ensECBS

ensECBS (ensemble Evolutionary Chemical Binding Similarity) is a software tool designed to improve chemical similarity searching by incorporating machine learning and evolutionary relationships of binding targets. The main features and functionalities of ensECBS are:

1. It defines chemical similarity based on the probability of chemical compounds binding to identical targets rather than just their shape similarity.

2. It integrates comprehensive and heterogeneous multiple target-binding chemical data into a paired data format.

3. The tool processes the data using multiple classification similarity-learning models considering various levels of target evolutionary information.

4. By encoding evolutionary information of binding targets to chemical compounds, ensECBS substantially expands the available chemical-target interaction data, significantly improving model performance.

5. The integrated model's output probability serves as a novel chemical similarity measure that effectively uncovers hidden chemical relationships.