Background: Why Optimize TPSA?
The Ascent Bio model leverages deep learning and transformer-based methods to map molecular structures and SMILES sequences to properties like TPSA, logP, and more. Trained on datasets with millions of molecular variations, the model captures intricate relationships between structure and properties. It recommends precise, property-specific modifications while maintaining molecular integrity and drug-like characteristics.More about TPSA
Step-by-Step Guide: Using the Ascent Bio API to Optimize TPSA
Step 1: Define Your Starting Molecule
Start by identifying your molecule using its SMILES notation, e.g.,"CC(=O)OC1=CC=CC=C1C(=O)O"
. This molecule (acetylsalicylic acid, as just an example) serves as input to the API for TPSA optimization. Knowing the baseline TPSA value can help set realistic goals for adjustment.
Step 2: Specify TPSA as the Target Property
Configure the API request to optimize TPSA:"target_props": ["TPSA"]
: Specifies TPSA as the target property."target_changes": [1]
: Indicates increasing TPSA (use[-1]
to decrease it).
- To enhance solubility, increase TPSA with
"target_changes": [1]
. - For better membrane permeability, decrease TPSA with
"target_changes": [-1]
.