Molecular Functionality

Molecular functionality research focuses on understanding and predicting the properties and behaviors of molecules, primarily to accelerate drug discovery and materials science. Current efforts leverage machine learning, particularly graph neural networks and large language models, along with novel algorithms like active deep kernel learning and multi-objective optimization frameworks, to design molecules with desired characteristics and quantify prediction uncertainties. These advancements enable more efficient exploration of chemical space, leading to improved accuracy in predicting molecular properties and ultimately facilitating the development of new therapeutics and materials.