Mol-Zero-GAN: zero-shot adaptation of molecular generative adversarial network for specific protein targets†
Ravipas Aphikulvanich, Natapol Pornputtapong, Duangdao Wichadakul · 2023
Read Mol-Zero-GAN: zero-shot adaptation of molecular generative adversarial network for specific protein targets† by Ravipas Aphikulvanich, Natapol Pornputtapong, Duangdao Wichadakul (2023) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-10714197.txt.
Description
Ravipas Aphikulvanich, Natapol Pornputtapong, and Duangdao Wichadakul adapt a molecule-making AI to new protein targets with no extra data. Their twenty twenty-three paper tackles a hard drug discovery problem. Some targets have too little data to train a model from scratch.
Their framework, Mol-Zero-GAN, tunes a trained generator by reshaping its weights with singular value math. A smart search method, Bayesian optimization, finds the best settings. The aim is drug-like molecules that are easy to make and bind well to the target. Readers see a zero-shot path to candidates for targets that data-poor fields often skip.
Catalog record
| CREATOR | Ravipas Aphikulvanich, Natapol Pornputtapong, Duangdao Wichadakul |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |