Abstract
The gene expression programming, a novel machine
learning algorithm, is used to develop quantitative
model as a potential screening mechanism for a series
of 1,4-dihydropyridine calcium channel antagonists for
the first time. The heuristic method was used to search
the descriptor space and select the descriptors
responsible for activity. A nonlinear, six-descriptor
model based on gene expression programming with
mean-square errors 0.19 was set up with a predicted
correlation coefficient (R2) 0.92. This paper provides
a new and effective method for drug design and
screening.
Graphical abstract
The log (1/IC50) for 45 1,4-dihydropyridines was
modelled using the descriptors calculated from the
molecular structure along with a quantitative
structure\u2013activity relationship (QSAR) technique.
The heuristic method (HM) and gene expression
programming (GEP) were used to construct the linear and
nonlinear prediction models, leading to a good
prediction.
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