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 *

137 related articles for article (PubMed ID: 38232765)

  • 1. Combining Force Fields and Neural Networks for an Accurate Representation of Bonded Interactions.
    Kamath G; Illarionov A; Sakipov S; Pereyaslavets L; Kurnikov IV; Butin O; Voronina E; Ivahnenko I; Leontyev I; Nawrocki G; Darkhovskiy M; Olevanov M; Cherniavskyi YK; Lock C; Greenslade S; Chen Y; Kornberg RD; Levitt M; Fain B
    J Phys Chem A; 2024 Feb; 128(4):807-812. PubMed ID: 38232765
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Benchmarking Force Field and the ANI Neural Network Potentials for the Torsional Potential Energy Surface of Biaryl Drug Fragments.
    Lahey SJ; Thien Phuc TN; Rowley CN
    J Chem Inf Model; 2020 Dec; 60(12):6258-6268. PubMed ID: 33263401
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions.
    Illarionov A; Sakipov S; Pereyaslavets L; Kurnikov IV; Kamath G; Butin O; Voronina E; Ivahnenko I; Leontyev I; Nawrocki G; Darkhovskiy M; Olevanov M; Cherniavskyi YK; Lock C; Greenslade S; Sankaranarayanan SK; Kurnikova MG; Potoff J; Kornberg RD; Levitt M; Fain B
    J Am Chem Soc; 2023 Nov; 145(43):23620-23629. PubMed ID: 37856313
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Toward a general neural network force field for protein simulations: Refining the intramolecular interaction in protein.
    Zhang P; Yang W
    J Chem Phys; 2023 Jul; 159(2):. PubMed ID: 37431910
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Toward Building Protein Force Fields by Residue-Based Systematic Molecular Fragmentation and Neural Network.
    Wang H; Yang W
    J Chem Theory Comput; 2019 Feb; 15(2):1409-1417. PubMed ID: 30550274
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A new force field (ECEPP-05) for peptides, proteins, and organic molecules.
    Arnautova YA; Jagielska A; Scheraga HA
    J Phys Chem B; 2006 Mar; 110(10):5025-44. PubMed ID: 16526746
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory.
    Stylianakis I; Zervos N; Lii JH; Pantazis DA; Kolocouris A
    J Comput Aided Mol Des; 2023 Dec; 37(12):607-656. PubMed ID: 37597063
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Analysis of the conformational profiles of fenamates shows route towards novel, higher accuracy, force-fields for pharmaceuticals.
    Uzoh OG; Galek PT; Price SL
    Phys Chem Chem Phys; 2015 Mar; 17(12):7936-48. PubMed ID: 25720865
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Intermolecular Non-Bonded Interactions from Machine Learning Datasets.
    Chen JA; Chao SD
    Molecules; 2023 Dec; 28(23):. PubMed ID: 38067629
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Explainable Solvation Free Energy Prediction Combining Graph Neural Networks with Chemical Intuition.
    Low K; Coote ML; Izgorodina EI
    J Chem Inf Model; 2022 Nov; 62(22):5457-5470. PubMed ID: 36317829
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Intrinsic Bond Energies from a Bonds-in-Molecules Neural Network.
    Yao K; Herr JE; Brown SN; Parkhill J
    J Phys Chem Lett; 2017 Jun; 8(12):2689-2694. PubMed ID: 28573865
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Study of peptide conformation in terms of the ABEEM/MM method.
    Yang ZZ; Zhang Q
    J Comput Chem; 2006 Jan; 27(1):1-10. PubMed ID: 16235260
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Differentiable Neural-Network Force Field for Ionic Liquids.
    Montes-Campos H; Carrete J; Bichelmaier S; Varela LM; Madsen GKH
    J Chem Inf Model; 2022 Jan; 62(1):88-101. PubMed ID: 34941253
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Development of a polarizable force field for proteins via ab initio quantum chemistry: first generation model and gas phase tests.
    Kaminski GA; Stern HA; Berne BJ; Friesner RA; Cao YX; Murphy RB; Zhou R; Halgren TA
    J Comput Chem; 2002 Dec; 23(16):1515-31. PubMed ID: 12395421
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Inter- and intramolecular potential for the N-formylglycinamide-water system. A comparison between theoretical modeling and empirical force fields.
    Hermida-Ramón JM; Brdarski S; Karlström G; Berg U
    J Comput Chem; 2003 Jan; 24(2):161-76. PubMed ID: 12497597
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.
    Cheng Z; Bi H; Liu S; Chen J; Misquitta AJ; Yu K
    J Chem Theory Comput; 2024 Jul; 20(13):5598-5608. PubMed ID: 38888427
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks.
    Pukrittayakamee A; Malshe M; Hagan M; Raff LM; Narulkar R; Bukkapatnum S; Komanduri R
    J Chem Phys; 2009 Apr; 130(13):134101. PubMed ID: 19355711
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Reverse turns in blocked dipeptides are intrinsically unstable in water.
    Tobias DJ; Sneddon SF; Brooks CL
    J Mol Biol; 1990 Dec; 216(3):783-96. PubMed ID: 2258940
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multipole-Based Force Fields from ab Initio Interaction Energies and the Need for Jointly Refitting All Intermolecular Parameters.
    Kramer C; Gedeck P; Meuwly M
    J Chem Theory Comput; 2013 Mar; 9(3):1499-511. PubMed ID: 26587612
    [TBL] [Abstract][Full Text] [Related]  

  • 20. AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials.
    Glick ZL; Metcalf DP; Koutsoukas A; Spronk SA; Cheney DL; Sherrill CD
    J Chem Phys; 2020 Jul; 153(4):044112. PubMed ID: 32752707
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.