High performance heterogeneous computing: Application in rational drug design Computación heterogénea de alta performance: Aplicación en el diseño racional de fármacos

BLANCO, RAMIRO; CHINESTRAD, PATRICIO; MENNA, PABLO LORENZANO; ZINNI, MARÍA ALEJANDRA; SAFAR, FÉLIX

2020 IEEE Congreso Bienal de Argentina, ARGENCON 2020 - 2020 IEEE Biennial Congress of Argentina, ARGENCON 2020

Institute of Electrical and Electronics Engineers Inc.

Año: 2020

This work presents an interdisciplinary end-to-end development applied to the computer-based rational design of drugs, in a context of heterogeneous high-performance computing. For that end it integrates the ARM big.LITTLE and Intel/AMD x64 architectures, the construction of an efficient cluster (UNQ-Cluster), and the addition of external computing power through a distributed virtual datacenter scheme, interconnected by means of VPNs. As the docking platform, the open Autodock Vina software is adopted, parallelizing over the CPU cores. The scheme is completed with a master-slave process manager, called Molecular Sniper, and the Sniper Sight web application, for the configuration of tasks, management of results, and statistics, both being own and open developments. As an application case, it is presented the search for candidate compounds for the preliminary design of potentially beneficial drugs to block the entry of the Covid-19 virus into the human cell. Ultimately, the development of an ad-hoc database of almost 350 thousand compounds along with the experimental computational docking performance for this application are described.