ABSTRACT
Leishmaniasis affects mainly rural areas and the poorest people in the world. A computational study of the antileishmanial activity of organic selenium and tellurium compounds was performed. The 3D structures of the compounds were optimized at the wb97xd/lanl2dz level and used in the quantitative structure-activity relationship (QSAR) analysis. The antileishmanial activity was measured by L. donovani β carbonic anhydrase inhibition (Ki) and the half-maximal inhibitory concentration (IC50) against L. infantum amastigotes. The dataset was divided into training (75%) and test sets (25%) by using a k-means clustering algorithm. For pKi prediction, model M3 with seven 3D topographic descriptors was characterized by the following statistical parameters: r2 = 0.879, Q2LOO = 0.822, and Q2ext = 0.840. For pIC50 prediction, model M12 with six attributes was characterized by the following statistical parameters: r2 = 0.907, Q2LOO = 0.824, and Q2ext = 0.795. Both models met all the requirements of Tropsha´s test, which implies predictions of pIC50 and pKi activities with high accuracy. Concomitantly, favourable interactions of the sulphonamide group with the Zn atom in the protein were revealed by the docking analysis.
Acknowledgements
The authors are grateful to the Instituto of Biomedicina and SINDE-1831-2019 of Universidad Católica Santiago de Guayaquil (UCSG), USFQ-Collaboration grants 2019-2020 for the financial support and Universidad del Norte, Colombia. The LSAyB of the UAZ thanks the self-financing, as well as the support granted by the Coordination of the Engineering and Technology area and the COZCyT. The authors have used the high-performance computing (HPC) system available in both, USFQ and Uninorte, for the development of this project.
Disclosure statement
No potential conflict of interest was reported by the authors.