ProteinTuneRL

Landajuela Larma, Mikel [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]; Lee, Chak Shing [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]; Hayes, ConorF [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]; Vashchenko, DenisV [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]

doi:10.11578/dc.20250821.1

DOE OSTI · code-161321

ProteinTuneRL

Landajuela Larma, Mikel [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]·Lee, Chak Shing [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]·Hayes, ConorF [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]·Vashchenko, DenisV [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]

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Abstract

ProteinTuneRL is a framework designed to harness the power of reinforcement learning for advanced protein design. The project enables fine-tuning of generative models to explore and optimize protein sequences with tailored structural and functional properties.

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Landajuela Larma, Mikel [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)], Lee, Chak Shing [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)], Hayes, ConorF [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)], Vashchenko, DenisV [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]. 2025-03-14. ProteinTuneRL. https://doi.org/10.11578/dc.20250821.1

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