Message passing interface and multithreading hybrid for parallel molecular docking of large databases on petascale high performance computing machines. - Xiaohua Zhang; Sergio Ernesto Wong; Felice C. Lightstone (J. Comput. Chem., 2013)

Catalytic site identification - a web server to identify catalytic site structural matches throughout PDB. - Daniel A. Kirshner; Jerome P. Nilmeier; Felice C. Lightstone (Nucleic Acids Res., 2013)

Toward Fully Automated High Performance Computing Drug Discovery: A Massively Parallel Virtual Screening Pipeline for Docking and Molecular Mechanics/Generalized Born Surface Area Rescoring to Improve Enrichment. - Xiaohua Zhang; Sergio Ernesto Wong; Felice C. Lightstone (J. Chem. Inf. Model., 2014)

Molecular Dynamics Simulations of Ligand Recognition upon Binding Antithrombin: A MM/GBSA Approach. - Xiaohua Zhang; Horacio Pérez Sánchez; Felice C. Lightstone (IWBBIO (2), 2015)

An Electrostatic Funnel in the GABA-Binding Pathway. - Timothy S. Carpenter; Felice C. Lightstone (PLoS Comput. Biol., 2016)

A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer. - Francesco Di Natale; Harsh Bhatia; Timothy S. Carpenter; Chris Neale; Sara Kokkila Schumacher; Tomas Oppelstrup; Liam Stanton; Xiaohua Zhang; Shiv Sundram; Thomas R. W. Scogland; Gautham Dharuman; Michael P. Surh; et al. (SC, 2019)

Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. - Derek Jones; Hyojin Kim 001; Xiaohua Zhang; Adam T. Zemla; Garrett Stevenson; William D. Bennett; Dan Kirshner 001; Sergio Ernesto Wong; Felice C. Lightstone; Jonathan E. Allen (CoRR, 2020)

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning. - W. F. Drew Bennett; Stewart He; Camille L. Bilodeau; Derek Jones; Delin Sun; Hyojin Kim 001; Jonathan E. Allen; Felice C. Lightstone; Helgi I. Ingólfsson (J. Chem. Inf. Model., 2020)

Binding Affinity Prediction by Pairwise Function Based on Neural Network. - Fangqiang Zhu; Xiaohua Zhang; Jonathan E. Allen; Derek Jones; Felice C. Lightstone (J. Chem. Inf. Model., 2020)

Generalizable coordination of large multiscale workflows: challenges and learnings at scale. - Harsh Bhatia; Francesco Di Natale; Joseph Y. Moon; Xiaohua Zhang; Joseph R. Chavez; Fikret Aydin; Christopher B. Stanley; Tomas Oppelstrup; Chris Neale; Sara Kokkila Schumacher; Dong H. Ahn; Stephen Herbein; et al. (SC, 2021)

High-throughput virtual screening of small molecule inhibitors for SARS-CoV-2 protein targets with deep fusion models. - Garrett A. Stevenson; Derek Jones; Hyojin Kim 001; W. F. Drew Bennett; Brian J. Bennion; Monica Borucki; Feliza Bourguet; Aidan Epstein; Magdalena Franco; Brooke Harmon; Stewart He; Max P. Katz; et al. (SC, 2021)

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models. - Sam Ade Jacobs; Tim Moon; Kevin McLoughlin; Derek Jones; David Hysom; Dong H. Ahn; John C. Gyllenhaal; Pythagoras Watson; Felice C. Lightstone; Jonathan E. Allen; Ian Karlin; Brian Van Essen (Int. J. High Perform. Comput. Appl., 2021)

Improved Protein-Ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference. - Derek Jones; Hyojin Kim 001; Xiaohua Zhang; Adam T. Zemla; Garrett Stevenson; W. F. Drew Bennett; Daniel A. Kirshner; Sergio Ernesto Wong; Felice C. Lightstone; Jonathan E. Allen (J. Chem. Inf. Model., 2021)

Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations. - Harsh Bhatia; Timothy S. Carpenter; Helgi I. Ingólfsson; Gautham Dharuman; Piyush Karande; Shusen Liu 001; Tomas Oppelstrup; Chris Neale; Felice C. Lightstone; Brian Van Essen; James N. Glosli; Peer-Timo Bremer (Nat. Mach. Intell., 2021)

Scalable Composition and Analysis Techniques for Massive Scientific Workflows. - Dong H. Ahn; Xiaohua Zhang; Jeffrey Mast; Stephen Herbein; Francesco Di Natale; Dan Kirshner 001; Sam Ade Jacobs; Ian Karlin; Daniel J. Milroy; Bronis R. de Supinski; Brian Van Essen; Jonathan E. Allen; et al. (e-Science, 2022)

Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints. - Konstantia Georgouli; Helgi I. Ingólfsson; Fikret Aydin; Mark Heimann; Felice C. Lightstone; Peer-Timo Bremer; Harsh Bhatia (CoRR, 2022)

Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning. - Fikret Aydin; Konstantia Georgouli; Gautham Dharuman; James N. Glosli; Felice C. Lightstone; Helgi I. Ingólfsson; Peer-Timo Bremer; Harsh Bhatia (CoRR, 2022)

Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery. - Ya Ju Fan; Jonathan E. Allen; Kevin S. McLoughlin; Da Shi; Brian J. Bennion; Xiaohua Zhang; Felice C. Lightstone (CoRR, 2022)

A biology-informed similarity metric for simulated patches of human cell membrane. - Harsh Bhatia; Jayaraman J. Thiagarajan; Rushil Anirudh; T. S. Jayram; Tomas Oppelstrup; Helgi I. Ingólfsson; Felice C. Lightstone; Peer-Timo Bremer (Mach. Learn. Sci. Technol., 2022)

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules. - Martin Stroet; Bertrand Caron; Martin S. Engler; Jimi van der Woning; Aude Kauffmann; Marc van Dijk; Mohammed El-Kebir; Koen Visscher; Josef Holownia; Callum Macfarlane; Brian J. Bennion; Svetlana Gelpi-Dominguez; et al. (J. Comput. Aided Mol. Des., 2023)

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method. - Garrett A. Stevenson; Dan Kirshner 001; Brian J. Bennion; Yue Yang; Xiaohua Zhang; Adam T. Zemla; Marisa W. Torres; Aidan Epstein; Derek Jones; Hyojin Kim 001; W. F. Drew Bennett; Sergio Ernesto Wong; et al. (J. Chem. Inf. Model., 2023)

Machine Learning-driven Multiscale MD Workflows: The Mini-MuMMI Experience. - Loïc Pottier; Konstantia Georgouli; Timothy S. Carpenter; Fikret Aydin; Jeremy O. B. Tempkin; Dwight V. Nissley; Frederick H. Streitz; Thomas R. W. Scogland; Peer-Timo Bremer; Felice C. Lightstone; Helgi I. Ingólfsson (CoRR, 2025)