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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

310 related items for PubMed ID: 31463704

  • 21.
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  • 22. D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.
    Gaieb Z, Parks CD, Chiu M, Yang H, Shao C, Walters WP, Lambert MH, Nevins N, Bembenek SD, Ameriks MK, Mirzadegan T, Burley SK, Amaro RE, Gilson MK.
    J Comput Aided Mol Des; 2019 Jan; 33(1):1-18. PubMed ID: 30632055
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  • 24. Alchemical Grid Dock (AlGDock) calculations in the D3R Grand Challenge 3 : Binding free energies between flexible ligands and rigid receptors.
    Xie B, Minh DDL.
    J Comput Aided Mol Des; 2019 Jan; 33(1):61-69. PubMed ID: 30084078
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  • 25. Affinity prediction using deep learning based on SMILES input for D3R grand challenge 4.
    Lim S, Lee YO, Yoon J, Kim YJ.
    J Comput Aided Mol Des; 2022 Mar; 36(3):225-235. PubMed ID: 35314897
    [Abstract] [Full Text] [Related]

  • 26. Performance evaluation of molecular docking and free energy calculations protocols using the D3R Grand Challenge 4 dataset.
    Elisée E, Gapsys V, Mele N, Chaput L, Selwa E, de Groot BL, Iorga BI.
    J Comput Aided Mol Des; 2019 Dec; 33(12):1031-1043. PubMed ID: 31677003
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  • 28. Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight.
    Xu X, Ma Z, Duan R, Zou X.
    J Comput Aided Mol Des; 2019 Mar; 33(3):367-374. PubMed ID: 30689079
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  • 29. Performance of HADDOCK and a simple contact-based protein-ligand binding affinity predictor in the D3R Grand Challenge 2.
    Kurkcuoglu Z, Koukos PI, Citro N, Trellet ME, Rodrigues JPGLM, Moreira IS, Roel-Touris J, Melquiond ASJ, Geng C, Schaarschmidt J, Xue LC, Vangone A, Bonvin AMJJ.
    J Comput Aided Mol Des; 2018 Jan; 32(1):175-185. PubMed ID: 28831657
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  • 30.
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  • 31. Blinded evaluation of cathepsin S inhibitors from the D3RGC3 dataset using molecular docking and free energy calculations.
    Chaput L, Selwa E, Elisée E, Iorga BI.
    J Comput Aided Mol Des; 2019 Jan; 33(1):93-103. PubMed ID: 30206740
    [Abstract] [Full Text] [Related]

  • 32. Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2.
    Baumgartner MP, Evans DA.
    J Comput Aided Mol Des; 2018 Jan; 32(1):45-58. PubMed ID: 29127581
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  • 33.
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  • 34. Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study.
    Réau M, Langenfeld F, Zagury JF, Montes M.
    J Comput Aided Mol Des; 2018 Jan; 32(1):231-238. PubMed ID: 28913743
    [Abstract] [Full Text] [Related]

  • 35. Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations.
    Mey ASJS, Jiménez JJ, Michel J.
    J Comput Aided Mol Des; 2018 Jan; 32(1):199-210. PubMed ID: 29134431
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  • 37.
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  • 38. Exploring fragment-based target-specific ranking protocol with machine learning on cathepsin S.
    Yang Y, Lu J, Yang C, Zhang Y.
    J Comput Aided Mol Des; 2019 Dec; 33(12):1095-1105. PubMed ID: 31729618
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  • 39.
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  • 40. Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4.
    Wang B, Ng HL.
    J Comput Aided Mol Des; 2020 Feb; 34(2):201-217. PubMed ID: 31916049
    [Abstract] [Full Text] [Related]

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