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Journal Abstract Search

480 related items for PubMed ID: 30265513

  • 1. Reliability of Docking-Based Virtual Screening for GPCR Ligands with Homology Modeled Structures: A Case Study of the Angiotensin II Type I Receptor.
    Chen H, Fu W, Wang Z, Wang X, Lei T, Zhu F, Li D, Chang S, Xu L, Hou T.
    ACS Chem Neurosci; 2019 Jan 16; 10(1):677-689. PubMed ID: 30265513
    [Abstract] [Full Text] [Related]

  • 2. Assessing GPCR homology models constructed from templates of various transmembrane sequence identities: Binding mode prediction and docking enrichment.
    Loo JSE, Emtage AL, Ng KW, Yong ASJ, Doughty SW.
    J Mol Graph Model; 2018 Mar 16; 80():38-47. PubMed ID: 29306746
    [Abstract] [Full Text] [Related]

  • 3. Efficiency of Homology Modeling Assisted Molecular Docking in G-protein Coupled Receptors.
    Bhunia SS, Saxena AK.
    Curr Top Med Chem; 2021 Mar 16; 21(4):269-294. PubMed ID: 32901584
    [Abstract] [Full Text] [Related]

  • 4. Ligand binding determinants for angiotensin II type 1 receptor from computer simulations.
    Matsoukas MT, Cordomí A, Ríos S, Pardo L, Tselios T.
    J Chem Inf Model; 2013 Nov 25; 53(11):2874-83. PubMed ID: 24090110
    [Abstract] [Full Text] [Related]

  • 5. GPCR homology model template selection benchmarking: Global versus local similarity measures.
    Castleman PN, Sears CK, Cole JA, Baker DL, Parrill AL.
    J Mol Graph Model; 2019 Jan 25; 86():235-246. PubMed ID: 30390544
    [Abstract] [Full Text] [Related]

  • 6. Benchmarking GPCR homology model template selection in combination with de novo loop generation.
    Szwabowski GL, Castleman PN, Sears CK, Wink LH, Cole JA, Baker DL, Parrill AL.
    J Comput Aided Mol Des; 2020 Oct 25; 34(10):1027-1044. PubMed ID: 32737667
    [Abstract] [Full Text] [Related]

  • 7. Improving virtual screening of G protein-coupled receptors via ligand-directed modeling.
    Coudrat T, Simms J, Christopoulos A, Wootten D, Sexton PM.
    PLoS Comput Biol; 2017 Nov 25; 13(11):e1005819. PubMed ID: 29131821
    [Abstract] [Full Text] [Related]

  • 8. Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity.
    Jaiteh M, Rodríguez-Espigares I, Selent J, Carlsson J.
    PLoS Comput Biol; 2020 Mar 25; 16(3):e1007680. PubMed ID: 32168319
    [Abstract] [Full Text] [Related]

  • 9. Application of Multiscale Simulation Tools on GPCRs. An Example with Angiotensin II Type 1 Receptor.
    Erol I, Aksoydan B, Kantarcioglu I, Durdagi S.
    Methods Mol Biol; 2018 Mar 25; 1824():431-448. PubMed ID: 30039423
    [Abstract] [Full Text] [Related]

  • 10. Docking and Virtual Screening Strategies for GPCR Drug Discovery.
    Beuming T, Lenselink B, Pala D, McRobb F, Repasky M, Sherman W.
    Methods Mol Biol; 2015 Mar 25; 1335():251-76. PubMed ID: 26260606
    [Abstract] [Full Text] [Related]

  • 11. Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?
    Kapla J, Rodríguez-Espigares I, Ballante F, Selent J, Carlsson J.
    PLoS Comput Biol; 2021 May 25; 17(5):e1008936. PubMed ID: 33983933
    [Abstract] [Full Text] [Related]

  • 12. A benchmarking study on virtual ligand screening against homology models of human GPCRs.
    Lim VJY, Du W, Chen YZ, Fan H.
    Proteins; 2018 Sep 25; 86(9):978-989. PubMed ID: 30051928
    [Abstract] [Full Text] [Related]

  • 13. The impact of molecular dynamics sampling on the performance of virtual screening against GPCRs.
    Tarcsay A, Paragi G, Vass M, Jójárt B, Bogár F, Keserű GM.
    J Chem Inf Model; 2013 Nov 25; 53(11):2990-9. PubMed ID: 24116387
    [Abstract] [Full Text] [Related]

  • 14. Current assessment of docking into GPCR crystal structures and homology models: successes, challenges, and guidelines.
    Beuming T, Sherman W.
    J Chem Inf Model; 2012 Dec 21; 52(12):3263-77. PubMed ID: 23121495
    [Abstract] [Full Text] [Related]

  • 15. From heptahelical bundle to hits from the Haystack: structure-based virtual screening for GPCR ligands.
    Kooistra AJ, Roumen L, Leurs R, de Esch IJ, de Graaf C.
    Methods Enzymol; 2013 Dec 21; 522():279-336. PubMed ID: 23374191
    [Abstract] [Full Text] [Related]

  • 16. Evaluating the performance of MM/PBSA for binding affinity prediction using class A GPCR crystal structures.
    Yau MQ, Emtage AL, Chan NJY, Doughty SW, Loo JSE.
    J Comput Aided Mol Des; 2019 May 21; 33(5):487-496. PubMed ID: 30989574
    [Abstract] [Full Text] [Related]

  • 17. Template selection and refinement considerations for modelling aminergic GPCR-ligand complexes.
    Urmi KF, Finch AM, Griffith R.
    J Mol Graph Model; 2017 Sep 21; 76():488-503. PubMed ID: 28818718
    [Abstract] [Full Text] [Related]

  • 18. GPCR Homology Model Generation for Lead Optimization.
    Tautermann CS.
    Methods Mol Biol; 2018 Sep 21; 1705():115-131. PubMed ID: 29188560
    [Abstract] [Full Text] [Related]

  • 19. Critical analysis of the successes and failures of homology models of G protein-coupled receptors.
    Bhattacharya S, Lam AR, Li H, Balaraman G, Niesen MJ, Vaidehi N.
    Proteins; 2013 May 21; 81(5):729-39. PubMed ID: 23042299
    [Abstract] [Full Text] [Related]

  • 20. Dopamine D3 receptor antagonist reveals a cryptic pocket in aminergic GPCRs.
    Ferruz N, Doerr S, Vanase-Frawley MA, Zou Y, Chen X, Marr ES, Nelson RT, Kormos BL, Wager TT, Hou X, Villalobos A, Sciabola S, De Fabritiis G.
    Sci Rep; 2018 Jan 17; 8(1):897. PubMed ID: 29343833
    [Abstract] [Full Text] [Related]

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