Artificial intelligence in molecular de novo design: Integration with experiment.

Journal: Current opinion in structural biology
Published Date:

Abstract

In this mini review, we capture the latest progress of applying artificial intelligence (AI) techniques based on deep learning architectures to molecular de novo design with a focus on integration with experimental validation. We will cover the progress and experimental validation of novel generative algorithms, the validation of QSAR models and how AI-based molecular de novo design is starting to become connected with chemistry automation. While progress has been made in the last few years, it is still early days. The experimental validations conducted thus far should be considered proof-of-principle, providing confidence that the field is moving in the right direction.

Authors

  • Jon Paul Janet
    Department of Chemical Engineering , Massachusetts Institute of Technology , Cambridge , MA 02139 , USA . Email: hjkulik@mit.edu ; Tel: +1-617-253-4584.
  • Lewis Mervin
    Molecular AI, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK. Electronic address: lewis.mervin1@astrazeneca.com.
  • Ola Engkvist
    Hit Discovery, Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, AstraZeneca R&D Gothenburg, 431 83, Mölndal, Sweden.