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Overview This repository contains 48 structures predicted with AlphaFold 3, and 2 molecular dynamics trajectories, reported in the publication: "Enhancing PROTAC Ternary Complex Prediction with Ligand Information in AlphaFold 3" by Francisco Erazo, Nils Dunlop, Farzaneh Jalalypour, Rocío Mercado The accompanying code is available at: https://github.com/NilsDunlop/PROTACFold/. AlphaFold 3 Output Terms of Use By using this information, you agree to the AlphaFold 3 Output Terms of Use, found at: https://github.com/google-deepmind/alphafold3/blob/main/OUTPUT_TERMS_OF_USE.md. To request access to the AlphaFold 3 model parameters, follow the process outlined at: https://github.com/google-deepmind/alphafold3. You may only use these parameters if received directly from Google. Use is subject to terms of use available at: https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md. All-Atom Molecular Simulations In addition to the AlphaFold 3-predicted structures, this repository includes all-atom molecular simulations of the PROTAC ternary complex (PDB ID: 9B9W, AF3-predicted complex) using GROMACS with the Amber force field. Simulation Details Two independent 300 ns replicas (Rep1 and Rep2) Trajectory data saved at 5 ns intervals File Descriptions Replica 1 (Rep1) - 300 ns Simulation structure.gro → Structure file containing the entire system structure_complex.gro → Structure file containing the complex (excluding water and ions) Structure.tpr → Portable binary run input file Rep1.xtc → Trajectory file (excluding water and ions) Rep1.mov → QuickTime movie of the simulation Replica 2 (Rep2) - 300 ns Simulation structure.gro → Structure file containing the entire system structure_complex.gro → Structure file containing the complex (excluding water and ions) Structure.tpr → Portable binary run input file Rep2.xtc → Trajectory file (excluding water and ions) Rep2.mov → QuickTime movie of the simulation Contact Information For any inquiries regarding this dataset, please contact: rocio.mercado@chalmers.se.
protein structure prediction, PROTAC, generative AI, deep learning, targeted protein degradation, alphafold
protein structure prediction, PROTAC, generative AI, deep learning, targeted protein degradation, alphafold
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