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Molecular Similarity Searching Using COSMO Screening Charges (COSMO/3PP)

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Computational Life Sciences (CompLife 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3695))

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Abstract

We present a novel approach to define molecular similarity and its application in virtual screening. The algorithm is based on molecular surface properties in combination with a geometric encoding scheme. The molecular surface is described by screening charges calculated via COSMO. COSMO, the COnductor-like Screening MOdel, is a quantum-chemical molecular description originally developed and widely validated for solubilities and partition coefficients of molecules in the liquid state. The screening charges it calculates also define properties relevant to ligand-target binding such as hydrogen-bond donors and acceptors, positive and negative charges and lipophilic moieties from first principles. Encoding of properties is performed by three-point pharmacophores which were found to outperform other approaches. The similarity measure was validated on a dataset derived from the MDL Drug Data Report (MDDR) which comprises five classes of active compounds that are 5HT3 ligands, ACE inhibitors, HMG-CoA reductase inhibitors, PAF antagonists and TXA2 inhibitors. Compared to other approaches, the method presented here compares favorably with respect to the number of active compounds retrieved, finds different active scaffolds and is based on a solid theoretical foundation. Further work will be undertaken in order to find better shape and pharmacophoric feature encoding schemes as well as to make quantitative predictions of bioactivity.

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© 2005 Springer-Verlag Berlin Heidelberg

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Bender, A., Klamt, A., Wichmann, K., Thormann, M., Glen, R.C. (2005). Molecular Similarity Searching Using COSMO Screening Charges (COSMO/3PP). In: R. Berthold, M., Glen, R.C., Diederichs, K., Kohlbacher, O., Fischer, I. (eds) Computational Life Sciences. CompLife 2005. Lecture Notes in Computer Science(), vol 3695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11560500_16

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  • DOI: https://doi.org/10.1007/11560500_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29104-6

  • Online ISBN: 978-3-540-31726-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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