In the summer of 2023, I had an amazing 10-week paid internship working under the mentorship of Professors Kyle Chard and Ian Foster, in Globus Labs at the University of Chicago. I explored the K-Nearest Neighbors machine learning algorithm to accelerate virtual drug screening. Here is a taste of what my summer research project was about. The COVID-19 pandemic has highlighted the power of using computational methods for virtual drug screening. However, the molecular search space is enormous and protein docking methods are still computationally intractable without access to the world’s largest supercomputers. Instead, researchers are using AI methods to help guide docking campaigns. In such approaches, a lightweight surrogate model is trained and then used to identify promising candidates for screening.

I designed and developed ParslDock, a Python-based pipeline using the Parsl parallel programming library and the K-Nearest Neighbors machine learning model to screen a huge molecular space of molecules against arbitrary receptors. We achieved a 38X speedup with ParslDock compared to a brute-force docking approach. Our results have been accepted for publication through a peer-reviewed process at IEEE/ACM SuperComputing/SC 2023 conference, which I presented in Denver Colorado in November as a poster (writeup,poster), as well as an oral presentation. At the SC'23 conference, I was awarded 2nd Place Winner of the ACM Student Research Competition (SRC)!

My summer work was the foundation of a tutorial to showcase Parsl coupled with Machine Learning that was given to an audience of 40 people on September 14th at the Developing Large-Scale Parallel Programs in Python with Parsl Workshop co-located with the TAPIA Conference 2023.

News

• 12/22/2023: Johnny Raicu awarded for research, Glenbrook South High School Oracle
• 11/16/2023: John Raicu received 2nd Place Award in undergraduate track, ACM Student Research Competition
• 11/01/2023: John Raicu's Google Scholar profile is live

Source Code

• ParslDock Summer Project
• ParslDock Tutorial

Publications

1. John Raicu, Valerie Hayot-Sasson, Kyle Chard, and Ian Foster. “Navigating the Molecular Maze: A Python-Powered Approach to Virtual Drug Screening”, IEEE/ACM SuperComputing/SC 2023 [poster]
2. Jamison Kerney, John Raicu, Kyle Chard, Ioan Raicu. "Towards Fine-grained Parallelism in Parallel and Distributed Python Libraries”, IEEE International Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS) 2024, co-located with IEEE IPDPS 2024

Technical Reports

1. John Raicu, Valerie Hayot-Sasson, Kyle Chard, and Ian Foster. “ParslDock: A Python-Powered Approach to Virtual Drug Screening”, Technical Report, University of Chicago, 2023

Presentations

1. “Navigating the Molecular Maze: A Python-Powered Approach to Virtual Drug Screening”, IEEE/ACM SuperComputing/SC 2023, November 2023
2. “ParslDock: Accelerating Virtual Drug Screening with Parallelism and Machine Learning", ParslFest 2023, October 2023
3. “Navigating the Molecular Maze: A Python-Powered Approach to Virtual Drug Screening”, Globus Labs, University of Chicago, August 2023