U.S. Department of Energy

Pacific Northwest National Laboratory

Neeraj Kumar

Professional Title: 
Data Scientist

Dr. Neeraj Kumar, a computational data scientist, has extensive research experience in computational chemistry, biophysics, drug discovery, structural and molecular biology, bio/cheminformatics, multi-omics data analysis, metabolic network, molecular modeling and simulation of complex biological systems. His graduate research was directed toward the molecular-level understanding of Vitamin B12 mediated enzymatic reactions and structure-based drug design using machine learning. Currently, his research interests are focused on developing mathematical and artificial intelligence (AI)/machine learning (ML) tools to solve challenging structural and systems biology problems at a fundamental level using basic principles of statistical physics/chemistry including chemical properties and accurate data computed from first principles approximation. This includes developing an AI-based models for therapeutic design (small molecule and peptide) and protein engineering or biomedical applications. 

  • Post-Doctoral, Pacific Northwest National Lab., Computational Catalysis/Biophysics, 2016
  • Ph.D., University of Louisville, Louisville, Computational Chemistry, 2013
  • Graduate Research Intern, Bioscience Division, LLNL, Livermore, Computational Biology, 2012
  • M. S., Panjab University, Chandigarh, India, Computational Chemistry
  • B. S., Panjab University, Chandigarh, India, Math/Physics
  • Early Career Exceptional Achievement Ronald L. Brodzinski Award for recognizing outstanding scientific contributions in fields of importance to PNNL, the Department of Energy and other clients (Sep. 2020).
  • Outstanding Performance Award, Pacific Northwest National Laboratory, Biological Science Division (Dec. 2019)
  • Received appreciation award at the OLC International Biotechnology Conference (Sep. 2019)
  • Outstanding Performance Award, Pacific Northwest National Laboratory, Computational Catalysis (April 2016)
  • Awarded Graduate Dean’s Citation for Excellence in Graduate Studies at University of Louisville, (Dec. 2013)
  • Lawrence Graduate Student Award, Biosciences Division, Lawrence Livermore National Laboratory, Livermore, CA (July 2012)
  • Graduate Student Union (GSU) Fellowship, University of Louisville (Feb. 2011).
Research Interests: 
  • Artificial Intelligence and Machine learning/Deep Learning for therapeutic design 
  • Computational Chemistry methods such as Quantum Mechanics, Molecular Dynamics, and Molecular Mechanics
  • Computational modeling and analysis of genome-scale metabolic networks (Genome Annotation and Pathway Engineering)
  • Multi-omics (transcriptomics, proteomics, and metabolomics ) data analysis, integration, and prediction
  • Quantum Computing/Sensing, Cloud Computing and High-Performance Computing


  • Joshi, R., McNaughton, A.D., Thomas, D.G., Henry, C., Canon, S., McCue, L., and Kumar, N. "Quantum Mechanical Methods Predict Accurate Thermodynamics of Biochemical Reactions" ACS Omega 2021 https://doi.org/10.1021/acsomega.1c00997 (Accepted)
  • Joshi R.; Kumar N. "Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective" (2021); arXiv e-prints DOI: arXiv:2102.06045
  • Choi, R.;  Zhou, M.;  Shek, R.;  Wilson, J. W.;  Tillery, L.;  Craig, J. K.;  Salukhe, I. A.;  Hickson, S. E.;  Kumar, N.;  James, R. M.;  Buchko, G. W.;  Wu, R.;  Huff, S.;  Nguyen, T.-T.;  Hurst, B. L.;  Cherry, S.;  Barrett, L. K.;  Hyde, J. L.; Van Voorhis, W. C., High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity. (2021bioRxiv 2021, 2021.01.21.427657.
  • Siriwardane, E.; Joshi, R.; Kumar, N.; and Cakir, D. “Machine Learning and DFT Prediction of Formation/Exfoliation Energy and Structure Correlation of MAB Phases.” ACS Appl. Mater. Interfaces 2020, 26 (12), 29424-29431.
  • Ward L, Bilbrey, JA, Choudhury, S, Kumar, N, Sivaraman G.. Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19. (2021) arXiv:2102.04977


  • Artz, J. H.; Zadvornyy, O. A.; Mulder, D. W.; Keable, S. M.; Cohen, A. E.; Ratzloff, M. W.; Williams, S. G.; Ginovska, B.; Kumar, N.; Song, J.; McPhillips, S. E.; Davidson, C. M.; Lyubimov, A. Y.; Pence, N.; Schut, G. J.; Jones, A. K.; Soltis, S. M.; Adams, M. W. W.; Raugei, S.; King, P. W.; Peters, J. W., Tuning Catalytic Bias of Hydrogen Gas Producing Hydrogenases. J. Am. Chem. Soc. 2020, 142 (3), 1227-1235.
  • Nakayasu E. S.; Chazin-Gray, A. M.; Auberry, D. L.; Munoz, N.; Cottam, J. A.; Zucker, J.D.; Kumar, N.; Nicora C. D.; Mitchell H. D.; Kim Y.; Nelson W. C.; Egbert R. G. "Resource reallocation in engineered Escherichia coli strains with reduced genomes" bioRxiv 2020.10.19.346155 (2020); doi: https://doi.org/10.1101/2020.10.19.346155
  • Siriwardane, E.; Joshi, R.; Kumar, N.; and Cakir, D. “Machine Learning and DFT Prediction of Formation/Exfoliation Energy and Structure Correlation of MAB Phases.” ACS Appl. Mater. Interfaces 2020, 26 (12), 29424-29431.


  • Kumar, N.; Bucher, D.; Kozlowski, P. M. “Reaction Mechanism for the Initial Step of B12-Dependent Methylmalonyl CoA Mutase” Journal of Physical Chemistry B  2019, 123, 2210-2216 .
  • Pegis, M. L.; Martin, D. J.; Wise, C. F.; Brezny, A. C.; Johnson, S. I.; Johnson, L. E.; Kumar, N.; Raugei, S.; Mayer, J. M. “Mechanism of Catalytic O2 Reduction by Iron Tetraphenylporphyrin” J. Am. Chem. Soc. 2019 141 (20), 8315-8326.
  • Cannon, W., Britton, S., Zucker, J., Baxter, D., Kumar, N., et. al (2018). “Prediction of Metabolite Concentrations Using Maximum Entropy-Based Simulations with Application to Central Metabolism of Neurospora crassa” Biophysical Journal, 2019, 116(3), 130.
  • Kumar, N.; Darmon, J.; Weiss, C.; Helm, M.; Raugei, S.; Bullock, M. R. “Outer Coordination Sphere Proton Relay Base and Proximity Effects on Hydrogen Oxidation with Iron Electrocatalysts” Organometallics, 2019. DOI:10.1021/acs.organomet.8b00805 
  • Hurley, J. M.; Jankowski, M. S.; Crowell, A.; Fordyce, S.; Zucker, J. D.; Kumar, N.; De Los Santos, H.; Purvine, S.; Robinson, E.; Shukla, A.; Zink, E.; Cannon, W. R.; Baker, S.; Loros, J. J.; Dunlap, J. C., Circadian proteomic analysis uncovers mechanisms of post-transcriptional regulation in metabolic pathways. Cell Systems 2018, 7, 613-626.


  • Smallwood, C. R., Chen J-H, Kumar, N., Chrisler, W. B., Purvine, S. O., Kyle, J. E., Nicora. C. D., Boudreau, R., Ekman, A., Hixson. K. H., Moore, R. J., Mcdermott, G., Cannon, R.,  Evans, J. E. "Integrated systems biology and imaging of the smallest free-living eukaryote" BioRxiv (2018) doi: 10.1101/293704
  • Cannon WR, JD Zucker, DJ Baxter, N Kumar, SE Baker, J Hurley, and JC 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(6):Article No. 63.  doi:10.3390/pr6060063


  • Cardenas AJ, B Ginovska-Pangovska, N Kumar, J Hou, S Raugei, ML Helm, AM Appel, RM Bullock, and MJ O'Hagan. 2016. "Controlling Proton Delivery with Catalyst Structural Dynamics." Angewandte Chemie International Edition 55(43):13509-13513. doi:10.1002/anie.201607460
  • Pegis ML, BA McKeown, N Kumar, K Lang, DJ Wasylenko, P Zhang, S Raugei, and JM Mayer. 2016. "Homogenous Electrocatalytic Oxiygen Reduction Rates Correlate with Reaction Overpotential in Acidic Organic Solutions." ACS Central Science 2(11):850-856. doi:10.1021/acscentsci.6b00261
  • Brady, G; Kumar, N.; Jaworska, M.; Lodowski, P.; Kozlowski, P. M. “Electronically Excited States of Cob(II)alamin: Insights from CASSCF/XMCQDPT2 and TD-DFT Calculations” Phys. Chem. Chem. Phys., 2016, 18, 4513-4526.


  • Hulley E, N Kumar, S Raugei, and RM Bullock. 2015. "Manganese-Based Molecular Electrocatalysts for Oxidation of Hydrogen." ACS Catalysis 5(11):6838-6847. doi:10.1021/acscatal.5b01751
  • Darmon JM, N Kumar, E Hulley, CJ Weiss, S Raugei, RM Bullock, and ML 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(5):2737-2745.  doi:10.1039/C5SC00398A (Selected as cover page for the journal).


  • Kumar N, DM Camaioni, M Dupuis, S Raugei, and AM Appel. 2014. "Mechanistic Insights into Hydride Transfer for Catalytic Hydrogenation of CO2 with Cobalt Complexes." Dalton Transactions 43(31):11803-11806.  doi:10.1039/c4dt01551g (Selected as cover page for the journal).
  • Kumar, N.; Kozlowski, P. M. “Mechanistic Insights for the formation of organometallic Co-C bond in the reaction catalyzed by methionine synthase” J. Phys. Chem. B2013117, 16044-16057.
  • Kumar, N. Camaioni, D. M., Dupuis, M., Raugei S., Appel, A. M. “Inside Front Cover for Mechanistic Insights into Hydride Transfer for Catalytic Hydrogenation of CO2 with Cobalt Complexes” Dalton Trans., 2014, 43, 11770.


  • Kumar, N.; Kuta, J.; Galezowski, W.; Kozlowski, P. M. “One-Electron-Oxidized Form of the Methylcobalamin Cofactor: Spin Density Distribution and Pseudo-Jahn-Teller Effect” Inor. Chem. 2013, 52, 1762-1771.
  • Koziol, L.; Kumar, N.; Wong, E. S.; Lightstone, F. C. “Molecular recognition of aromatic rings by flavin: electrostatics and dispersion determine ring positioning above isoalloxazine” J. Phys. Chem. A, 2013, 117, 12946-12952.
  • Kumar, N.; Kozlowski, P. M. “Mechanistic Insights for the formation of organometallic Co-C bond in the reaction catalyzed by methionine synthase” J. Phys. Chem. B2013117, 16044-16057.
  • Kornobis, K.; Kumar, N.; Wong, B. M.; Jaworska, M.; Lodowski, P.; Kozlowski, P. M. “Electronic Structure of S1 State in Methylcobalamin: Benchmark Analysis Including CASSCF/MC-XQDPT2, EOM-CCSD and TD-DFT Calculations” J. Comput. Chem. 2013, 44, 1987-1004.
  • Kumar, N.; Liu S. B.; Kozlowski, P.M. “Charge Separation Propensity of the Coenzyme B12–Tyrosine Complex in Adenosylcobalamin-Dependent Methylmalonyl–CoA Mutase Enzyme” J. Phys. Chem. Letters 2012, 3, 1035-1038.


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