A new 3D molecular structure representation using quantum topology with application to structure-property relationships

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Alsberg:2000:CILS,
  author =       "Bjorn K. Alsberg and Nathalie Marchand-Geneste and 
                 Ross D. King",
  title =        "A new {3D} molecular structure representation using
                 quantum topology with application to structure-property
                 relationships",
  journal =      "Chemometrics and Intelligent Laboratory Systems",
  year =         "2000",
  volume =       "54",
  pages =        "75--91",
  number =       "2",
  keywords =     "genetic algorithms, genetic programming, Structure
                 representation using quantum topology, StruQT,
                 Quantitative structure-activity relationships, QSAR,
                 Quantitative structure-property relationships, QSPR,
                 Atoms in molecules, AIM, Quantum chemistry, Bader
                 theory, Multivariate analysis, Partial least squares
                 regression, 3D structure representation, Variable
                 selection",
  ISSN =         "0169-7439",
  owner =        "wlangdon",
  URL =          "http://www.sciencedirect.com/science/article/B6TFP-426XTF7-1/2/36265a259de8f80d4918ee6612612218",
  DOI =          "doi:10.1016/S0169-7439(00)00101-5",
  abstract =     "We present a new 3D molecular structure representation
                 based on Richard F.W. Bader's quantum topological atoms
                 in molecules (AIM) theory for use in quantitative
                 structure-property/activity relationship (QSPR/QSAR)
                 modelling. Central to this structure representation
                 using quantum topology (StruQT) are critical points
                 located on the electron density distribution of the
                 molecules. Other gradient fields such as the Laplacian
                 of the electron density distribution can also be used.
                 The type of critical point of particular interest is
                 the bond critical point (BCP) which is here
                 characterised by using the following three parameters:
                 electron density [rho], the Laplacian [nabla]2[rho] and
                 the ellipticity [epsi]. This representation has the
                 advantage that there is no need to probe a large number
                 of lattice points in 3D space to capture the important
                 parts of the 3D electronic structure as is necessary
                 in, e.g. comparative field analysis (CoMFA).

                 We tested the new structure representation by
                 predicting the wavelength of the lowest UV transition
                 for a system of 18 anthocyanidins. Different
                 quantitative structure-property relationship (QSPR)
                 models are constructed using several
                 chemometric/machine learning methods such as standard
                 partial least squares regression (PLS), truncated PLS
                 variable selection, genetic algorithm-based variable
                 selection and genetic programming (GP). These models
                 identified bonds that either take part in decreasing or
                 increasing the dominant excitation wavelength. The
                 models also correctly emphasised on the involvement of
                 the conjugated [pi] system for predicting the
                 wavelength through flagging the BCP ellipticity
                 parameters as important for this particular data set.",
}

Genetic Programming entries for Bjorn K Alsberg Nathalie Marchand-Geneste Ross D King

Citations