These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1391 related articles for article (PubMed ID: 23832629)

  • 1. CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data.
    Huang J; MacKerell AD
    J Comput Chem; 2013 Sep; 34(25):2135-45. PubMed ID: 23832629
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Further Optimization and Validation of the Classical Drude Polarizable Protein Force Field.
    Lin FY; Huang J; Pandey P; Rupakheti C; Li J; Roux BT; MacKerell AD
    J Chem Theory Comput; 2020 May; 16(5):3221-3239. PubMed ID: 32282198
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles.
    Best RB; Zhu X; Shim J; Lopes PE; Mittal J; Feig M; Mackerell AD
    J Chem Theory Comput; 2012 Sep; 8(9):3257-3273. PubMed ID: 23341755
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Improved Modeling of Halogenated Ligand-Protein Interactions Using the Drude Polarizable and CHARMM Additive Empirical Force Fields.
    Lin FY; MacKerell AD
    J Chem Inf Model; 2019 Jan; 59(1):215-228. PubMed ID: 30418023
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Probing Methyl Group Dynamics in Proteins by NMR Cross-Correlated Dipolar Relaxation and Molecular Dynamics Simulations.
    Ali AAAI; Hoffmann F; Schäfer LV; Mulder FAA
    J Chem Theory Comput; 2022 Dec; 18(12):7722-7732. PubMed ID: 36326619
    [TBL] [Abstract][Full Text] [Related]  

  • 6. CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field.
    Lee J; Cheng X; Swails JM; Yeom MS; Eastman PK; Lemkul JA; Wei S; Buckner J; Jeong JC; Qi Y; Jo S; Pande VS; Case DA; Brooks CL; MacKerell AD; Klauda JB; Im W
    J Chem Theory Comput; 2016 Jan; 12(1):405-13. PubMed ID: 26631602
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Biomolecular force fields: where have we been, where are we now, where do we need to go and how do we get there?
    Dauber-Osguthorpe P; Hagler AT
    J Comput Aided Mol Des; 2019 Feb; 33(2):133-203. PubMed ID: 30506158
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Force field development phase II: Relaxation of physics-based criteria… or inclusion of more rigorous physics into the representation of molecular energetics.
    Hagler AT
    J Comput Aided Mol Des; 2019 Feb; 33(2):205-264. PubMed ID: 30506159
    [TBL] [Abstract][Full Text] [Related]  

  • 9. On the ability of molecular dynamics force fields to recapitulate NMR derived protein side chain order parameters.
    O'Brien ES; Wand AJ; Sharp KA
    Protein Sci; 2016 Jun; 25(6):1156-60. PubMed ID: 26990788
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Force Field for Peptides and Proteins based on the Classical Drude Oscillator.
    Lopes PE; Huang J; Shim J; Luo Y; Li H; Roux B; Mackerell AD
    J Chem Theory Comput; 2013 Dec; 9(12):5430-5449. PubMed ID: 24459460
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Scrutinizing molecular mechanics force fields on the submicrosecond timescale with NMR data.
    Lange OF; van der Spoel D; de Groot BL
    Biophys J; 2010 Jul; 99(2):647-55. PubMed ID: 20643085
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Fitting Force Field Parameters to NMR Relaxation Data.
    Kümmerer F; Orioli S; Lindorff-Larsen K
    J Chem Theory Comput; 2023 Jun; 19(12):3741-3751. PubMed ID: 37276045
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Accuracy of MD solvent models in RNA structure refinement assessed via liquid-crystal NMR and spin relaxation data.
    Bergonzo C; Grishaev A
    J Struct Biol; 2019 Sep; 207(3):250-259. PubMed ID: 31279068
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers.
    Hoffmann F; Mulder FAA; Schäfer LV
    J Chem Phys; 2020 Feb; 152(8):084102. PubMed ID: 32113361
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Experimental verification of force fields for molecular dynamics simulations using Gly-Pro-Gly-Gly.
    Aliev AE; Courtier-Murias D
    J Phys Chem B; 2010 Sep; 114(38):12358-75. PubMed ID: 20825228
    [TBL] [Abstract][Full Text] [Related]  

  • 16. How accurately do force fields represent protein side chain ensembles?
    Petrović D; Wang X; Strodel B
    Proteins; 2018 Sep; 86(9):935-944. PubMed ID: 29790608
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Narrowing the gap between experimental and computational determination of methyl group dynamics in proteins.
    Hoffmann F; Xue M; Schäfer LV; Mulder FAA
    Phys Chem Chem Phys; 2018 Oct; 20(38):24577-24590. PubMed ID: 30226234
    [TBL] [Abstract][Full Text] [Related]  

  • 18. (Ala)(4)-X-(Ala)4 as a model system for the optimization of the χ1 and χ2 amino acid side-chain dihedral empirical force field parameters.
    Shim J; Zhu X; Best RB; MacKerell AD
    J Comput Chem; 2013 Mar; 34(7):593-603. PubMed ID: 23197420
    [TBL] [Abstract][Full Text] [Related]  

  • 19. ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB.
    Maier JA; Martinez C; Kasavajhala K; Wickstrom L; Hauser KE; Simmerling C
    J Chem Theory Comput; 2015 Aug; 11(8):3696-713. PubMed ID: 26574453
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Toward a predictive understanding of slow methyl group dynamics in proteins.
    Long D; Li DW; Walter KF; Griesinger C; Brüschweiler R
    Biophys J; 2011 Aug; 101(4):910-5. PubMed ID: 21843482
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 70.