SBVS | GHDDI's Free Structure based Prediction Service

To systematically assess the structure based model properties:

1. Please paste your SMILES list, Drug Name list or upload a file here. (example) Each query can handle 100 compounds at most.

DRUG_NAMES
SMILES

Select input file(*.csv,*.xls, *.xlsx)

Clear

2. Select 1 or more property category listed below.

Structure based (none-docking) AI model

3. Please upload a pdb file here.

protein pdb
pocket pdb + pocket center coordinate (x, y, z)

Select PDB file

4. Select the output report type.

Download predictive results as csv file
Show predictive results on the website

Model Documentation

Structure based (none-docking) AI model

The structure-based AI model was constructed based on GHDDI’s in-house developed HAG-net. The model is universal for all targets with 3D structures. The model was evaluated using the DUD.E benchmark set with an average AUC of 0.99; after removal of computer generated decoys, the model showed an average AUC of 0.945. The performance is based on 2 million protein-ligand interactions of over 185 protein targets. Given a target 3D structure, preferably the binding pocket with a radius of 15 Å, and screening library SMILES list as input, we are able to screen 14 million compounds per day on a single GPU, saving over 1000 times of computational cost compared to traditional docking tools. The model output is a probability distribution between 0 and 1 where a predicted value closer to 1 predicts a greater probability of docking.