  Developing complex biomolecular workflows is not always straightforward. It
requires tedious developments to enable the interoperability between the
different biomolecular simulation and analysis tools. Moreover, the need to
execute the pipelines on distributed systems increases the complexity of these
developments. To address these issues, we propose a methodology to simplify the
implementation of these workflows on HPC infrastructures. It combines a
library, the BioExcel Building Blocks (BioBBs), that allows scientists to
implement biomolecular pipelines as Python scripts, and the PyCOMPSs
programming framework which allows to easily convert Python scripts into
task-based parallel workflows executed in distributed computing systems such as
HPC clusters, clouds, containerized platforms, etc. Using this methodology, we
have implemented a set of computational molecular workflows and we have
performed several experiments to validate its portability, scalability,
reliability and malleability.
