AI Algorithm and Applications in Drug Design
Overview
LSCCB has developed the AI algorithm (EDKT) to predict the bioactivity of potential small molecule drug. Our models demonstrate prediction accuracy comparable to state-of-the-art methods and high-throughput experiments. Additionally, we have established an AI-driven generative chemistry protocol, which includes EDKT to select the most promising drug molecules for development.
Problem addressed
Accurate and rapid bioactivity prediction has historically been a significant challenge in drug design. With the AI-driven molecular generation tools and the design of synthetic accessible compound libraries, the ability to extrapolate bioactivity prediction to novel chemical structures has become even more crucial for novel drug design.
Innovation
- Our method capitalizes on the rapidly increasing volume of data and advancements in deep learning models
- We have tested different molecular representations to achieve more accurate predictions
Key impact
- Prediction accuracy comparable to state-of-the-art methods and high-throughput experiments
- Our method offers the unique advantage of uncertainty quantification, which has been demonstrated in some application cases
Application
- Prediction of bioactivity for low molecular weight drug molecules, virtual screening
Laboratory for Synthetic Chemistry and Chemical Biology (LSCCB) is an R&D centre funded by Health@InnoHK progamme of Innovation and Technology Commission of HKSAR. Established in 2020, LSCCB is operated with tripartite joint collaboration of The University of Hong Kong, Imperial College London and Peking University. LSCCB aims at integrating chemical and biomedical sciences to develop new molecular medicines and diagnostic tools for the treatment and analysis of human diseases, in particular, cancer. LSCCB currently assembles more than 20 principal investigators for 4 major research programmes including (a) Synthetic Chemistry; (b) Chemical Biology of Natural Products and Chinese Medicine; (c) Metal Anticancer Medicine, Diagnostics and Theranostics; and (d) Multi-Omics and Innovative Analytical Technologies for InnoHealth.
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