LigSeeSVM: Ligand-based virtual Screening using Support Vector Machines and data fusion

Yen Fu Chen, Kai Cheng Hsu, Po Tsun Lin, D. Frank Hsu, Bruce S. Kristal, Jinn Moon Yang

研究成果: 雜誌貢獻文章同行評審

4 引文 斯高帕斯(Scopus)

摘要

Ligand-based in silico drug screening is useful for lead discovery, in particular for those targets without structures. Here, we have developed LigSeeSVM, a ligand-based screening tool using data fusion and Support Vector Machines (SVMs). We used Atom Pair (AP) structure descriptors and Physicochemical (PC) descriptors of compounds to generate SVM-AP and SVM-PC models. Sequentially, the two models were combined using rank-based data fusion to create LigSeeSVM model. LigSeeSVM was evaluated on five data sets. Experimental results show that the performance of LigSeeSVM is better than other ligand-based virtual screening approaches. We believe that LigSeeSVM is useful for lead compounds.
原文英語
頁(從 - 到)274-289
頁數16
期刊International Journal of Computational Biology and Drug Design
4
發行號3
DOIs
出版狀態已發佈 - 7月 2011
對外發佈

ASJC Scopus subject areas

  • 電腦科學應用
  • 藥物發現

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