Local Structural Changes, Global Data Views: Graphical Substructure鈭扐ctivity Relationship Trailing

详细信息    查看全文

• 作者：Mathias Wawer ; Ju虉rgen Bajorath
• 刊名：Journal of Medicinal Chemistry
• 出版年：2011
• 出版时间：April 28, 2011
• 年：2011
• 卷：54
• 期：8
• 页码：2944-2951
• 全文大小：999K
• 年卷期：v.54,no.8(April 28, 2011)
• ISSN：1520-4804

文摘

The systematic extraction of structure鈭抋ctivity relationship (SAR) information from large and diverse compound data sets depends on the application of computational analysis methods. Irrespective of the methodological details, the ultimate goal of large-scale SAR analysis is to identify most informative compounds and rationalize structural changes that determine SAR behavior. Such insights provide a basis for further chemical exploration. Herein we introduce the first graphical SAR analysis method that globally organizes large compound data sets on the basis of local structural relationships, hence providing an immediate access to important structural modifications and SAR determinants.