Pharmacophore Modeling and Database Mining to Identify Novel Lead Compounds Active Against the Disease Stage of Trypanosomiasis in the Central Nervous System

Abstract

Introduction: Sleeping sickness has long been considered as a neglected disease, and very few pharmaceutical companies and research organizations are involved in the design and development of anti-trypanosomal drugs. This may be especially due to poor financial returns. Materials and Methods: In view of the dire need for new drugs for sleeping sickness, we have implemented in-silico ligand- and structure-based methods for the development of a universal pharmacophore model. The ligand-based pharmacophore models for 1,2-dihydroquinolin-6-ols and their ester derivatives were developed using Catalyst HypoGen refine algorithm. The best quantitative pharmacophore hypothesis was selected on the basis of correlation coefficient (0.92), root mean square deviation (0.97), and cost difference (76) values. The best pharmacophore model was compared with a structure-based model developed using the Protein Data Bank structure of trypanothione reductase (TR) bound to WPC inhibitor. Results and Discussion: High consistency between ligand- and structure-based models was observed, and both the approaches indicate that four-point interactions [three hydrophobic and one hydrogen bond acceptor (HBA)] are necessary for the anti-trypanosomal activity of 1,2-dihydroquinolin-6-ols. The pharmacophoric features obtained were in accordance with the binding requirement of TR binding site, indicating that these compounds can act as TR inhibitors. To further evaluate the model, an external test set comprising known trypanocidal agents were mapped on to a developed pharmacophoric model, which also showed four-point mapping and estimated values in close range to actual values. The screening of chemical database resulted in the identification of three druggable structurally diverse potent lead compounds. Conclusion: Since no pharmacophore model has been developed for this new series of compounds till date, the achieved results will allow researchers to further use this 3D pharmacophore model and hits for the design and synthesis of newer anti-trypanosomal compounds.