EventsMOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Published
This submission belongs to the session 03. NICEXSM-05: North-Ibero-American Congress on Exp. and Simul. Methods, Valencia, Bilbao, Spain-Miami, USA, 2019 of the event MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Published date
20 Sep, 2019
Citation
Ramón García-Domenech, Ines Baptista Peraza, Camila Otero-Pérez, Stephanie González-Apraez, Ana Pertegás-Sevilla, Jorge Galvez, Application of Molecular Topology to the Analysis of Antimalarial Activity of 4-Aminobicyclo[2.2.2]Octan-2-yl 4-Aminobutanoate and their Equivalents Ethanoates and Propanoates, in Proceedings of MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed., 20 March–20 December 2019, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-05-06255
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Application of Molecular Topology to the Analysis of Antimalarial Activity of 4-Aminobicyclo[2.2.2]Octan-2-yl 4-Aminobutanoate and their Equivalents Ethanoates and Propanoates

Ines Baptista Peraza 2
Camila Otero-Pérez 2
Stephanie González-Apraez 2
Ana Pertegás-Sevilla 2
1. Catedratico Quimica Fisica Universitat de Valencia, Spain, Spain
2. Post graduate student
3. Catedratico Quimica Fisica Universitat de Valencia, Spain
Abstract

Malaria causes one of the highest mortality rates worldwide. Malaria cases and malaria deaths are still increasing due to, among other factors, the resistance that the parasite has developed to treatments. New molecules have been studied to be used as treatment for this disease. The present study analyzed the antiplasmodial activity of the Aminobicyclo[2.2.2]octan-2-yl 4-aminobutanoates and their ethanoates and propanoates analogs using molecular topology to develop a quantitative structure-activity relation (QSAR) model. Linear discriminant analysis was used to find a mathematical statement able to classify 32 of 35 compounds accurately by their antiplasmodial activity. The model classified 82.35% of molecules considered active with experimental methods, and differentiated 100% of the inactive molecules as such. Multilinear regression analysis was applied to find an equation with the ability to predict the antiplasmodial activity of each compound in terms of pIC50. Crossvalidation technique and randomness test were used to validate this model. After the analysis, new potential antiplasmodial molecules were suggested.

Keywords
Molecular topology
QSAR
malaria
antimalarial drugs
Manuscript
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