Quantitative comparison of five molecular structure spaces in selecting analogs of chemicals

Subhash C Basak, Brian D Gute, Gregory D. Grunwald

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Five methods for characterizing intermolecular similarity have been used in the selection of analogs for a diverse set of seventy-six compounds. These methods include an atom pair (AP) based similarity measure, three principal component spaces derived from topostructural indices, topochemical indices, the combined set of all (topostructural and topochemical) indices, as well as one structure space consisting of principal components calculated from physicochemical properties. Each method has been used in the selection of sets analogs, ranging from five to forty in number in increments of five, for each of the seventy-six compounds. The degree of overlap of the sets of analogs selected by the five separate methods was analyzed.

Original languageEnglish (US)
Title of host publicationComputation in Modern Science and Engineering - Proceedings of the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007)
Pages544-547
Number of pages4
Edition2
DOIs
StatePublished - Dec 1 2007
EventInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007 - Corfu, Greece
Duration: Sep 25 2007Sep 30 2007

Publication series

NameAIP Conference Proceedings
Number2
Volume963
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

OtherInternational Conference on Computational Methods in Science and Engineering 2007, ICCMSE 2007
CountryGreece
CityCorfu
Period9/25/079/30/07

Keywords

  • Analog selection
  • Atom pairs
  • Molecular graph
  • Molecular similarity
  • Principal components

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    Basak, S. C., Gute, B. D., & Grunwald, G. D. (2007). Quantitative comparison of five molecular structure spaces in selecting analogs of chemicals. In Computation in Modern Science and Engineering - Proceedings of the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007) (2 ed., pp. 544-547). (AIP Conference Proceedings; Vol. 963, No. 2). https://doi.org/10.1063/1.2836136