國家衛生研究院 NHRI:Item 3990099045/12232
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    題名: Logistic regression method for ligand discovery
    作者: Chen, C;Wang, HY
    貢獻者: Institute of Population Health Sciences
    摘要: Protein-based virtual screening is integral to the modern drug discovery process. Most protein-based virtual screening experiments are performed using docking programs. The accuracy of a docking program strongly relies on the incorporated scoring function used, which is based on various energy terms. The existing scoring functions deal with the energy terms that use the equal weight function or other weight functions, which do not depend on characteristics of the protein. To improve the existing methods, Lu and Wang proposed a protein-specific scoring function based on a regression analysis that was shown to have higher performance than the existing methods. In this study, we propose a protein-specific scoring approach to select potential ligands based on logistic regression analysis. The performance of our method was evaluated using the Directory of Useful Decoys docked data set, which contains 40 protein targets. The results showed that the proposed method can increase the enrichment factors for most of the 40 protein targets.
    日期: 2020-06
    關聯: Journal of Computational Biology. 2020 Jun;27(6): 934-940.
    Link to: http://dx.doi.org/10.1089/cmb.2019.0232
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1066-5277&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000487270600001
    顯示於類別:[其他] 期刊論文

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