David Koes

David Koes, Ph.D.
Assistant Professor

Ph.D. in Computer Science, Carnegie Mellon University
David Koes

Phone: (412) 383-5745
E-mail: dkoes@pitt.edu
Website: bits.csb.pitt.edu

Research Summary
The goal of my research is to develop novel computational methods and applications that unlock the potential of computational drug discovery to revolutionize the treatment of disease. I develop new applications of machine learning for computational drug discovery as well as discrete algorithms for accelerating the drug discovery workflow. In addition to developing new computational techniques, I deploy these techniques via easy to use online applications and apply them in prospective drug discovery exercises.



MSCBIO2025 Introduction to Bioinformatics Programming in Python (Fall Semester)  This course is a graduate level introduction to programming in Python in the context of computational biology applications.

MSCBIO2065 Scalable Machine Learning for Big Data Biology (Spring Semester)  This course is a rigorous introduction to the effective application of machine learning to large and complex biomedical data.


Recent Publications
Gau D, Vignaud L, Allen A, Guo Z, Sahel J, Boone DN, Koes DR, Guillonneau X, Roy P. Disruption of profilin1 function suppresses developmental and pathological retinal neovascularization. J Biol Chem. 2020 May 22;. doi: 10.1074/jbc.RA120.012613. [Epub ahead of print] PMID: 32444495.
Sunseri J, Koes DR. libmolgrid: Graphics Processing Unit Accelerated Molecular Gridding for Deep Learning Applications. J Chem Inf Model. 2020 Mar 23;60(3):1079-1084. doi: 10.1021/acs.jcim.9b01145. Epub 2020 Feb 26. PMID: 32049525.
Sunseri J, King JE, Francoeur PG, Koes DR. Convolutional neural network scoring and minimization in the D3R 2017 community challenge. J Comput Aided Mol Des. 2019 Jan;33(1):19-34. doi: 10.1007/s10822-018-0133-y. Epub 2018 Jul 10. PMID: 29992528; PubMed Central PMCID: PMC6931043.
Koes DR. The Pharmit backend: A computer systems approach to enabling interactive online drug discovery. IBM Journal of Research and Development. 2018 November; 62(6):3:1-3:6. NIHMSID: NIHMS1063500.doi: 10.1147/JRD.2018.2883977.
Hochuli J, Helbling A, Skaist T, Ragoza M, Koes DR. Visualizing convolutional neural network protein-ligand scoring. J Mol Graph Model. 2018 Sep;84:96-108. doi: 10.1016/j.jmgm.2018.06.005. PMID: 29940506; PMCID: PMC6343664.


Project title Proj Start Date Proj End Date Funding Source
Methods, Tools and Resources for Interactive Online Virtual Screening and Lead Optimization 2/1/2017 2/1/2021 NIGMS