An integrated machine learning approach delineates an entropic expansion mechanism for the binding of a small molecule to α-synuclein
Sneha Menon, Subinoy Adhikari, Jagannath Mondal, Rosana Collepardo, Sneha Menon, Subinoy Adhikari, Jagannath Mondal · 2024
Read An integrated machine learning approach delineates an entropic expansion mechanism for the binding of a small molecule to α-synuclein by Sneha Menon, Subinoy Adhikari, Jagannath Mondal, Rosana Collepardo, Sneha Menon, Subinoy Adhikari, Jagannath Mondal (2024) 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-11655066.txt.
Description
Sneha Menon, Subinoy Adhikari, and Jagannath Mondal use machine learning in 2024 to watch a small drug molecule change a shapeless protein. The protein is alpha-synuclein, which clumps in Parkinson's disease. It has no fixed shape and no pockets. Drug designers therefore struggle to grip it.
Training a neural network to tell apart the protein's shape ensembles, the team compared plain water with water holding the drug fasudil. The drug shifts the population of shapes. It expands the ensemble entropically rather than locking one pose. An expansion mechanism suggests a new way to think about drugging disordered proteins.
Catalog record
| CREATOR | Sneha Menon, Subinoy Adhikari, Jagannath Mondal, Rosana Collepardo, Sneha Menon, Subinoy Adhikari, Jagannath Mondal |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 159 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |