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 *

183 related articles for article (PubMed ID: 37609301)

  • 1. Approximating conformational Boltzmann distributions with AlphaFold2 predictions.
    Brown BP; Stein RA; Meiler J; Mchaourab H
    bioRxiv; 2023 Aug; ():. PubMed ID: 37609301
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Approximating Projections of Conformational Boltzmann Distributions with AlphaFold2 Predictions: Opportunities and Limitations.
    Brown BP; Stein RA; Meiler J; Mchaourab HS
    J Chem Theory Comput; 2024 Feb; 20(3):1434-1447. PubMed ID: 38215214
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Interpretable Atomistic Prediction and Functional Analysis of Conformational Ensembles and Allosteric States in Protein Kinases Using AlphaFold2 Adaptation with Randomized Sequence Scanning and Local Frustration Profiling.
    Raisinghani N; Alshahrani M; Gupta G; Tian H; Xiao S; Tao P; Verkhivker G
    bioRxiv; 2024 Feb; ():. PubMed ID: 38496487
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Estimating conformational heterogeneity of tryptophan synthase with a template-based Alphafold2 approach.
    Casadevall G; Duran C; Estévez-Gay M; Osuna S
    Protein Sci; 2022 Oct; 31(10):e4426. PubMed ID: 36173176
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sampling alternative conformational states of transporters and receptors with AlphaFold2.
    Del Alamo D; Sala D; Mchaourab HS; Meiler J
    Elife; 2022 Mar; 11():. PubMed ID: 35238773
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Investigating the conformational landscape of AlphaFold2-predicted protein kinase structures.
    Al-Masri C; Trozzi F; Lin SH; Tran O; Sahni N; Patek M; Cichonska A; Ravikumar B; Rahman R
    Bioinform Adv; 2023; 3(1):vbad129. PubMed ID: 37786533
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Exploring kinase DFG loop conformational stability with AlphaFold2-RAVE.
    Vani BP; Aranganathan A; Tiwary P
    ArXiv; 2023 Sep; ():. PubMed ID: 37731662
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Methods for Efficiently and Accurately Computing Quantum Mechanical Free Energies for Enzyme Catalysis.
    Kearns FL; Hudson PS; Boresch S; Woodcock HL
    Methods Enzymol; 2016; 577():75-104. PubMed ID: 27498635
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Exploring Kinase Asp-Phe-Gly (DFG) Loop Conformational Stability with AlphaFold2-RAVE.
    Vani BP; Aranganathan A; Tiwary P
    J Chem Inf Model; 2024 Apr; 64(7):2789-2797. PubMed ID: 37981824
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prediction of Inter-residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning.
    Zhang F; Li Z; Zhao K; Zhao P; Zhang G
    IEEE/ACM Trans Comput Biol Bioinform; 2024 Jun; PP():. PubMed ID: 38857126
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Rosetta Energy Analysis of AlphaFold2 models: Point Mutations and Conformational Ensembles.
    Stein RA; Mchaourab HS
    bioRxiv; 2024 Jan; ():. PubMed ID: 37732281
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Exploring AlphaFold2's Performance on Predicting Amino Acid Side-Chain Conformations and Its Utility in Crystal Structure Determination of B318L Protein.
    Zhao H; Zhang H; She Z; Gao Z; Wang Q; Geng Z; Dong Y
    Int J Mol Sci; 2023 Feb; 24(3):. PubMed ID: 36769074
    [TBL] [Abstract][Full Text] [Related]  

  • 13.
    Fossat MJ; Pappu RV
    J Phys Chem B; 2019 Aug; 123(32):6952-6967. PubMed ID: 31362509
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Co-evolutionary distance predictions contain flexibility information.
    Schwarz D; Georges G; Kelm S; Shi J; Vangone A; Deane CM
    Bioinformatics; 2021 Dec; 38(1):65-72. PubMed ID: 34383892
    [TBL] [Abstract][Full Text] [Related]  

  • 15. High-throughput prediction of protein conformational distributions with subsampled AlphaFold2.
    Monteiro da Silva G; Cui JY; Dalgarno DC; Lisi GP; Rubenstein BM
    Nat Commun; 2024 Mar; 15(1):2464. PubMed ID: 38538622
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Structural validation and assessment of AlphaFold2 predictions for centrosomal and centriolar proteins and their complexes.
    van Breugel M; Rosa E Silva I; Andreeva A
    Commun Biol; 2022 Apr; 5(1):312. PubMed ID: 35383272
    [TBL] [Abstract][Full Text] [Related]  

  • 17. AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design.
    Casadevall G; Duran C; Osuna S
    JACS Au; 2023 Jun; 3(6):1554-1562. PubMed ID: 37388680
    [TBL] [Abstract][Full Text] [Related]  

  • 18. AlphaFold2 models indicate that protein sequence determines both structure and dynamics.
    Guo HB; Perminov A; Bekele S; Kedziora G; Farajollahi S; Varaljay V; Hinkle K; Molinero V; Meister K; Hung C; Dennis P; Kelley-Loughnane N; Berry R
    Sci Rep; 2022 Jun; 12(1):10696. PubMed ID: 35739160
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties.
    Sala D; Hildebrand PW; Meiler J
    Front Mol Biosci; 2023; 10():1121962. PubMed ID: 36876042
    [TBL] [Abstract][Full Text] [Related]  

  • 20. AlphaFold2: A versatile tool to predict the appearance of functional adaptations in evolution: Profilin interactions in uncultured Asgard archaea: Profilin interactions in uncultured Asgard archaea.
    Ponlachantra K; Suginta W; Robinson RC; Kitaoku Y
    Bioessays; 2023 Feb; 45(2):e2200119. PubMed ID: 36461738
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.