Molecular Mechanics Poisson-Boltzmann Surface Area on Cloud Computing

Following our widely explored repository “𝗠𝗼𝗹𝗲𝗰𝘂𝗹𝗮𝗿 𝗗𝘆𝗻𝗮𝗺𝗶𝗰𝘀 𝗼𝗻 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴” and its pre-print, we’re introducing a workflow designed for Google Colab and HPC/Jupyter systems (environments without a GUI) to run GMX_MMPBSA (𝙈𝙤𝙡𝙚𝙘𝙪𝙡𝙖𝙧 𝙈𝙚𝙘𝙝𝙖𝙣𝙞𝙘𝙨 𝙋𝙤𝙞𝙨𝙨𝙤𝙣–𝘽𝙤𝙡𝙩𝙯𝙢𝙖𝙣𝙣 𝙎𝙪𝙧𝙛𝙖𝙘𝙚 𝘼𝙧𝙚𝙖)!

Molecular dynamics (MD) simulations help us see how biological molecules behave in motion, revealing mechanisms behind drug binding, protein folding, and key processes that drive life at the molecular level. After MD simulations, binding free energy estimation is a critical step, and GMX_MMPBSA remains one of the most widely used tools for that. This GitHub repository enables faster, parallelized (MPI) free energy calculations and smooth transition from MD simulations to post-analysis, significantly reducing total simulation time.

GitHub: https://github.com/karagol-taner/gmx_MMPSA_conda_Jupyter_colab

bioRxiv Link: Karagöl, T., & Karagöl, A. (2024). Benchmarking GROMACS on Optimized Colab Processors and the Flexibility of Cloud Computing for Molecular Dynamics. bioRxiv, 2024-11.

Thanks to the developers of GROMACS and GMX_MMPBSA, and to the growing community of researchers advancing molecular simulations on both cloud and HPC environments!

(Image: Karagöl et al. Pharm Res, 2024)