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arXiv · 2509.00937

Parallelizing Drug Discovery: HPC Pipelines for Alzheimer's Molecular Docking and Simulation

Paul Ruiz Alliata·Diana Rubaga·Daniel Kumlin·Alberto Puliga
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Abstract

High-performance computing (HPC) is reshaping computational drug discovery by enabling large-scale, time-efficient molecular simulations. In this work, we explore HPC-driven pipelines for Alzheimer's disease drug discovery, focusing on virtual screening, molecular docking, and molecular dynamics simulations. We implemented a parallelised workflow using GROMACS with hybrid MPI-OpenMP strategies, benchmarking scaling performance across energy minimisation, equilibration, and production stages. Additionally, we developed a docking prototype that demonstrates significant runtime gains when moving from sequential execution to process-based parallelism using Python's multiprocessing library. Case studies on prolinamide derivatives and baicalein highlight the biological relevance of these workflows in targeting amyloid-beta and tau proteins. While limitations remain in data management, computational costs, and scaling efficiency, our results underline the potential of HPC to accelerate neurodegenerative drug discovery.

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Paul Ruiz Alliata, Diana Rubaga, Daniel Kumlin, Alberto Puliga. 2025-08-31. Parallelizing Drug Discovery: HPC Pipelines for Alzheimer's Molecular Docking and Simulation. https://arxiv.org/abs/2509.00937

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