Tunable and Portable Extreme-Scale Drug Discovery Platform at Exascale: the LIGATE Approach

Autor: Palermo, Gianluca, Accordi, Gianmarco, Gadioli, Davide, Vitali, Emanuele, Silvano, Cristina, Guindani, Bruno, Ardagna, Danilo, Beccari, Andrea R., Bonanni, Domenico, Talarico, Carmine, Lunghini, Filippo, Martinovic, Jan, Silva, Paulo, Bohm, Ada, Beranek, Jakub, Krenek, Jan, Jansik, Branislav, Crisci, Luigi, Biagio, Cosenza, Thoman, Peter, Salzmann, Philip, Fahringer, Thomas, Alexander, Leila, Tauriello, Gerardo, Schwede, Torsten, Durairaj, Janani, Emerson, Andrew, Ficarelli, Federico, Wingbermuhle, Sebastian, Lindahl, Eric, Gregori, Daniele, Sana, Emanuele, Coletti, Silvano, Gschwandtner, Philip
Rok vydání: 2023
Předmět:
Druh dokumentu: Working Paper
DOI: 10.1145/3587135.3592172
Popis: Today digital revolution is having a dramatic impact on the pharmaceutical industry and the entire healthcare system. The implementation of machine learning, extreme-scale computer simulations, and big data analytics in the drug design and development process offers an excellent opportunity to lower the risk of investment and reduce the time to the patient. Within the LIGATE project, we aim to integrate, extend, and co-design best-in-class European components to design Computer-Aided Drug Design (CADD) solutions exploiting today's high-end supercomputers and tomorrow's Exascale resources, fostering European competitiveness in the field. The proposed LIGATE solution is a fully integrated workflow that enables to deliver the result of a virtual screening campaign for drug discovery with the highest speed along with the highest accuracy. The full automation of the solution and the possibility to run it on multiple supercomputing centers at once permit to run an extreme scale in silico drug discovery campaign in few days to respond promptly for example to a worldwide pandemic crisis.
Comment: Paper Accepted to the 20th ACM International Conference on Computing Frontiers (CF'23)
Databáze: arXiv
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