Erik Nordquist

Erik Nordquist

Postdoctoral Research Fellow Alex MacKerell Group University of Maryland, Baltimore

Publications


    Peer-reviewed Research Articles

    2024

  1. Nordquist E#, Zhang M#, Kumar A, MacKerell A. Combined physics- and machine-learning-based method to identify druggable binding sites using SILCS-Hotspots. J. Chem. Inf. Model. 2024 (submitted) chemRxiv DOI: 10.26434/chemrxiv-2024-hrqq9
  2. Nordquist E, Jia Z, Chen J. Small molecule NS11021 promotes BK channel activation by increasing inner pore hydration. J. Chem. Inf. Model. 2024 (submitted) bioRxiv DOI: 10.1101/2024.06.03.597166

    3. 2023

  3. Nordquist E#, Zhang G#, Barethiya S, Ji N, White K, Han L, Jia Z, Shi J, Cui J, and Chen J. Incorporating physics to overcome data scarcity in predictive modeling of protein function: a case study of BK channels. PLOS Comput. Biol. 2023 19(9): e1011460. DOI: 10.1371/journal.pcbi.1011460
  4. Nordquist E, Jia Z, Chen J. Inner pore hydration free energy controls the activation of big potassium channels. Biophys. J. 2023, 122, 1158-1167. DOI: 10.1016/j.bpj.2023.02.005 (Best of BJ 2023 issue!)

    5. 2022

  5. Nordquist E#, Schultz S#, Chen J. Using metadynamics to explore the free energy of dewetting in biologically-relevant nanopores. J. Phys. Chem. B 2022, 126 (34), 6428-6437 DOI: 10.1021/acs.jpcb.2c04157

    6. 2021

  6. Nordquist E, English C, Clerico E, Sherman W, Gierasch L, and Chen J. Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones. PLOS Comput. Biol., 2021, 17 (11): e1009567. DOI: 10.1371/journal.pcbi.1009567 PubMed

    7. 2020

  7. Gong X, Chiricotto M, Liu X, Nordquist E, Feig M, Brooks C, Chen J. Accelerating the generalized born with molecular volume and solvent accessible surface area implicit solvent model using graphics processing units. J. Comput. Chem., 2020, 41, 830–838. DOI: 10.1002/jcc.26133 PubMed

#These authors contributed equally to the work.

    Review Articles and Book Chapters

  1. Zhang L#, Barethiya S#, Nordquist E, Chen J. Machine Learning Generation of Dynamic Protein Conformational Ensembles. Molecules 2023, 28(10), 4047. DOI: 10.3390/molecules28104047
  2. Nordquist E, Clerico E, Chen J, Gierasch L. Computationally-aided modeling of Hsp70-client interactions: past, present, and future. J. Phys. Chem. B, 2022, 126 (36), 6780–6791 DOI: 10.1021/acs.jpcb.2c03806