Abstract (EN):
Desirability theory (DT) is a well-known multi-criteria
decision-making approach. In this work, DT
is employed as a prediction model (PM) interpretation
tool to extract useful information on the
desired trade-offs between binding and relative
efficacy of N6-substituted-4¢-thioadenosines A3
adenosine receptor (A3AR) agonists. At the same
time, it was shown the usefulness of a parallel but
independent approach providing a feedback on
the reliability of the combination of properties
predicted as a unique desirability value. The appliance
of belief theory allowed the quantification of
the reliability of the predicted desirability of a
compound according to two inverse and independent
but complementary prediction approaches.
This information is proven to be useful as a ranking
criterion in a ligand-based virtual screening
study. The development of a linear PM of the
A3AR agonists overall desirability allows finding
significant clues based on simple molecular
descriptors. The model suggests a relevant role of
the type of substituent on the N6 position of the
adenine ring that in general contribute to reduce
the flexibility and hydrophobicity of the lead compound. The mapping of the desirability function
derived of the PM offers specific information
such as the shape and optimal size of the N6 substituent.
The model herein developed allows a
simultaneous analysis of both binding and relative
efficacy profiles of A3AR agonists. The information
retrieved guides the theoretical design and
assembling of a combinatorial library suitable for
filtering new N6-substituted-4¢-thioadenosines
A3AR agonist candidates with simultaneously
improved binding and relative efficacy profiles.
The utility of the desirability ⁄ belief-based proposed
virtual screening strategy was deduced
from our training set. Based on the overall results,
it is possible to assert that the combined use of
desirability and belief theories in computational
medicinal chemistry research can aid the discovery
of A3AR agonist candidates with favorable balance
between binding and relative efficacy
profiles.
Language:
English
Type (Professor's evaluation):
Scientific
Contact:
mfernandamborges@gmail.com