Abstract：
:In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.
journal_name
J Chem Inf Modeljournal_title
Journal of chemical information and modelingauthors
Yasuo K,Yamaotsu N,Gouda H,Tsujishita H,Hirono Sdoi
10.1021/ci800313hsubject
Has Abstractpub_date
2009-04-01 00:00:00pages
853-64issue
4eissn
1549-9596issn
1549-960Xjournal_volume
49pub_type
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journal_title：Journal of chemical information and modeling
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journal_title：Journal of chemical information and modeling
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journal_title：Journal of chemical information and modeling
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abstract：:Accurate and affordable assessment of ligand-protein affinity for structure-based virtual screening (SB-VS) is a standing challenge. Hence, empirical postdocking filters making use of various types of structure-activity information may prove useful. Here, we introduce one such filter based upon three-dimensional struc...
journal_title：Journal of chemical information and modeling
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journal_title：Journal of chemical information and modeling
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journal_title：Journal of chemical information and modeling
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更新日期：2007-05-01 00:00:00
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journal_title：Journal of chemical information and modeling
pub_type： 杂志文章
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更新日期：2018-04-23 00:00:00
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journal_title：Journal of chemical information and modeling
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更新日期：2017-03-27 00:00:00
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journal_title：Journal of chemical information and modeling
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