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Prediction of SAMPL4 host–guest binding affinities using funnel metadynamics
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  • 作者:Ya-Wen Hsiao (1)
    P?r S?derhjelm (2)
  • 关键词:Funnel metadynamics ; Binding affinity ; CGENFF ; GAFF ; NAMD
  • 刊名:Journal of Computer-Aided Molecular Design
  • 出版年:2014
  • 出版时间:April 2014
  • 年:2014
  • 卷:28
  • 期:4
  • 页码:443-454
  • 全文大小:
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  • 作者单位:Ya-Wen Hsiao (1)
    P?r S?derhjelm (2)

    1. CVMD Innovative Medicine, AstraZeneca, 431 83, M?lndal, Sweden
    2. Department of Theoretical Chemistry, Lund University, Chemical Center, P.O. Box 124, 221 00, Lund, Sweden
  • ISSN:1573-4951
文摘
Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A?tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et?al. in Proc Natl Acad Sci USA 110:6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding free energy. We apply funnel metadynamics to predict host–guest binding affinities for the cucurbit[7]uril host as part of the SAMPL4 blind challenge. Using total simulation times of 300-00?ns per ligand, we show that the errors due to inadequate sampling are below 1?kcal/mol. However, despite the large investment in terms of computational time, the results compared to experiment are not better than a random guess. As we obtain differences of up to 11?kcal/mol when switching between two commonly used force fields (with automatically generated parameters), we strongly believe that in the pursuit of accurate binding free energies a more careful force-field parametrization is needed to address this type of system.

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