Bernard R Brooks, Ph.D.

Affiliations: 
National Heart, Lung, and Blood Institute National Institutes of Health, Bethesda, MD 
Area:
Computational Biophysics
Website:
http://www.lobos.nih.gov/cbs/
Google:
"Bernard Brooks"
Bio:

Chief, Laboratory of Computational Biology

Mean distance: 7.69
 
SNBCP
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Publications

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Krämer A, Pickard FC, Huang J, et al. (2019) Interactions of Water and Alkanes: Modifying Additive Force Fields to Account for Polarization Effects. Journal of Chemical Theory and Computation
König G, Brooks BR, Thiel W, et al. (2018) On the convergence of multi-scale free energy simulations. Molecular Simulation. 44: 1062-1081
König G, Pickard FC, Huang J, et al. (2018) A Comparison of QM/MM Simulations with and without the Drude Oscillator Model Based on Hydration Free Energies of Simple Solutes. Molecules (Basel, Switzerland). 23
Prasad S, Huang J, Zeng Q, et al. (2018) An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge. Journal of Computer-Aided Molecular Design
Hudson PS, Han K, Woodcock HL, et al. (2018) Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale. Journal of Computer-Aided Molecular Design
Tofoleanu F, Yuan Y, Pickard FC, et al. (2018) Structural Modulation of Human Amylin Protofilaments by Naturally-Occurring Mutations. The Journal of Physical Chemistry. B
Leonard AN, Simmonett AC, Pickard FC, et al. (2017) Comparison of Additive and Polarizable Models with Explicit Treatment of Long-Range Lennard-Jones Interactions using Alkane Simulations. Journal of Chemical Theory and Computation
Huang J, Simmonett AC, Pickard FC, et al. (2017) Mapping the Drude polarizable force field onto a multipole and induced dipole model. The Journal of Chemical Physics. 147: 161702
Wang M, Li P, Jia X, et al. (2017) An Efficient Strategy for the Calculation of Solvation Free Energies in Water and Chloroform at the Quantum Mechanical/Molecular Mechanical Level. Journal of Chemical Information and Modeling
Li Y, Li H, Pickard FC, et al. (2017) Machine Learning Force Field Parameters from Ab Initio Data. Journal of Chemical Theory and Computation
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