Dear AMBER community,
I am currently using Amber24 to perform normal mode analysis (NMA) through MMPBSA.py on a large dataset of approximately 10⁵ structures. However, as NMA is CPU-dependent and not parallelized in the same manner as other components of the workflow, the calculations are turning out to be extremely time-consuming. I was wondering if there are any ways to accelerate this step, given the scale of the dataset. Specifically, I would appreciate any suggestions on how to efficiently handle such a large number of structures—whether through parallelization strategies, offloading the NMA portion outside of MMPBSA.py, or any best practices that have worked for similar large-scale analyses. Any guidance or recommendations would be highly appreciated.
Best regards,
Rahul Singal
Third-year UG Student
IIIT Hyderabad
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Received on Wed Jun 11 2025 - 00:00:02 PDT
