Shihang-Wang-58/DeepSA
A Deep-learning Driven Predictor of Compound Synthesis Accessibility
This tool helps drug discovery scientists quickly assess if a newly designed molecule is easy or difficult to synthesize in the lab. You provide a list of molecule structures (SMILES strings), and it tells you which ones are likely to be cost-effective to produce. This reduces the time and expense spent on synthesizing molecules that turn out to be impractical.
No commits in the last 6 months. Available on PyPI.
Use this if you are a medicinal chemist or drug discovery researcher needing to quickly filter a large list of computationally generated molecules based on their predicted synthesis feasibility.
Not ideal if you need to design synthetic routes or optimize reaction conditions for specific molecules, as it only predicts accessibility, not how to make them.
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40
Forks
9
Language
Python
License
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Category
Last pushed
Jun 06, 2025
Commits (30d)
0
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