Modeling natural anti-inflammatory compounds by molecular topology

Abstract

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with the remaining compounds (those not used in building up the model), has been carried out. Finally, a virtual screening on natural products was performed and 74 compounds showed actual anti-inflammatory activity. From them, 54 had been previously described as anti-inflammatory in the literature. This can be seen as a plus in the model validation and as a reinforcement of the role of Molecular Topology as an efficient tool for the discovery of new anti-inflammatory natural compounds.

Keywords: Molecular Topology; anti-inflammatory; linear discriminant analysis; natural; virtual screening.

Figure 1

Average, maximum and minimum values (gray, white and black bars, respectively) obtained with molecular weight, MW, partition coefficient, logP, and Randic index, ¹χ for the training and test sets of compounds.

Figure 2

Pharmacological distribution diagram for natural anti-inflammatory compounds obtained using the discriminant function DF. (The black color represents the compounds with anti-inflammatory activity and the white color, the compounds without it).

Figure 3

General overview of the active and inactive compounds by their structural and chemical properties.