LogBB_Pred

Blood-Brain Barrier Permeablility (LogBB) Predictor

Conventional experimental approaches for blood-brain barrier (BBB) permeability measurement are expensive, time-consuming, and labor-intensive. Thus, accurate prediction of BBB permeability of a compound is a major challenge in neurotherapeutic drug discovery. We developed a logBB prediction model (LogBB_Pred) using a large dataset for practical applications. This model can be used for compound screening in early stage of brain drug discovery. This web server works on Chrome, Firefox, and Opera.

Blood-Brain Barrier Permeablility (LogBB) Predictor

Conventional experimental approaches for blood-brain barrier (BBB) permeability measurement are expensive, time-consuming, and labor-intensive. Thus, accurate prediction of BBB permeability of a compound is a major challenge in neurotherapeutic drug discovery. We developed a logBB prediction model (LogBB_Pred) using a large dataset for practical applications. This model can be used for compound screening in early stage of brain drug discovery. This web server works on Chrome, Firefox, and Opera.

Server Submission
LogBB_Pred accepts compounds in SMILES format (Simplified Molecular-Input Line-Entry System). Please submit a single compound in SMILES or submit a file containing multiple compounds in SMILES. Examples: CCCCCC, CCCC, CCCC
Input SMILES: or Submit .SMI File:

Citation: Shaker. B., Lee. J., Lee. Y., et al. A machine learning-based quantitative model (LogBB_Pred) to predict the blood-brain barrier permeability (logBB value) of drug compounds, Bioinformatics, btad577 (2023)

Bug reports: blisszen [at] cau.ac.kr

Dataset used for LogBB_Pred model is available at: http://ssbio.cau.ac.kr/software/logbb_pred/dataset.zip

The 2D structure of query compound is generated using SmileDrawer tool. https://doi.org/10.1021/acs.jcim.7b00425

School of integrative engineering
Chung-Ang University, Korea