LLMs Meet Molecular Search

This is a TAMU CSCE670 project: LLMs Meet Molecular Search. We aim to asking LLMs to recommend molecules (via SMILES) with property queries.

Test Set

We randomly picked 50 molecular SMILES in QM9 dataset, and then referred to https://pubchem.ncbi.nlm.nih.gov for property labelling. The test set contains the SMILES, density, melting point, boiling point, solubility in water, vapor pressure, and functional group of the labelled molecules.

Demo

Please see demo.ipynb The input query includes properties of a molecular, and the output is recommended SMILES expressions, and a reference website.

Example:

Input Query: {'molecular weight': '55.08 g/mol', 'density': '772 mg/mL', 'melting point': '-91.8 C', 'boiling point': '97.2 C', 'vapor pressure': '40 mmHg', 'functional group': ['Primary Amine']}

Output:

1: CC(N)=O https://pubchem.ncbi.nlm.nih.gov/compound/178

2: CCC#N https://pubchem.ncbi.nlm.nih.gov/compound/7854 (This one is what we want.)

3: O=CC=O https://pubchem.ncbi.nlm.nih.gov/compound/7860

4: CCC#C https://pubchem.ncbi.nlm.nih.gov/compound/7846

5: CC(C)=O https://pubchem.ncbi.nlm.nih.gov/compound/180

6: NC(N)=O https://pubchem.ncbi.nlm.nih.gov/compound/1176

7: O=CC#N https://pubchem.ncbi.nlm.nih.gov/compound/3843063

8: C#CC#N https://pubchem.ncbi.nlm.nih.gov/compound/14055

9: CC1CC1 https://pubchem.ncbi.nlm.nih.gov/compound/11657

10: O=CC#C https://pubchem.ncbi.nlm.nih.gov/compound/12222

Experiment Results

We record the average running time and the top10 accuracy (in the prompt, we ask models to return 10 recommended molecules). GPT3.5 with RAG and additional rules outperform other method (0.36 top10 accuracy).