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Open AccessArticle

Classical QSAR and Docking Simulation of 4-Pyridone Derivatives for Their Antimalarial Activity

1
Laboratorio de Fisicoquímica Orgánica y Química Computacional, Escuela de Ciencias, Departamento de Química, Universidad de Oriente, Cumaná 6001, Venezuela
2
Departamento de Química, Pontificia Universidad Católica de Chile, Casilla 306, Santiago 6094411, Chile
3
Grupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, vía Puerto Colombia, Barranquilla 081007, Colombia
4
Grupo de Química computacional y teórica (QCT-USFQ) & instituto de Simulación Computacional (ISC-USF) Colegio Politécnico de Ciencias e Ingeniería Diego de Robles, y Vía Interoceánica, Universidad San Francisco de Quito, Quito 170901, Ecuador
5
Grupo de Investigación en Oxi/Hidrotratamiento Catalítico y Nuevos Materiales, Programa de Química-Ciencias Básicas, Universidad del Atlántico, Barranquilla 081001, Colombia
*
Author to whom correspondence should be addressed.
Academic Editor: Simone Brogi
Molecules 2018, 23(12), 3166; https://doi.org/10.3390/molecules23123166
Received: 13 October 2018 / Revised: 21 November 2018 / Accepted: 22 November 2018 / Published: 1 December 2018
(This article belongs to the Special Issue Computational Approaches for Drug Discovery)
In this work, the minimum energy structures of 22 4-pyridone derivatives have been optimized at Density Functional Theory level, and several quantum molecular, including electronic and thermodynamic descriptors, were computed for these substrates in order to obtain a statistical and meaningful QSAR equation. In this sense, by using multiple linear regressions, five mathematical models have been obtained. The best model with only four descriptors (r2 = 0.86, Q2 = 0.92, S.E.P = 0.38) was validated by the leave-one-out cross-validation method. The antimalarial activity can be explained by the combination of the four mentioned descriptors e.g., electronic potential, dipolar momentum, partition coefficient and molar refractivity. The statistical parameters of this model suggest that it is robust enough to predict the antimalarial activity of new possible compounds; consequently, three small chemical modifications into the structural core of these compounds were performed specifically on the most active compound of the series (compound 13). These three new suggested compounds were leveled as 13A, 13B and 13C, and the predicted biological antimalarial activity is 0.02 µM, 0.03 µM, and 0.07 µM, respectively. In order to complement these results focused on the possible action mechanism of the substrates, a docking simulation was included for these new structures as well as for the compound 13 and the docking scores (binding affinity) obtained for the interaction of these substrates with the cytochrome bc1, were −7.5, −7.2, −6.9 and −7.5 kcal/mol for 13A, 13B, 13C and compound 13, respectively, which suggests that these compounds are good candidates for its biological application in this illness. View Full-Text
Keywords: computational study; DFT; nitrogen compounds; molecular descriptors computational study; DFT; nitrogen compounds; molecular descriptors
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MDPI and ACS Style

Flores-Sumoza, M.; Alcázar, J.J.; Márquez, E.; Mora, J.R.; Lezama, J.; Puello, E. Classical QSAR and Docking Simulation of 4-Pyridone Derivatives for Their Antimalarial Activity. Molecules 2018, 23, 3166.

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