David Ryan Koes, PhD

Removing barriers to computational drug discovery one bit at a time

About

I am an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh.

I develop novel computational algorithms and build full-scale systems to support rapid and inexpensive drug discovery while simultaneously applying these methods to develop novel therapeutics. I seek to unlock the power of computation and machine learning to solve challenging, real world problems and am a staunch advocate of open source software and open science.

I use a light-themed IDE.

Contact

748 Murdoch Building
Department of Computational & Systems Biology
School of Medicine, University of Pittsburgh
3420 Forbes Ave
Pittsburgh, PA 15213-3203

(412) 383-5745


Publications

Google Scholar NCBI

Presentations and Data

People

Graduate Students

Jonathan King, Paul Francoeur, Drew McNutt, Dillon Gavlock (COBB), Jocelyn Sunseri

Research Fellows

Matthew Ragoza, Rishal Aggarwal, Tomohide Masuda

Undergraduate Students

Di Zhang, Letian Deng, Lucas Morley, Zoey Yang, Sneha Mittal, Christian Tumandao, Adam Cippel,Nishita Kalepalli, Callum Harding, Liz Chiyka, Ebru Lider, Rich Iovanisci, Zach Kunning, Amitha Halthore, Dale Erikson, Shane Buckley, Andrew Jia, Ian Snyder, Nick Ranellone, Hunter Haaf, Jinlang Wang, Ajay Subramanian, Alex Visbisky, Amrita Nallathambi, Hanna Sommers, Lily Turner, Alex Ludwig (TECBio), Aaron Zheng, Sharanya Bandla, Christopher Dunstan (TECBio), Pulkit Mittal, Sara Amato, Roosha Mandal, Elisa Idrobo (TECBio), Karla Robles (TECBio), Josh Hochuli, Haiyang Huang, Noah Bastola, Anthony Tummillo, Jesus Bracho, Ethan Hain (TECBio), Jasmine Collins, Christine Grassi (TECBio), James Castiglione, Nick Rego, Jacob Riddle

Former

Teaching

MSCBIO2025: Introduction to Bioinformatics Programming in Python

An graduate-level introductory programming course with a focus on analyzing biological data.
Fall Semester

MSCBIO2066: Scalable Machine Learning for Big Data Biology

Distributed and cloud computing meets machine learning meets computational biology.
The focus is on applications rather than theory. Co-taught with Maria Chikina
Spring Semester

CompBio Academy (formerly DiscoBio)

The Computational Biology Summer Academy at UPMC Hillman Cancer Center.
An experiential summer academy for rising high school juniors and seniors.
Co-Director

Software (GitHub)

libmolgrid
Python library for CUDA accelerated molecular gridding

gnina
Deep learning for molecular docking

pharmit
Interactive exploration of chemical space

3Dmol.js
Molecular visualization with WebGL

qsar-tools
Collection of scripts for creating and visualizing 2D QSAR models

smina*
Scoring and Minimization with AutoDock Vina

AnchorQuery*
Specialized pharmacophore search for targeting protein-protein interactions with multicomponent reaction chemistry.

Pharmer*
General pharmacophore search open-source software.

ZINCPharmer*
Free online pharmacophore search engine for the ZINC database.

PocketQuery*
Identify PPI inhibitor starting points from PPI structure.

ShapeDB*
Indexed search of molecular shapes

*Developed in collaboration with the Camacho Lab

Funding

I am currently funded through R01GM108340 from the National Institute of General Medical Sciences and CHE-1800435 from the National Science Foundation (with Geoff Hutchison). I have previously received funding from R21NS107785 from the National Institute of Neurological Disorders and Stroke (with Sam Poloyac and Lee McDermott), Relay Therapeutics, the Samuel and Emma Winters Foundation, the CTSI Biomedical Modeling Pilot Award, and aigrant.org, as well as hardware and software support from NVIDIA and Google Cloud Platform.

PittProxy: