About Me
I am a recent PhD graduate of the Joint Carnegie Mellon/University of Pittsburgh PhD program for Computational Biology, where I worked under the guidance of Prof. David Ryan Koes. My research expertise lies in enhancing the representations of protein-ligand interactions with a focus on structure-based methods. This has involved exploring various computational drug discovery approaches, including virtual screening, docking, and binding affinity prediction.
I am passionate about leveraging deep learning and computational methods to advance the drug discovery pipeline, as demonstrated by my collaboration with Christian Fernandez’s Lab at the University of Pittsburgh, where we discovered a novel inhibitor of the Nuclear Factor of Activated T-Cells 2 (NFATC2) (published in Frontiers in Pharmacology).
Research Interests:
- Drug Discovery
- Deep Learning
- Structural Biology
- Metric Learning
- Self-Supervised Learning
I graduated from Purdue University with honors in 2019 with a double major in Physics and Mathematics.
Other Interests
When I am not doing research I enjoy cooking, baking, and fermenting (Checkout my Cookbook). My other time is spent outdoors enjoying nature while climbing, hiking, and camping.
Papers and Talks
A list of the published papers and conference talks that I have given.
For a more up to date list, check out my Google Scholar page.
GNINA 1.3: the next increment in molecular docking with deep learning
Andrew McNutt, Yanjing Li, Rocco Meli, Rishal Aggarwal, David Ryan Koes
Link to PaperInterpretable adenylation domain specificity prediction using protein language models
Abhinav K. Adduri Andrew McNutt, Caleb Ellington, Krish Suraparaju, Nan Fang, Donghui Yan, Benjamin Krummenacher, Sitong Li, Camila Bodden, Eric Xing, Bahar Behsaz, David Ryan Koes, Hosein Mohimani
Link to PaperDuvelisib is a novel NFAT inhibitor that mitigates adalimumab-induced immunogenicity
Aboli Bhingarkar, Yuyin Wang, Keito Hoshitsuki, Katherine Marie Eichinger, Sanjay Rathod, Yin Zhu, He Lyu, Andrew McNutt, Larry W Moreland, Lee Mcdermott, David Ryan Koes, Christian Fernandez
Link to PaperSPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes
Andrew McNutt, Abhinav K. Adduri, Caleb N. Ellington, Monica T. Dayao, Hosein Mohimani, Eric P. Xing, David R. Koes
Link to Paper Link to PosterUltra-High-Throughput Virtual Screening for Antimicrobials
Caleb N. Ellington, Abhinav K. Adduri, Andrew McNutt, Monica T. Dayao, Hosein Mohimani, David R. Koes, Eric P. Xing
Condensing Molecular Docking CNNs via Knowledge Distillation
Andrew McNutt, Yanjing Li, Paul Francoeur, David Ryan Koes
Link to PaperOpen-ComBind: Harnessing unlabeled data for improved binding pose prediction
Andrew McNutt, David Ryan Koes
Link to PaperConformer Generation for Structure-Based Drug Design: How Many and How Good?
Andrew McNutt, Fatimah Bisiriyu, Sophia Song, Ananya Vyas, Geoffrey R. Hutchison, David Ryan Koes
Link to PaperImproving 𝚫𝚫G Predictions with a Multitask Convolutional Siamese Network
Andrew McNutt, David Ryan Koes
Link to PaperIntegrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis
Seth Winfree, Andrew McNutt, Suraj Khochare, Tyler J. Borgard, Daria Barwinska, Angela R. Sabo, Michael J. Ferkowicz, James C. Williams Jr, James E. Lingeman, Connor J Gulbronson, Katherine J. Kelly, Timothy A. Sutton, Pierre C. Dagher, Michael T. Eadon, Kenneth W. Dunn, Tarek M. El-Achkar
Link to PaperExploring 𝚫𝚫G prediction with Siamese Networks
Andrew McNutt, David Koes
Link to TalkGNINA 1.0: Molecular docking with deep learning
Andrew McNutt, Paul Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, David Koes
Link to Paper Link to TalkIn situ classification of cell types in human kidney tissue using 3D nuclear staining
Andre Woloshuk, Suraj Khochare, Aljohara F Almulhim, Andrew McNutt, Dawson Dean, Daria Barwinska, Michael J Ferkowicz, Michael T Eadon, Katherine J Kelly, Kenneth W Dunn, Mohammad A Hasan, Tarek M El‐Achkar, Seth Winfree
Link to PaperComparison of Supervised Machine Learning and Probabilistic Approaches for Record Linkage
Andrew McNutt, Shaun J Grannis, Na Bo, Huiping Xu, Suranga N Kasthurirathne
Education & Experience
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Aug 2019 - Jan 2025
PhD Student in Koes Lab
Structure-Based Drug Design Deep Learning Virtual Screening Affinity Prediction Molecular Docking -
Summer 2019
Student Research Assistant - Center for Biomedical Informatics
Neural Networks Hyperparameter Optimization -
Summer 2018
Student Intern
Clustering Dimensionality Reduction -
Summer 2017
Indiana University O'Brien Student Intern
Java -
2017 - 2019
Undergraduate Research Assistant - Department of Medicinal Chemistry & Molecular Pharmacology
Molecular Dynamics Machine Learning -
2015 - 2019
B.S. Physics & Mathematics
Minor in Chemistry