Enabling HPC-Accelerated Virtual Screening for Drug Discovery through the LEXIS Platform
Abstract
High-performance computing (HPC) plays a vital role in modern drug discovery, enabling large-scale virtual screening campaigns that evaluate millions of protein–ligand interactions. However, deploying and managing such workflows on HPC systems remains challenging due to complex software environments, nonstandardized configurations, and limited accessibility for non-expert users. These factors not only limit the broader adoption of HPC in early-stage drug discovery but also highlight the need for scalable and accessible workflows for a wider research community. Building on the workflow concepts demonstrated in LIGATE and leveraging the capabilities of the LEXIS Platform, we extended these developments within the AVITHRAPID project to deploy a LiGen-based virtual screening workflow on the Karolina supercomputer at IT4Innovations, featuring a custom, flexible, and ergonomic user interface that simplifies access to virtual screening. The LEXIS Platform unifies workflow orchestration, data management, and federated user access across supercomputing resources. LiGen is an advanced in silico simulator optimized for HPC environments. Our solution provides both an ergonomic graphical and command-line interfaces for configuring, submitting, and monitoring large-scale virtual screening tasks. It enables reproducible, containerized execution and secure federated access for researchers across multiple institutions. This implementation simplifies the use of supercomputing resources, reduces manual configuration effort, lowers the entry barrier for new users, and supports scalable, high-throughput studies in drug discovery while applicable to other scientific domains.
Fields of Study & Subjects
Scientific Computing and Data Management
Computational Drug Discovery Methods
Distributed and Parallel Computing Systems
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 10 February 2026
- Language
- EN