Discovery of Natural Products Targeting NQO1 via an Approach Combining Network-Based Inference and Identification of Privileged Substructures

NAD­(P)­H:quinone
oxidoreductase 1 (NQO1) has been shown to be a
potential therapeutic target for various human diseases, such as cancer
and neurodegenerative disorders. Recent advances in computational
methods, especially network-based methods, have made it possible to
identify novel compounds for a target with high efficiency and low
cost. In this study, we designed a workflow combining network-based
methods and identification of privileged substructures to discover
new compounds targeting NQO1 from a natural product library. According
to the prediction results, we purchased 56 compounds for experimental
validation. Without the assistance of privileged substructures, 31
compounds (31/56 = 55.4%) showed IC50 < 100 μM,
and 11 compounds (11/56 = 19.6%) showed IC50 < 10 μM.
With the assistance of privileged substructures, the two success rates
were increased to 61.8 and 26.5%, respectively. Seven natural products
further showed inhibitory activity on NQO1 at the cellular level,
which may serve as lead compounds for further development. Moreover,
network analysis revealed that osthole may exert anticancer effects
against multiple cancer types by inhibiting not only carbonic anhydrases
IX and XII but also NQO1. Our workflow and computational methods can
be easily applied in other targets and become useful tools in drug
discovery and development.