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Quantum topological QSAR models based on the MOLMAP approach

Bahram Hemmateenejad, Ahmadreza Mehdipour (UGent) and Paul L. A. Popelier
(2008) CHEMICAL BIOLOGY & DRUG DESIGN. 72(6). p.551-563
Author
Organization
Abstract
Quantum topological molecular similarity produces a two-dimensional array of descriptors for each molecule while a three-dimensional array is obtained by placing the descriptor data matrices of a set of molecules beside each other. Here, we use the multiway data analysis method called molecular maps (MOLMAP) of atom-level properties in a new way. We transferred the three-dimensional array of quantum topological molecular similarity descriptors into new two-dimensional parameters using Kohonen networks, followed by partial least squares. Six different data sets were analyzed by the proposed procedure, which were previously analyzed (Eur. J. Med. Chem. 2006 41 862) by partial least squares applied to unfolded data. They include: (i) the pK(a) of imidazoles, (ii) the ability of a set of indole derivatives to displace [H-3] flunitrazepam from binding to bovine cortical membranes, (iii) the inhibitory effect of a set of benzimidazoles on the influenza virus, (iv) the interaction of amides with liver alcohol dehydrogenase, (v) inhibition of carbonic anhydrase by sulfonamides and (vi) the toxicity of a set of chlorophenols. Overall, the results showed better statistical results compared with simple unfolding. Furthermore, variable important in projection plots confirmed previous findings about active centers and even in some cases showed more accurate results.
Keywords
MOLECULAR SIMILARITY DESCRIPTORS, PHENOLIC ANTIOXIDANTS, NEURAL-NETWORK, BOND LENGTHS, DERIVATIVES, PREDICTION, TOXICITY, PLS, CYTOTOXICITY, QSPR, Kohonen network, MOLMAP, QSAR, quantum chemical topology

Citation

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MLA
Hemmateenejad, Bahram, et al. “Quantum Topological QSAR Models Based on the MOLMAP Approach.” CHEMICAL BIOLOGY & DRUG DESIGN, vol. 72, no. 6, 2008, pp. 551–63, doi:10.1111/j.1747-0285.2008.00731.x.
APA
Hemmateenejad, B., Mehdipour, A., & Popelier, P. L. A. (2008). Quantum topological QSAR models based on the MOLMAP approach. CHEMICAL BIOLOGY & DRUG DESIGN, 72(6), 551–563. https://doi.org/10.1111/j.1747-0285.2008.00731.x
Chicago author-date
Hemmateenejad, Bahram, Ahmadreza Mehdipour, and Paul L. A. Popelier. 2008. “Quantum Topological QSAR Models Based on the MOLMAP Approach.” CHEMICAL BIOLOGY & DRUG DESIGN 72 (6): 551–63. https://doi.org/10.1111/j.1747-0285.2008.00731.x.
Chicago author-date (all authors)
Hemmateenejad, Bahram, Ahmadreza Mehdipour, and Paul L. A. Popelier. 2008. “Quantum Topological QSAR Models Based on the MOLMAP Approach.” CHEMICAL BIOLOGY & DRUG DESIGN 72 (6): 551–563. doi:10.1111/j.1747-0285.2008.00731.x.
Vancouver
1.
Hemmateenejad B, Mehdipour A, Popelier PLA. Quantum topological QSAR models based on the MOLMAP approach. CHEMICAL BIOLOGY & DRUG DESIGN. 2008;72(6):551–63.
IEEE
[1]
B. Hemmateenejad, A. Mehdipour, and P. L. A. Popelier, “Quantum topological QSAR models based on the MOLMAP approach,” CHEMICAL BIOLOGY & DRUG DESIGN, vol. 72, no. 6, pp. 551–563, 2008.
@article{8730876,
  abstract     = {{Quantum topological molecular similarity produces a two-dimensional array of descriptors for each molecule while a three-dimensional array is obtained by placing the descriptor data matrices of a set of molecules beside each other. Here, we use the multiway data analysis method called molecular maps (MOLMAP) of atom-level properties in a new way. We transferred the three-dimensional array of quantum topological molecular similarity descriptors into new two-dimensional parameters using Kohonen networks, followed by partial least squares. Six different data sets were analyzed by the proposed procedure, which were previously analyzed (Eur. J. Med. Chem. 2006 41 862) by partial least squares applied to unfolded data. They include: (i) the pK(a) of imidazoles, (ii) the ability of a set of indole derivatives to displace [H-3] flunitrazepam from binding to bovine cortical membranes, (iii) the inhibitory effect of a set of benzimidazoles on the influenza virus, (iv) the interaction of amides with liver alcohol dehydrogenase, (v) inhibition of carbonic anhydrase by sulfonamides and (vi) the toxicity of a set of chlorophenols. Overall, the results showed better statistical results compared with simple unfolding. Furthermore, variable important in projection plots confirmed previous findings about active centers and even in some cases showed more accurate results.}},
  author       = {{Hemmateenejad, Bahram and Mehdipour, Ahmadreza and Popelier, Paul L. A.}},
  issn         = {{1747-0277}},
  journal      = {{CHEMICAL BIOLOGY & DRUG DESIGN}},
  keywords     = {{MOLECULAR SIMILARITY DESCRIPTORS,PHENOLIC ANTIOXIDANTS,NEURAL-NETWORK,BOND LENGTHS,DERIVATIVES,PREDICTION,TOXICITY,PLS,CYTOTOXICITY,QSPR,Kohonen network,MOLMAP,QSAR,quantum chemical topology}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{551--563}},
  title        = {{Quantum topological QSAR models based on the MOLMAP approach}},
  url          = {{http://doi.org/10.1111/j.1747-0285.2008.00731.x}},
  volume       = {{72}},
  year         = {{2008}},
}
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