2 research outputs found
Chemical equilibria studies using multivariate analysis methods
Chemical multiequilibria systems can be monitored
efficiently with the aid of spectroscopic techniques.
Both hard- and soft-modeling are effective and powerful
tools to extract chemical information from spectroscopic
data. Recently, hybrid approaches that combine the flexibility
of soft-modeling with the precise solutions provided
by hard-modeling have been proposed. Here, we tested the
performance of these three chemometric approaches for the
analysis of several simulated data sets. In addition,
experimental data recorded during the study of the acid–
base equilibria of two DNA structures (G-quadruplex and imotif)
corresponding to two short sequences of the k-ras
oncogene were studied. Finally, we also analyzed the
interaction of the two DNA sequences with the model
ligand TMPyP4. The results obtained from the analysis of
these data sets may be useful to determine the most
appropriate use of each approach.Whenever the presence
of optically active interferences or unknown drifts can be
neglected and a chemical model can easily be proposed and
fitted, the hard-modeling method shows the best performance.
If any of these conditions is not fulfilled, a hybridmodeling
approach may be a better option because all the
contributions (chemical and unknown) can be modeled and
the ambiguities inherent to soft-modeling methods show
minor effects.This research was supported by the Spanish
Ministerio de Ciencia e Innovación (grant number CTQ2009-11572)
and the Generalitat de Catalunya (grant number 2009-SGR-45).Peer reviewe