CCK-21: David Koes

TL;DR: CCK-21 will feature Prof. David Koes from the University of Pittsburgh on Friday, June 28th, 2024, at 4:00 pm in the Seminar Room, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU. Free refreshments at 5 pm.

This Friday! We’re delighted to announce Prof. David Koes from the University of Pittsburgh will be speaking at our next Comp Chem Kitchen, CCK-21, on Friday, June 28th, 2024, at 4:00 pm in the Seminar Room, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU. The title of his talk is ”Deep learning for structure-based drug discovery”.

Abstract

Prof. Koes 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, he will describe his 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.

About Prof. David Koes

Prof. David R. Koes is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh and an Associate Director of the Joint Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology (CPCB). He is also affiliated with the Integrative Systems Biology, Intelligent Systems Program, and Computational Biomedicine & Biotechnology graduate programs at the University of Pennsylvania.

Prof. Koes develops novel computational algorithms and builds full-scale systems to support rapid and inexpensive drug discovery while simultaneously applying these methods to develop novel therapeutics. He seeks to unlock the power of computation and machine learning to solve challenging, real world problems and is a staunch advocate of open source software and open science.