Staff information

PNNL Publications

2024

• Kim D., A.D. McNaughton, and N. Kumar. 2024. "Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody-Antigen Interactions." Bioengineering (Basel) 11, no. 2:Art. No. 185. PNNL-SA-194122. doi:10.3390/bioengineering11020185

2023

• Joshi R., K.J. Schultz, J.W. Wilson, A. Kruel, R.A. Varikoti, C. Kombala Nanayakkara Thambiliya, and D.W. Kneller, et al. 2023. "AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2." Journal of Chemical Information and Modeling 63, no. 5:1438-1453. PNNL-SA-176233. doi:10.1021/acs.jcim.2c01377
• McNaughton A.D., R. Joshi, C.R. Knutson, F. Anubhav, K.J. Luebke, J.P. Malerich, and P. Madrid, et al. 2023. "Machine Learning Models for Predicting Molecular UV-Vis Spectra with Quantum Mechanical Properties." Journal of Chemical Information and Modeling 63, no. 5:1401-1648. PNNL-SA-171633. doi:10.1021/acs.jcim.2c01662

2022

• Clyde A., S. Galanie, D.W. Kneller, H. Ma, Y. Babuji, B. Blaiszik, and A. Brace, et al. 2022. "High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor." Journal of Chemical Information and Modeling 62, no. 1:116-128. PNNL-SA-161210. doi:10.1021/acs.jcim.1c00851
• Kim H., D.G. Hauner, J.A. Laureanti, A. Kruel, S. Raugei, and N. Kumar. 2022. "Mechanistic Investigation of SARS-CoV-2 Main Protease to Accelerate Design of Covalent Inhibitors." Scientific Reports 12, no. 1:Art. No. 21037. PNNL-SA-170467. doi:10.1038/s41598-022-23570-6
• Knutson C.R., M.S. Bontha, J.A. Bilbrey, and N. Kumar. 2022. "Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks." Scientific Reports 12. PNNL-SA-166075. doi:10.1038/s41598-022-10418-2
• Varikoti R.A., K.J. Schultz, M. Zhou, C. Kombala Nanayakkara Thambiliya, K.R. Brandvold, A. Kruel, and N. Kumar. 2022. Machine Learning-driven Molecular Design for Therapeutic Discovery. PNNL-33349. Richland, WA: Pacific Northwest National Laboratory. Machine Learning-driven Molecular Design for Therapeutic Discovery
• Wu Y., M. Cashman, N. Choma, E. Teixeira Prates, V.M. Vergara, M.B. Shah, and A. Chen, et al. 2022. "Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery." In Proceedings of the 10th International Conference on Learning Representations (ICLR 2022), April 25-29, 2022, Virtual, Online. PNNL-SA-165296.

2021

• Alexander F.J., J.A. Ang, J.A. Bilbrey, J. Balewski, T.A. Casey, R. Chard, and J. Choi, et al. 2021. "Co-design Center for Exascale Machine Learning Technologies (ExaLearn)." The International Journal of High Performance Computing Applications 35, no. 6:598-616. PNNL-SA-156070. doi:10.1177/10943420211029302
• Choi R., M. Zhou, R. Shek, J.W. Wilson, L. Tillery, J.C. Craig, and I.A. Salukhe, et al. 2021. "High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV-2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity." PLoS One 16, no. 4:e0250019. PNNL-SA-159108. doi:10.1371/journal.pone.0250019
• Joshi R., A.D. McNaughton, D.G. Thomas, C. Henry, S. Canon, L. McCue, and N. Kumar. 2021. "Quantum Mechanical Methods Predict Accurate Thermodynamics of Biochemical Reactions." ACS Omega 6, no. 14:9948-9959. PNNL-SA-157024. doi:10.1021/acsomega.1c00997
• Joshi R., and N. Kumar. 2021. "Artificial Intelligence for Autonomous Molecular Design: A Perspective." Molecules 26, no. 22:Art. No. 6761. PNNL-SA-159775. doi:10.3390/molecules26226761
• Joshi R., N. Gebauer, M.S. Bontha, M. Khazaieli, R. James, B. Brown, and N. Kumar. 2021. "3D-Scaffold: Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds." Journal of Physical Chemistry B 125, no. 44:12166-12176. PNNL-SA-162972. doi:10.1021/acs.jpcb.1c06437
• Matlock M., M. Hoffman, N. Dang, D. Folmsbee, L. Langkamp, G.R. Hutchison, and N. Kumar, et al. 2021. "Deep Learning Coordinate-Free Quantum Chemistry." Journal of Physical Chemistry A 125, no. 40:8978-8986. PNNL-SA-146299. doi:10.1021/acs.jpca.1c04462
• Moses I., R. Joshi, B. Ozdemir, N. Kumar, J. Eickholt, and V. Barone. 2021. "Machine Learning Screening of Metal-ion Battery Electrode Materials." ACS Applied Materials & Interfaces 13, no. 45:53355-53362. PNNL-SA-160595. doi:10.1021/acsami.1c04627
• Siriwardane E., R. Joshi, N. Kumar, and D. Cakir. 2021. "Revealing the Formation Energy-Exfoliation Energy-Structure Correlation of MAB Phases Using Machine Learning and DFT." ACS Applied Materials & Interfaces 12, no. 26:29424-29431. PNNL-SA-151212. doi:10.1021/acsami.0c03536

2020

• Artz J.H., O. Zadvornyy, D.W. Mulder, S.M. Keable, A.E. Cohen, M.W. Ratzloff, and S. Williams, et al. 2020. "Tuning catalytic bias of hydrogen gas producing hydrogenases." Journal of the American Chemical Society 142, no. 3:1227-1235. PNNL-SA-140081. doi:10.1021/jacs.9b08756

2019

• Kumar N., D. Butcher, and P.M. Kozlowski. 2019. "Reductive Co-C Bond Cleavage in B12-Dependent Methylmalonyl CoA Mutase: Mechanistic Implications." Journal of Physical Chemistry B 123, no. 10:2210-2216. PNNL-SA-138248. doi:10.1021/acs.jpcb.8b10820
• Kumar N., J.M. Darmon, C.J. Weiss, M.L. Helm, S. Raugei, and R.M. Bullock. 2019. "Outer Coordination Sphere Proton Relay Base and Proximity Effects on Hydrogen Oxidation with Iron Electrocatalysts." Organometallics 38, no. 6:1391-1396. PNNL-SA-139298. doi:10.1021/acs.organomet.8b00805
• Pegis M.L., D.J. Martin, C.F. Wise, A.C. Brezny, S. Johnson, L.E. Johnson, and N. Kumar, et al. 2019. "Mechanism of Catalytic O2 Reduction by Iron Tetraphenylporphyrin." Journal of the American Chemical Society 141, no. 20:8315-8326. PNNL-SA-141930. doi:10.1021/jacs.9b02640

2018

• Cannon W.R., J.D. Zucker, D.J. Baxter, N. Kumar, S.E. Baker, J. Hurley, and J.C. Dunlap. 2018. "Prediction of Metabolite Concentrations, Rate Constants and Post-Translational Regulation using Maximum Entropy-based Simulations with Application to Central Metabolism of Neurospora crassa." Processes 6, no. 6:Article No. 63. PNNL-SA-134563. doi:10.3390/pr6060063
• Hurley J.M., M.S. Jankowski, H. De Los Santos, A.M. Crowell, S. Fordyce, J.D. Zucker, and N. Kumar, et al. 2018. "Circadian proteomic analysis uncovers mechanisms of post-transcriptional regulation in metabolic pathways." Cell Systems 7, no. 6:613-626. PNNL-SA-138421. doi:10.1016/j.cels.2018.10.014

2016

• Cardenas A.J., B. Ginovska-Pangovska, N. Kumar, J. Hou, S. Raugei, M.L. Helm, and A.M. Appel, et al. 2016. "Controlling Proton Delivery with Catalyst Structural Dynamics." Angewandte Chemie International Edition 55, no. 43:13509-13513. PNNL-SA-115082. doi:10.1002/anie.201607460
• Pegis M.L., B.A. McKeown, N. Kumar, K. Lang, D.J. Wasylenko, P. Zhang, and S. Raugei, et al. 2016. "Homogenous Electrocatalytic Oxiygen Reduction Rates Correlate with Reaction Overpotential in Acidic Organic Solutions." ACS Central Science 2, no. 11:850-856. PNNL-SA-117180. doi:10.1021/acscentsci.6b00261

2015

• Darmon J.M., N. Kumar, E. Hulley, C.J. Weiss, S. Raugei, R.M. Bullock, and M.L. Helm. 2015. "Increasing the Rate of Hydrogen Oxidation without Increasing the Overpotential: A Bio-Inspired Iron Molecular Electrocatalyst with an Outer Coordination Sphere Proton Relay." Chemical Science 6, no. 5:2737-2745. PNNL-SA-105708. doi:10.1039/C5SC00398A
• Hulley E., N. Kumar, S. Raugei, and R.M. Bullock. 2015. "Manganese-Based Molecular Electrocatalysts for Oxidation of Hydrogen." ACS Catalysis 5, no. 11:6838-6847. PNNL-SA-112291. doi:10.1021/acscatal.5b01751

2014

• Kumar N., D.M. Camaioni, M. Dupuis, S. Raugei, and A.M. Appel. 2014. "Mechanistic Insights into Hydride Transfer for Catalytic Hydrogenation of CO2 with Cobalt Complexes." Dalton Transactions 43, no. 31:11803-11806. PNNL-SA-101141. doi:10.1039/c4dt01551g