Maximum-Score Diversity Selection for Early Drug Discovery

Meinl, Thorsten; Ostermann, Claude; Berthold, Michael R.

Maximum-Score Diversity Selection for Early Drug Discovery

Files

Meinl.pdf(4.54 MB)

Date

2011

Authors

Meinl, Thorsten

Ostermann, Claude

Berthold, Michael R.

Publication type

Journal article

Published in

Journal of Chemical Information and Modeling ; 51 (2011), 2. - pp. 237-247. - ISSN 1549-9596. - eISSN 1549-960X

Abstract

Diversity selection is a common task in early drug discovery. One drawback of current approaches is that usually only the structural diversity is taken into account and activity information is ignored. In this article we present a modified version of diversity selection - which we term "Maximum-Score Diversity Selection" - that additionally takes the estimated or predicted activities of the molecules into account. We show that finding an optimal solution to this problem is computationally very expensive (it is NP-hard) and therefore heuristic approaches are needed.
After a discussion of existing approaches we present our new method which is computationally far more efficient but at the same time produces comparable results. We conclude by validating these theoretical differences on several datasets.

Subject (DDC)

004 Computer Science

Keywords

Heuristik,Teilmengenauswahl

Cite This

ISO 690

MEINL, Thorsten, Claude OSTERMANN, Michael R. BERTHOLD, 2011. Maximum-Score Diversity Selection for Early Drug Discovery. In: Journal of Chemical Information and Modeling. 51(2), pp. 237-247. ISSN 1549-9596. eISSN 1549-960X. Available under: doi: 10.1021/ci100426r

BibTex

@article{Meinl2011-02-28Maxim-12389,
  year={2011},
  doi={10.1021/ci100426r},
  title={Maximum-Score Diversity Selection for Early Drug Discovery},
  number={2},
  volume={51},
  issn={1549-9596},
  journal={Journal of Chemical Information and Modeling},
  pages={237--247},
  author={Meinl, Thorsten and Ostermann, Claude and Berthold, Michael R.}
}

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Bibliography of Konstanz

Yes