Quantitative Structure Activity Relationship (QSAR) and Molecular Docking Study of Some Pyrrolones Antimalarial Agents against Plasmodium Falciparum

Year 2018, Volume: 5 Issue: 2, 569 - 584, 01.01.2018

Zaharaddeen Shehu , Adamu Uzairu Balarabe Sagagi

https://doi.org/10.18596/jotcsa.346661

Cited By: 5

Abstract

The increase in multidrug resistance
malaria cases necessitates the need to search for new cost effective drugs.
QSAR and molecular docking studies were performed on a data set of forty nine Pyrrolones antimalarial agents
against Plasmodium falciparum. Forty two molecules were used as training set
and seven as test set. The molecular descriptors were obtained by Density
Functional Theory (DFT) (B3LYP/6-31G**) level of calculation. The QSAR model
was built using Genetic Function Algorithm (GFA) method. The model with the
best statistical significance (N = 42, R²_ext = 0.700,
R² = 0.933,
R²a = 0.916,
Q²cv = 0.894,
LOF = 0.417, Min expt. error for non-significant LOF (95%) = 0.250 was selected. The docking experiment
was carried out using AutoDock Vina of PyRx and Discovery Studio Visualizer. Docking
analysis revealed that three of the
studied compounds with binding affinity values of -10.7 kcal/mol, -10.9
kcal/mol and -11.1 kcal/mol possess higher potency than standard antimalarial
drugs with binding affinity of values of -8.8 kcal/mol, -9.5 kcal/mol and -9.0
kcal/mol. It is envisioned that the
wealth of information provided by the QSAR and molecular docking results
in this study will offer important structural insights for further laboratory
experiments in the future design of novel and highly potent antimalarial from Pyrrolones.

Keywords

: Antimalarial agents, Density Functional Theory, Genetic Function Algorithm, Discovery Studio Visualizer

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