guanjq/targetdiff
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
This project helps medicinal chemists and drug discovery scientists design new drug candidates by generating novel 3D molecule structures that are predicted to bind effectively to a specific protein target. You provide the 3D structure of a protein pocket, and the system outputs potential small molecule structures along with their predicted binding affinities. This is ideal for early-stage drug discovery when exploring new chemical entities.
324 stars. No commits in the last 6 months.
Use this if you need to generate new small molecule designs that are computationally optimized to fit into a specific protein binding pocket and predict their binding strength.
Not ideal if you already have a set of molecules and simply want to screen them against a target without generating new structures.
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324
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51
Language
Python
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Last pushed
Jan 10, 2024
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