An important aspect in the development of novel chemicals is their environmental fate, that is their ability to degrade when released in the environment. To achieve this, the goal is to design compounds that fulfill a certain function – for example medication or pesticides, and at the same time allow for quick degradation into harmless metabolites. We will develop new algorithms that achieve this, evaluating on large databases of existing compounds. We will use standard machine learning models for predicting degradation products and pathways (see enviPath – https://envipath.org). Our approach will be to start with existing compounds, and transform them using adversarial methods and generative models (GANs) such that their degradability increases while at the same time keeping their original function.
Recommended skills: Basic knowledge of chemistry, machine learning, and python