Superpendentic index: a novel topological descriptor for predicting biological activity

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Gastric H+,K(+)-ATPase enzyme is a key target for antiulcer drug development.
• 4-substituted-2-guanidino thiazoles are known inhibitors of this enzyme.
• Predictive models are valuable for optimizing drug discovery efforts.

Purpose of the Study:

• To conceptualize a novel topological descriptor, the superpendentic index.
• To investigate the discriminating power of the superpendentic index for antiulcer activity.
• To evaluate the predictive accuracy of the superpendentic index against known biological data.

Main Methods:

• A dataset of 128 analogues of 4-substituted-2-guanidino thiazoles was compiled.
• The superpendentic index was computed for each analogue.
• The computed index values were used to identify an active range.
• Biological activity predictions were compared with reported in vitro and in vivo data.

Main Results:

• The superpendentic index was successfully computed for all 128 analogues.
• An active range for the superpendentic index was identified.
• Classification accuracy based on in vivo inhibitory activity reached 82% within the identified active range.
• The descriptor showed good correlation with reported antiulcer activities.

Conclusions:

• The superpendentic index is a simple, degenerating, pendenticity-based topological descriptor.
• This index demonstrates significant discriminating power for predicting antiulcer activity.
• The superpendentic index offers a valuable tool for the rational design of novel antiulcer agents.