931:
868:
782:
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1005:
446:
279:
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218:(HTS). HTS enables the rapid identification of active compounds. For example, virtual screening can be used as an early stage of the drug discovery pipeline to evaluate the interactions between large datasets of small molecules and a drug target, identifying potential hit candidates. This approach helps in identifying potential hit candidates by predicting how different compounds will bind to the target protein, which will go further in the experimental validation.
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Marconi machine, with a total of 10 PetaFLOPS. The ANTAREX project, which stands for AutoTuning and
Adaptivity appRoach for Energy efficient eXascale HPC systems, emphasized auto-tuning and energy efficiency of HPC applications, making them more effective in various research scenarios, including drug
2178:
Nicastri, Emanuele; Marinangeli, Franco; Pivetta, Emanuele; Torri, Elena; Reggiani, Francesco; Fiorentino, Giuseppe; Scorzolini, Laura; Vettori, Serena; Marsiglia, Carolina; Gavioli, Elizabeth Marie; Beccari, Andrea R.; Terpolilli, Giuseppe; De Pizzol, Maria; Goisis, Giovanni; Mantelli, Flavio (June
2095:
Nicastri, Emanuele; Marinangeli, Franco; Pivetta, Emanuele; Torri, Elena; Reggiani, Francesco; Fiorentino, Giuseppe; Scorzolini, Laura; Vettori, Serena; Marsiglia, Carolina; Gavioli, Elizabeth Marie; Beccari, Andrea R.; Terpolilli, Giuseppe; De Pizzol, Maria; Goisis, Giovanni; Mantelli, Flavio (June
991:
The project's large-scale campaign results are available through the MEDIATE (MolEcular DockIng AT homE) platform. The objective of MEDIATE is to collect a chemical library of Sars-COV-2 inhibitors. The MEDIATE portal provides access to a set of small molecules that research can use to start
1353:
Iaconis, Daniela; Bordi, Licia; Matusali, Giulia; Talarico, Carmine; Manelfi, Candida; Cesta, Maria
Candida; Zippoli, Mara; Caccuri, Francesca; Bugatti, Antonella; Zani, Alberto; Filippini, Federica; Scorzolini, Laura; Gobbi, Marco; Beeg, Marten; Piotti, Arianna (25 May 2022).
286:
The
Exscalate4Cov project followed the ANTAREX4ZIKA project, both of which aimed to leverage HPC for drug discovery, albeit targeting different viruses. While Exscalate4Cov focused on the SARS-CoV-2 virus responsible for COVID-19, ANTAREX4ZIKA was dedicated to addressing the
2045:
Vistoli, Giulio; Manelfi, Candida; Talarico, Carmine; Fava, Anna; Warshel, Arieh; Tetko, Igor V.; Apostolov, Rossen; Ye, Yang; Latini, Chiara; Ficarelli, Federico; Palermo, Gianluca; Gadioli, Davide; Vitali, Emanuele; Varriale, Gaetano; Pisapia, Vincenzo (3 August 2023).
836:(Ligand Generator) is one of the main components of the platform, and it is used to perform molecular docking and scoring simulations. LiGen is responsible for generating and evaluating the conformations of ligands. Another relevant component at the same level is the
1039:
The project's results also captured national interest in Italy, highlighted by various newspaper articles, due to the use of
Italian supercomputers during the pandemic. Additionally, the large-scale campaign results gained attention from international journals.
879:
against 70 billion molecules from the EXSCALATE chemical library. In
November 2020, consortium members coordinated one of the largest virtual screening campaigns, harnessing the combined computational power of two supercomputers totaling 81 PFLOPS.
2153:
974:. Hence, repurposing existing drugs with established safety and toxicology profiles provides a significant advantage by saving time in identifying potential new treatments. During the European Exscalate4Cov project activities,
828:
assesses the interaction strength between each ligand's pose and the protein. The pipeline ultimately produces a ranking of hit compounds as its output, indicating the most promising candidates for further investigation.
1232:
Gadioli, Davide; Vitali, Emanuele; Ficarelli, Federico; Latini, Chiara; Manelfi, Candida; Talarico, Carmine; Silvano, Cristina; Cavazzoni, Carlo; Palermo, Gianluca; Beccari, Andrea
Rosario (1 January 2023).
1035:
The experiments, including the discovery of raloxifene as a possible drug candidate against COVID-19, gained significant interest from the scientific community, as documented in several scientific articles.
938:
Another critical aspect of the experiment was data storage management. The platform leveraged efficient MPI I/O operations to handle multi-node computations. The input data required 3.3 TB of space in
2236:
1829:
Gadioli, Davide; Palermo, Gianluca; Cherubin, Stefano; Vitali, Emanuele; Agosta, Giovanni; Manelfi, Candida; Beccari, Andrea R.; Cavazzoni, Carlo; Sanna, Nico; Silvano, Cristina (January 2021).
901:, each node consists of 1 Intel Xeon Gold 6252 24C CPU (24 cores, 48 threads) and 4 NVIDIA V100 GPUs with 16 GB of VRAM. The machine consists of 1820 nodes, providing a total of 51.7 PFLOPS.
2262:
1291:
Allegretti, Marcello; Cesta, Maria
Candida; Zippoli, Mara; Beccari, Andrea; Talarico, Carmine; Mantelli, Flavio; Bucci, Enrico M.; Scorzolini, Laura; Nicastri, Emanuele (January 2022).
2288:
942:
format. However, SMILES data needed to be expanded in a pre-processing step involving 100 nodes over five days. Similarly, the post-processing step involved 19 nodes over five days.
891:, each node consists of 1 IBM POWER9 AC922 CPU (32 cores, 128 threads) and 4 NVIDIA V100 GPUs with 16 GB of VRAM. The machine consists of 970 nodes, providing a total of 29.3 PFLOPS.
240:
to accelerate the discovery of effective treatments for the coronavirus. By utilizing high-throughput virtual screening, Exscalate4Cov aimed to find faster solutions to the crisis.
225:
scenario, such as a pandemic, where time to solution is critical, virtual screening is used to identify hit molecules for the latter stages of the drug discovery pipeline, such as
694:
1023:
experiments, the E4C project identified raloxifene as a possible candidate to treat early-stage COVID-19 patients, aiming to prevent clinical progression. In
October 2020,
2181:"A phase 2 randomized, double-blinded, placebo-controlled, multicenter trial evaluating the efficacy and safety of raloxifene for patients with mild to moderate COVID-19"
2098:"A phase 2 randomized, double-blinded, placebo-controlled, multicenter trial evaluating the efficacy and safety of raloxifene for patients with mild to moderate COVID-19"
1907:
Vitali, Emanuele; Ficarelli, Federico; Bisson, Mauro; Gadioli, Davide; Accordi, Gianmarco; Fatica, Massimiliano; Beccari, Andrea R.; Palermo, Gianluca (1 April 2024).
2154:"EXSCALATE4COV: Italian Medicines Agency (AIFA) authorizes Raloxifene Clinical Trial for Paucisymptomatic Covid-19 Patients treated at Home and in Medical Facilities"
304:
The
Exscalate4Cov consortium of public-private entities has been coordinated by Dompè, and it involved 17 other institutions, from research centers to universities.
930:
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978:
was selected through a combined approach of drug repurposing and in-silico screening on SARS-CoV-2 target’s proteins, followed by subsequent in-vitro screening.
2315:
2369:
Gadioli, D.; et al. (July 2022), "EXSCALATE: An
Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2",
954:
files containing scores for each input ligand, occupying 69 TB. The resulting dataset, containing 570 million hit compounds, is freely available.
1562:
Yang, Yanqing; Zhu, Zhengdan; Wang, Xiaoyu; Zhang, Xinben; Mu, Kaijie; Shi, Yulong; Peng, Cheng; Xu, Zhijian; Zhu, Weiliang (18 January 2021).
233:. The Exscalate4Cov project was initiated after the COVID-19 pandemic outbreak. This project aimed to leverage the computational power of
910:
The large-scale campaign used a reservation of 800 Marconi100 nodes and 1500 HP5 nodes for 60 hours. Achieving an average throughput was
2399:
Beccari, A.; et al. (September 2022), "Exscalate4CoV: Innovative High Performing Computing (HPC) Strategies to Tackle Pandemic Crisis",
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2482:
2456:
1813:
1540:
744:
642:
1235:"EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2"
2341:
1868:
Vitali, Emanuele; Gadioli, Davide; Palermo, Gianluca; Beccari, Andrea; Cavazzoni, Carlo; Silvano, Cristina (July 2019).
851:
acceleration to take advantage of supercomputer's GPUs. The CUDA version has undergone various optimizations, including
1764:
668:
590:
1870:"Exploiting OpenMP and OpenACC to accelerate a geometric approach to molecular docking in heterogeneous HPC nodes"
1909:"GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis"
534:
432:
2565:
98:
1995:
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1027:
authorized clinical trials to treat COVID-19 patients, and it is currently undergoing testing for approval.
269:
Fast sharing of data and scientific discoveries with the community to work in an urgent computing scenario.
291:. The ANTAREX4ZIKA project concluded at the end of 2018 and involved a virtual screening campaign on the
203:. The goal is to find compounds that interact with the targets, leading to potential therapeutic effects.
1356:"Characterization of raloxifene as a potential pharmacological agent against SARS-CoV-2 and its variants"
1120:"EXaSCale smArt pLatform Against paThogEns for Corona Virus | EXSCALATE4CoV Project | Fact Sheet | H2020"
482:
248:
Exscalate4Cov's approach involved screening billions of compounds against various protein targets of the
1971:"HPC5 - PowerEdge C4140, Xeon Gold 6252 24C 2.1GHz, NVIDIA Tesla V100, Mellanox HDR Infiniband | TOP500"
966:
experiments. Drug repurposing offers an interesting approach to address unmet clinical needs in case of
562:
121:
113:
1908:
2047:
844:
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can be a long and costly process, often taking years and requiring substantial financial investment.
2048:"MEDIATE - Molecular DockIng at homE: Turning collaborative simulations into therapeutic solutions"
1024:
188:
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2555:
2550:
508:
332:
1624:"Exscalate4CoV: Innovative High Performing Computing (HPC) Strategies to Tackle Pandemic Crisis"
951:
616:
1564:"Ligand-based approach for predicting drug targets and for virtual screening against COVID-19"
1412:
380:
1461:
Kulkarni, V. S.; Alagarsamy, V.; Solomon, V. R.; Jose, P. A.; Murugesan, S. (1 April 2023).
324:
135:
1521:
Wildey, Mary Jo; Haunso, Anders; Tudor, Matthew; Webb, Maria; Connick, Jonathan H. (2017),
260:
Identify potential drug candidates against the coronavirus to combat the COVID-19 pandemic;
2316:"Supercomputer Research Leads to Human Trial of Potential COVID-19 Therapeutic Raloxifene"
8:
1956:
1831:"Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App"
1792:
Markidis, Stefano; Gadioli, Davide; Vitali, Emanuele; Palermo, Gianluca (November 2021).
406:
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Develop a computer-aided drug design platform that leverages supercomputer capabilities;
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2493:
The Drug Repurposing Strategy in the Exscalate4CoV Project: Raloxifene Clinical Trials
1869:
1794:"Understanding the I/O Impact on the Performance of High-Throughput Molecular Docking"
1293:"Repurposing the estrogen receptor modulator raloxifene to treat SARS-CoV-2 infection"
1182:
875:
The project's main experiment evaluated the interactions between 12 viral proteins of
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1183:"SOCIETAL CHALLENGES - Health, demographic change and well-being | Programme | H2020"
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1527:, Annual Reports in Medicinal Chemistry, vol. 50, Elsevier, pp. 149–195,
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To hinge the computational power offered by HPC centers, the docking platform uses
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2020:
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1996:"UG3.2: MARCONI100 UserGuide - SCAI - User Support - CINECA Technical Portal"
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817:
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Conduct a large-scale experiment as an example for future pandemic scenarios;
237:
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1157:
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At the software level, the project utilizes the EXSCALATE docking platform.
206:
2432:
2263:"Covid: Aifa, ok a test su Raloxifene in casi lievi - Altre news - Ansa.it"
2222:
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2289:"Coronavirus, il supercomputer italiano scopre terapia con 'raloxifene'"
2237:"Exscalate, il super software che scopre le molecole contro il Covid-19"
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2021 IEEE/ACM Sixth International Parallel Data Systems Workshop (PDSW)
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249:
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101:
2441:
The High-Performance Computing Resources for the EXSCALATE4CoV Project
1563:
1131:
2495:, SpringerBriefs in Applied Sciences and Technology, pp. 19–26,
2443:, SpringerBriefs in Applied Sciences and Technology, pp. 27–34,
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experiments, identifying a potentially effective molecule against
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library, which facilitates scaling across multi-node and cores.
804:
EXSCALATE Docking Pipeline, at different levels of abstractions.
30:
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2094:
1049:
939:
888:
859:, and other techniques, to enhance performance and efficiency.
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809:
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143:
SOCIETAL CHALLENGES - Health, demographic change and well-being
120:
pandemic. The project utilized high-throughput, extreme-scale,
86:
1463:"Drug Repurposing: An Effective Tool in Modern Drug Discovery"
695:
Lazzaro Spallanzani National Institute for Infectious Diseases
1957:"EXSCALATE4COV: 60 ORE DI SUPERCALCOLO CONTRO IL CORONAVIRUS"
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Therefore, the process of finding new drugs usually involves
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EXaSCale smArt pLatform Against paThogEns for Corona Virus
2535:
2342:"Osteoporosis Drug Shows Promise in Fighting Coronavirus"
1684:
898:
824:
stage that generates potential ligand conformations, a
458:
International Institute of Molecular and Cell Biology
2469:, SpringerBriefs in Applied Sciences and Technology,
1520:
1622:
Beccari, Andrea R.; Vistoli, Giulio (January 2022).
816:
of the virtual screening campaign, specifically the
1411:Berdigaliyev, Nurken; Aljofan, Mohamad (May 2020).
1410:
2371:IEEE Transactions on Emerging Topics in Computing
1239:IEEE Transactions on Emerging Topics in Computing
676:Scientific and technological research, education
624:Scientific and technological research, education
598:Scientific and technological research, education
440:Scientific and technological research, education
414:Scientific and technological research, education
388:Scientific and technological research, education
138:and involved 17 participants. It was part of the
2542:
2438:
1561:
256:with the target. The project's objectives were:
2464:
1413:"An Overview of Drug Discovery and Development"
2490:
2398:
1621:
2368:
1913:Journal of Parallel and Distributed Computing
996:drug design from a reduced set of molecules.
862:
2401:International Journal of Molecular Sciences
1628:International Journal of Molecular Sciences
1015:is a known chemical compound used to treat
808:Inputs at the application level consist of
130:The Exsclate4Cov project, which stands for
820:in the case of Exscalate4Cov. Following a
151:The project conducted one of the largest
29:
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2129:
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1924:
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962:The Exscalate4Cov project also conducted
1685:"Exscalate | AI Drug Discovery Platform"
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929:
866:
799:
277:
205:
175:
2313:
1467:Russian Journal of Bioorganic Chemistry
252:virus, identifying those with a higher
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745:Istituto Nazionale di Fisica Nucleare
643:SIB Swiss Institute of Bioinformatics
2340:Writer, Aila Slisco (18 June 2020).
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2314:Peckham, Oliver (29 October 2020).
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16:EU research project (2020 to 2021)
14:
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1275:
1200:
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1101:
669:KTH Royal Institute of Technology
2491:Beccari, A.; et al. (May 2023),
2439:Emerson, A.; et al. (May 2023),
2052:Expert Opinion on Drug Discovery
1297:Cell Death & Differentiation
812:from the chemical space and the
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591:University of Naples Federico II
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1555:
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535:Barcelona Supercomputing Center
433:Katholieke Universiteit, Leuven
1765:"ANTAREX: Project Description"
1404:
1175:
950:The final output consisted of
945:
1:
2269:(in Italian). 27 October 2020
2064:10.1080/17460441.2023.2221025
1874:The Journal of Supercomputing
1835:The Journal of Supercomputing
1095:
1008:Raloxifene chemical structure
999:
905:
883:The supercomputers used are:
299:
171:
2465:Coletti, S.; et al. (2023),
2243:(in Italian). 8 October 2021
2197:10.1016/j.eclinm.2022.101450
2114:10.1016/j.eclinm.2022.101450
1806:10.1109/PDSW54622.2021.00007
1187:CORDIS | European Commission
1124:CORDIS | European Commission
195:, which they test against a
87:https://www.exscalate4cov.eu
7:
2502:10.1007/978-3-031-30691-4_3
2449:10.1007/978-3-031-30691-4_4
1568:Briefings in Bioinformatics
1533:10.1016/bs.armc.2017.08.004
1043:
795:
483:Elettra Sincrotrone Trieste
116:(HPC) as a response to the
10:
2582:
2295:(in Italian). 19 June 2020
1935:10.1016/j.jpdc.2023.104819
1886:10.1007/s11227-019-02875-w
1847:10.1007/s11227-020-03295-x
1417:Future Medicinal Chemistry
1372:10.1038/s41419-022-04961-z
1309:10.1038/s41418-021-00844-6
986:
981:
863:Virtual screening campaign
180:Virtual screening pipeline
166:
122:computer-aided drug design
114:high-performance computing
2475:10.1007/978-3-031-30691-4
2383:10.1109/TETC.2022.3187134
1524:High-Throughput Screening
1479:10.1134/S1068162023020139
1251:10.1109/TETC.2022.3187134
216:high-throughput screening
210:High-throughput screening
127:to conduct experiments.
82:
74:
63:
55:
47:
37:
28:
23:
2025:mediate.exscalate4cov.eu
1714:mediate.exscalate4cov.eu
1360:Cell Death & Disease
887:Marconi100: Operated by
847:to scale multi-node and
563:Forschungszentrum JĂĽlich
243:
189:Pharmaceutical companies
1800:. IEEE. pp. 9–14.
749:Public research center
720:Associtazione Big Data
699:Research Organisations
647:Public research center
567:Public research center
539:Public research center
513:Research Organisations
509:Fraunhofer-Gesellschaft
487:Research Organisations
461:Public research center
357:Public research center
333:Pharmaceutical industry
191:have large datasets of
1009:
935:
872:
805:
617:University of Cagliari
283:
211:
181:
112:, aimed at leveraging
2566:Horizon 2020 projects
2526:Exscalate4Cov Website
2414:10.3390/ijms231911576
1641:10.3390/ijms231911576
1429:10.4155/fmc-2019-0307
1007:
933:
870:
803:
381:Politecnico di milano
281:
209:
179:
134:, was coordinated by
1740:"Exscalate Projects"
1162:www.exscalate4cov.eu
2241:Corriere della Sera
1580:10.1093/bib/bbaa422
934:Data storage system
914:ligands per second
407:University of Milan
24:Exscalate4Cov (E4C)
1021:drug repositioning
1010:
964:drug repositioning
958:Drug repositioning
936:
918:on Marconi100 and
873:
806:
673:Public university
621:Public university
595:Public university
437:Public university
411:Public university
385:Public university
325:Dompé Farmaceutici
284:
212:
193:chemical compounds
182:
157:drug repositioning
136:Dompé Farmaceutici
2536:EXSCALATE Webpage
2512:978-3-031-30690-7
2484:978-3-031-30690-7
2458:978-3-031-30690-7
2185:eClinicalMedicine
2102:eClinicalMedicine
1815:978-1-6654-1837-9
1542:978-0-12-813069-8
1132:10.3030/101003551
1090:Virtual screening
1055:COVID-19 pandemic
1019:. As a result of
822:molecular docking
793:
792:
274:Previous projects
227:lead optimization
153:virtual screening
108:program from the
104:supported by the
92:
91:
59:30 September 2021
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2363:Further readings
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1880:(7): 3374–3396.
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1819:
1789:
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1761:
1755:
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1750:
1744:www.exscalate.eu
1736:
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1697:
1695:
1681:
1672:
1671:
1661:
1643:
1619:
1610:
1609:
1599:
1574:(2): 1053–1064.
1559:
1553:
1552:
1551:
1549:
1518:
1509:
1508:
1498:
1458:
1449:
1448:
1408:
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1179:
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968:urgent computing
786:
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783:
762:
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759:
752:Research center
736:
734:
733:
712:
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686:
684:
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660:
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650:Research center
634:
632:
631:
608:
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582:
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579:
554:
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526:
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516:Research center
500:
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490:Research center
474:
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464:Research center
450:
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424:
422:
421:
398:
396:
395:
372:
370:
369:
344:
342:
341:
307:
306:
254:binding affinity
223:urgent computing
201:protein receptor
145:founding funding
33:
21:
20:
2581:
2580:
2576:
2575:
2574:
2572:
2571:
2570:
2541:
2540:
2531:E4C Cordis page
2522:
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2256:
2246:
2244:
2235:
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2176:
2172:
2162:
2160:
2152:
2151:
2147:
2093:
2089:
2043:
2039:
2029:
2027:
2019:
2018:
2014:
2004:
2002:
1994:
1993:
1989:
1979:
1977:
1969:
1968:
1964:
1955:
1954:
1950:
1905:
1901:
1866:
1862:
1827:
1823:
1816:
1790:
1783:
1773:
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1620:
1613:
1560:
1556:
1547:
1545:
1543:
1519:
1512:
1459:
1452:
1423:(10): 939–947.
1409:
1405:
1351:
1342:
1289:
1276:
1230:
1201:
1191:
1189:
1181:
1180:
1176:
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1156:
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1146:
1136:
1134:
1118:
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1102:
1098:
1046:
1033:
1031:Public interest
1002:
989:
984:
960:
948:
928:
908:
897:: Operated by
865:
798:
781:
779:
757:
755:
731:
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629:
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469:
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419:
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393:
391:
367:
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339:
337:
302:
276:
246:
174:
169:
17:
12:
11:
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2579:
2569:
2568:
2563:
2561:Bioinformatics
2558:
2556:Supercomputing
2553:
2551:Drug discovery
2539:
2538:
2533:
2528:
2521:
2520:External links
2518:
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2087:
2058:(8): 821–833.
2037:
2012:
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1975:www.top500.org
1962:
1948:
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1860:
1841:(1): 841–869.
1821:
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1199:
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1085:Supercomputing
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110:European Union
106:Horizon Europe
99:public-private
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78:Project Closed
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2467:Exscalate4CoV
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2158:www.dompe.com
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2000:wiki.u-gov.it
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818:spike protein
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310:Organization
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2345:
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2319:
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2297:. Retrieved
2292:
2283:
2271:. Retrieved
2267:Agenzia ANSA
2266:
2257:
2245:. Retrieved
2240:
2231:
2188:
2184:
2173:
2161:. Retrieved
2157:
2148:
2105:
2101:
2090:
2073:2434/1009370
2055:
2051:
2040:
2028:. Retrieved
2024:
2015:
2003:. Retrieved
1999:
1990:
1978:. Retrieved
1974:
1965:
1951:
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1873:
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1772:. Retrieved
1768:
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1747:. Retrieved
1743:
1717:. Retrieved
1713:
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1692:. Retrieved
1688:
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1567:
1557:
1546:, retrieved
1523:
1470:
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1420:
1416:
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1300:
1296:
1242:
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1190:. Retrieved
1186:
1177:
1165:. Retrieved
1161:
1135:. Retrieved
1123:
1070:Horizon 2020
1038:
1034:
1017:osteoporosis
1011:
993:
990:
961:
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937:
926:Data storage
919:
915:
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770:Chelonia SA
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183:
150:
146:
142:
140:Horizon 2020
131:
129:
94:
93:
51:1 April 2020
18:
2424:2434/943376
2377:: 170–181,
946:Output data
871:GPUs system
788:Switzerland
662:Switzerland
296:discovery.
197:drug target
118:coronavirus
2545:Categories
2191:: 101450.
2108:: 101450.
1926:2209.05069
1919:: 104819.
1366:(5): 498.
1096:References
1080:Raloxifene
1013:Raloxifene
1000:Raloxifene
976:raloxifene
920:2000 lig/s
906:Throughput
877:SARS-CoV-2
300:Consortium
289:Zika virus
250:SARS-CoV-2
199:, often a
172:Background
161:SARS-CoV-2
102:consortium
67:2 970 875
2205:2589-5370
2122:2589-5370
2082:1746-0441
1943:0743-7315
1894:0920-8542
1855:0920-8542
1769:www.up.pt
1650:1422-0067
1588:1467-5463
1487:1608-330X
1437:1756-8919
1380:2041-4889
1317:1476-5403
1269:2168-6750
1158:"Science"
972:pandemics
970:, due to
922:on HPC5.
702:Hospital
316:Industry
2433:36232873
2346:Newsweek
2223:35582123
2140:35582123
1668:36232873
1606:33461215
1505:36852389
1445:32270704
1398:35614039
1335:34404919
1044:See also
838:libdpipe
796:Pipeline
773:Company
723:Company
329:Private
319:Country
125:software
48:Launched
2320:HPCwire
2214:9098200
2179:2022).
2163:10 July
2131:9098200
2096:2022).
1774:10 July
1659:9569893
1597:7929377
1548:11 July
1496:9945820
1389:9130985
1326:8370058
1065:EuroHPC
994:de-novo
987:Mediate
982:Results
916:(lig/s)
853:OpenACC
810:ligands
584:Germany
528:Germany
452:Belgium
167:Context
83:Website
64:Funding
38:Country
2509:
2481:
2455:
2431:
2351:9 July
2325:9 July
2299:9 July
2273:9 July
2247:9 July
2221:
2211:
2203:
2138:
2128:
2120:
2080:
2030:9 July
2021:"Home"
2005:9 July
1980:9 July
1941:
1892:
1853:
1812:
1749:9 July
1719:9 July
1710:"Home"
1694:9 July
1666:
1656:
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1493:
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1386:
1378:
1333:
1323:
1315:
1267:
1192:9 July
1167:9 July
1137:9 July
1050:CINECA
940:SMILES
889:CINECA
857:OpenMP
776:Other
761:
735:
726:Other
711:
688:Sweden
685:
633:
607:
581:
553:
525:
499:
476:Poland
473:
449:
423:
397:
371:
353:CINECA
343:
293:CINECA
221:In an
97:was a
75:Status
56:Closed
1921:arXiv
834:LiGen
764:Italy
738:Italy
714:Italy
636:Italy
610:Italy
556:Spain
502:Italy
426:Italy
400:Italy
374:Italy
346:Italy
313:Type
244:Scope
2507:ISBN
2479:ISBN
2453:ISBN
2429:PMID
2353:2024
2327:2024
2301:2024
2275:2024
2249:2024
2219:PMID
2201:ISSN
2165:2024
2136:PMID
2118:ISSN
2078:ISSN
2032:2024
2007:2024
1982:2024
1939:ISSN
1890:ISSN
1851:ISSN
1810:ISBN
1776:2024
1751:2024
1721:2024
1696:2024
1664:PMID
1646:ISSN
1602:PMID
1584:ISSN
1550:2024
1537:ISBN
1501:PMID
1483:ISSN
1441:PMID
1433:ISSN
1394:PMID
1376:ISSN
1331:PMID
1313:ISSN
1265:ISSN
1194:2024
1169:2024
1139:2024
1075:HPC5
1025:AIFA
912:2400
895:HPC5
849:CUDA
229:and
163:.
155:and
2497:doi
2471:doi
2445:doi
2419:hdl
2409:doi
2387:hdl
2379:doi
2209:PMC
2193:doi
2126:PMC
2110:doi
2068:hdl
2060:doi
1931:doi
1917:186
1882:doi
1843:doi
1802:doi
1654:PMC
1636:doi
1592:PMC
1576:doi
1529:doi
1491:PMC
1475:doi
1425:doi
1384:PMC
1368:doi
1321:PMC
1305:doi
1255:hdl
1247:doi
1128:doi
952:CSV
899:Eni
845:MPI
2547::
2505:,
2477:,
2451:,
2427:,
2417:,
2405:23
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2344:.
2318:.
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2239:.
2217:.
2207:.
2199:.
2189:48
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