Deep learning for structure based drug discovery
We will describe the training and development of convolutional neural networks for protein-ligand scoring and how these deep learning models are integrated into the GNINA molecular docking open source software. Successful prospective evaluations of GNINA will be discussed, including recent top performance in the Critical Assessment of Computational Hit-Finding Experiments (CACHE). Additionally, we will describe our open source pharmacophore screening resource, Pharmit, which enables the screening of millions of compounds in seconds and discuss several generative approaches for hit discovery using deep generative models.
Date:
28 June 2024, 16:00 (Friday, 10th week, Trinity 2024)
Venue:
Dorothy Crowfoot Hodgkin Building, off South Parks Road OX1 3QU
Venue Details:
Seminar Room 1
Speaker:
Prof David Ryan Koes (University of Pittsburgh)
Organising department:
Department of Biochemistry
Organiser:
Prof Phil Biggin (University of Oxford)
Organiser contact email address:
philip.biggin@bioch.ox.ac.uk
Part of:
SBCB Seminar Series
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Philip Biggin
