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Structural Diversity of Biologically Interesting Datasets: a Scaffold Analysis Approach by Varun Khanna; Shoba Ranganathan is a Computer Science article available to read on EtoBox.
What is Structural Diversity of Biologically Interesting Datasets: a Scaffold Analysis Approach about?
## Background The recent public availability of the human metabolome and natural product datasets has revitalized "metabolite-likeness" and "natural product-likeness" as a drug design concept to design lead libraries targeting specific pathways. Many reports have analyzed the physicochemical property space of biologically important datasets, with only a few comprehensively characterizing the scaffold diversity in public datasets of biological interest. With large collections of high quality public data currently available, we carried out a comparative analysis of current day leads with other biologically relevant datasets. ## Results In this study, we note a two-fold enrichment of metabolite scaffolds in drug dataset (42%) as compared to currently used lead libraries (23%). We also note that only a small percentage (5%) of natural product scaffolds space is shared by the lead dataset. We have identified specific scaffolds that are present in metabolites and natural products, with close counterparts in the drugs, but are missing in the lead dataset. To determine the distribution of compounds in physicochemical property space we analyzed the __molecular polar surface area__, the __mo
Who reads Structural Diversity of Biologically Interesting Datasets: a Scaffold Analysis Approach?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Varun Khanna; Shoba Ranganathan
- Publisher
- BioMed Central; Springer (Biomed Central Ltd.); Chemistry Central; London: Chemistry Central Ltd. in association with BioMed Central, 2009-; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 1758-2946)
- Published
- 2011
- Language
- EN
- Field
- Computer Science (Physical Sciences)