Search Results - "McKiernan, Keri A"

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  1. 1

    Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15 by Wang, Lee-Ping, McKiernan, Keri A, Gomes, Joseph, Beauchamp, Kyle A, Head-Gordon, Teresa, Rice, Julia E, Swope, William C, Martínez, Todd J, Pande, Vijay S

    Published in The journal of physical chemistry. B (27-04-2017)
    “…The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical…”
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    Journal Article
  2. 2

    Modeling the mechanism of CLN025 beta-hairpin formation by McKiernan, Keri A, Husic, Brooke E, Pande, Vijay S

    Published in The Journal of chemical physics (14-09-2017)
    “…Beta-hairpins are substructures found in proteins that can lend insight into more complex systems. Furthermore, the folding of beta-hairpins is a valuable test…”
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    Journal Article
  3. 3

    Dynamical model of the CLC-2 ion channel reveals conformational changes associated with selectivity-filter gating by McKiernan, Keri A, Koster, Anna K, Maduke, Merritt, Pande, Vijay S

    Published in PLoS computational biology (01-03-2020)
    “…This work reports a dynamical Markov state model of CLC-2 "fast" (pore) gating, based on 600 microseconds of molecular dynamics (MD) simulation. In the…”
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    Journal Article
  4. 4

    Markov modeling reveals novel intracellular modulation of the human TREK-2 selectivity filter by Harrigan, Matthew P., McKiernan, Keri A., Shanmugasundaram, Veerabahu, Denny, Rajiah Aldrin, Pande, Vijay S.

    Published in Scientific reports (04-04-2017)
    “…Two-pore domain potassium (K2P) channel ion conductance is regulated by diverse stimuli that directly or indirectly gate the channel selectivity filter (SF)…”
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    Journal Article
  5. 5

    Development and validation of a potent and specific inhibitor for the CLC-2 chloride channel by Koster, Anna K., Reese, Austin L., Kuryshev, Yuri, Wen, Xianlan, McKiernan, Keri A., Gray, Erin E., Wu, Caiyun, Huguenard, John R., Maduke, Merritt, Du Bois, J.

    “…CLC-2 is a voltage-gated chloride channel that is widely expressed in mammalian tissues. In the central nervous system, CLC-2 appears in neurons and glia…”
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    Journal Article
  6. 6

    Training and Validation of a Liquid-Crystalline Phospholipid Bilayer Force Field by McKiernan, Keri A, Wang, Lee-Ping, Pande, Vijay S

    Published in Journal of chemical theory and computation (13-12-2016)
    “…We present a united-atom model (gb-fb15) for the molecular dynamics simulation of hydrated liquid-crystalline dipalmitoylphosphatidylcholine (DPPC)…”
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    Journal Article
  7. 7

    A Minimum Variance Clustering Approach Produces Robust and Interpretable Coarse-Grained Models by Husic, Brooke E, McKiernan, Keri A, Wayment-Steele, Hannah K, Sultan, Mohammad M, Pande, Vijay S

    Published in Journal of chemical theory and computation (13-02-2018)
    “…Markov state models (MSMs) are a powerful framework for the analysis of molecular dynamics data sets, such as protein folding simulations, because of their…”
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    Journal Article
  8. 8

    Pressure-induced crystallization of amorphous red phosphorus by Rissi, Erin N., Soignard, Emmanuel, McKiernan, Keri A., Benmore, Chris. J., Yarger, Jeffery L.

    Published in Solid state communications (01-03-2012)
    “…Structural transitions in amorphous red phosphorus were studied at ambient temperature and pressures up to 12 GPa. Amorphous (red) phosphorus was observed to…”
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    Journal Article
  9. 9
  10. 10

    Improving and Applying Atomistic Simulation to Study Biophysical Conformational Dynamics by McKiernan, Keri A

    Published 01-01-2018
    “…Models are tools used to interpret and draw conclusions from nature. Molecular dynamics (MD) simulation is a powerful technique for modeling complex atomistic…”
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    Dissertation
  11. 11

    Classical Quantum Optimization with Neural Network Quantum States by Gomes, Joseph, McKiernan, Keri A, Eastman, Peter, Pande, Vijay S

    Published 23-10-2019
    “…The classical simulation of quantum systems typically requires exponential resources. Recently, the introduction of a machine learning-based wavefunction…”
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    Journal Article
  12. 12

    Automated quantum programming via reinforcement learning for combinatorial optimization by McKiernan, Keri A, Davis, Erik, Alam, M. Sohaib, Rigetti, Chad

    Published 21-08-2019
    “…We develop a general method for incentive-based programming of hybrid quantum-classical computing systems using reinforcement learning, and apply this to solve…”
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    Journal Article