxifene emerged as a promising molecule: according to the project, it is effective in blocking the replication of the virus in cells, and could thus hold up the progression of the disease. Researchers have indicated that its advantages include its high patient tolerability, safety and established toxicological profile. The consortium is discussing with the European Medicines Agency how to advance to clinical trials to evaluate the new potential use for Raloxifene. If successful, the drug could be quickly made available in high volumes and at low cost.

Industrial Organisations Involved:

The supercomputing centers Eni, CINECA (Italy), BSC (Spain) and Jülich (Germany) performed the molecular dynamics simulations of viral proteins and the ultra-fast virtual screening of the E4C library. The University of Milan and the Politecnico di Milano were engaged respectively in supporting the virtual screening activity and in accelerating the computational process. Results from the virtual screening led to the selection of active compounds tested in phenotypic screening phase at the KU Leuven research infrastructure through a multiparameter high throughput screening platform on live pathogens at high (level 3) or unknown biosafety risk. The Fraunhofer Institute for Molecular Biology and Applied Ecology (IME) have integrated phenotypic screening with the biochemical assay on targets of different putative viruses through access to the Fraunhofer BROAD Repurposing Library. The University of Cagliari ran the biological evaluation by defining the mechanism of action of inhibitors and the selection of mutants in systems. This information was crucial to define the genetic barriers of potential drugs, selecting more promising molecules to develop. The Elettra Synchrotron Trieste and the International Institute of Molecular and Cellular Biology produced the Xray structures for the most interesting viral enzymes and related inhibitors supporting the rational design of new chemical structures able to inhibit Corona viruses. The Medical Chemistry team of the University of Naples Federico II supported the EXSCALATE team in the selection of the best compounds, as well as dealing with the chemical synthesis of the best candidates. The National Institute for Infectious Diseases Lazzaro Spallanzani was the reference centre for the clinical trials activated by the consortium.

Technical/scientific Challenge:

The E4C project addresses a globally unmet societal and medical need: is there an infrastructure/operating workflow which might help in quickly identifying existing drugs or novel NCE in case of a pandemic outbreak? We think that E4C had a high societal importance, under these premises. The project addressed the issues related to public health as well. Virus epidemics are one of the most serious issues of health in the world which need to be transacted. This project targets issues related to public health. Virus epidemics are one of the most serious health issues in the world which need to be transacted and the growth in the number of infected cases detected and fatality rapidly alarming the world. Using a solid scientific method was critical for bringing this outbreak under control.

A private-public consortium aimed to develop a realistic and fast operational workflow to tackle this aspect of scientific answer to pandemic cases was certainly of impact. The parallel and integrated effort in structural biology, biochemistry, and cellular biology to identify old drug (repurposing) and novel NCEs with high synthetic feasibility has been coupled, in unprecedented way, to the provided IT technology with the ambition to as quick as possible deliver validated candidate drugs to public health officers (EMA) and operators (hospitals).


Summarizing, the benefits of E4C was twofold: to identify molecules capable of targeting the new coronavirus (SARS-CoV2) and to develop a tool effective for countering future pandemics. More specifically, E4C aims to:

  • Establish a sustainable example for a rapid scientific answer to any future pandemic scenario. The model leverages a rapid and effective High Performance Computing platform for the generation and analysis of 3D models and experimental 3D X-ray structures of protein targets from pandemic pathogens.
  • Drive a fast virtual identification of known drugs (repurposing) or proprietary/commercial candidate molecules to be further experimentally characterized.
  • Define a workflow scheme for biochemical and cellular screening test to validate the candidate molecules in previous points and assure, through phenotypic and genomic assays;
  • Prepare, together with EMA, a development plan for successful candidates for direct “first-in-human” studies or for further testing in animals for bridging studies.
  • Identify SARS-CoV-2 genomic regions involved in host adaptation, pathogenicity and mutations.


  • EXSCALATE4CoV, COVID-19, coronavirus, supercomputing, SARS-CoV-2, virus, Raloxifene, AI

This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation program and Germany, Bulgaria, Austria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, the United Kingdom, France, the Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro