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

Flores-Sumoza, Máryury; Alcázar, Jackson J.; Márquez, Edgar; Mora, José R.; Lezama, Jesús; Puello-Polo, Esneyder

doi:10.3390/molecules23123166

Cited by 12 publications

(12 citation statements)

References 37 publications

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“…e molecules were characterized as minimum stationary points, which were obtained by a frequency calculation on the optimized structures at 298.15 K [30]. 892 topological descriptors were calculated by using the free software QuBiLs-MIDAS and MAS, available on http://tomocomd.com/ [31], and that pool wad enlarged by the addition of 5 descriptors: cLogP, cLogS, druglikeness, total surface area, and polar surface area were calculated using the software OSIRIS DataWarrior [32]. e hydrophilicity of a drug is measured by the logarithm of the concentration of a drug in n-octanol over water (equation 2); values of marked drugs are between −10 and 8.…”

Section: Datasetmentioning

confidence: 99%

Computational Molecular Modeling of Pin1 Inhibition Activity of Quinazoline, Benzophenone, and Pyrimidine Derivatives

Cabrera

Mora

Márquez

2019

Journal of Chemistry

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Pin1 (peptidyl-prolyl cis-trans isomerase NIMA-interacting 1) is directly involved in cancer cell-cycle regulation because it catalyses the cis-trans isomerization of prolyl amide bonds in proteins. In this sense, a modeling evaluation of the inhibition of Pin1 using quinazoline, benzophenone, and pyrimidine derivatives was performed by using multilinear, random forest, SMOreg, and IBK regression algorithms on a dataset of 51 molecules, which was divided randomly in 78% for the training and 22% for the test set. Topological descriptors were used as independent variables and the biological activity (pIC50) as a dependent variable. The most robust individual model contained 9 features, and its predictive capability was statistically validated by the correlation coefficient for adjusting, 10-fold cross validation, test set, and bootstrapping with values of 0.910, 0.819, 0.841, and 0.803, respectively. In order to improve the prediction of the pIC50 values, the aggregation of the individual models was performed through the construction of an ensemble, and the most robust one was constructed by two individual models (LR3 and RF1) by applying the IBK algorithm, and a substantial improvement in predictive performance is reflected in the values of R2ADJ = 0.982, Q2CV = 0.962, and Q2EXT = 0.918. Mean square errors <0.165 and good fitting between calculated and experimental pIC50 values suggest a robustness on the prediction of pIC50. Regarding the docking simulation, a binding affinity between the molecules and the active site for the Pin1 inhibition into the protein (3jyj) was estimated through the calculation of the binding free energy (BE), with values in the range of −5.55 to −8.00 kcal/mol, implying a stabilizing interaction molecule receptor. The ligand interaction diagrams between the drugs and amino acid in the binding site for the three most active compounds denoted a good wrapper of these organic compounds into the protein mainly by polar amino acids.

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Section: Datasetmentioning

confidence: 99%

Computational Molecular Modeling of Pin1 Inhibition Activity of Quinazoline, Benzophenone, and Pyrimidine Derivatives

Cabrera

Mora

Márquez

2019

Journal of Chemistry

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“…The relationships of antileukemia activity and the most relevant molecular descriptors were studied using multiple linear regressions. The method used has been described [13,70] before. Briefly, attempts were made to map the relationship between two or more independent variables with a dependent variable by fitting a linear equation involving the observed data.…”

Section: Quantitative Structure-activity Relationship (Qsar) and Statmentioning

confidence: 99%

“…The protocol used herein to perform the molecular docking has been reported previously [68,72], and has been used to model the interactions of drugs with the active sites in different diseases, such as Pin1 (peptidyl-prolyl cis-trans isomerase NIMA-interacting 1) [15] inhibition and antimalarial activity [13]. Autodock4 software was used to this end [79].…”

Section: Molecular Dockingmentioning

confidence: 99%

Modeling the Antileukemia Activity of Ellipticine-Related Compounds: QSAR and Molecular Docking Study

et al. 2019

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The antileukemia cancer activity of organic compounds analogous to ellipticine representes a critical endpoint in the understanding of this dramatic disease. A molecular modeling simulation on a dataset of 23 compounds, all of which comply with Lipinski’s rules and have a structure analogous to ellipticine, was performed using the quantitative structure activity relationship (QSAR) technique, followed by a detailed docking study on three different proteins significantly involved in this disease (PDB IDs: SYK, PI3K and BTK). As a result, a model with only four descriptors (HOMO, softness, AC1RABAMBID, and TS1KFABMID) was found to be robust enough for prediction of the antileukemia activity of the compounds studied in this work, with an R2 of 0.899 and Q2 of 0.730. A favorable interaction between the compounds and their target proteins was found in all cases; in particular, compounds 9 and 22 showed high activity and binding free energy values of around −10 kcal/mol. Theses compounds were evaluated in detail based on their molecular structure, and some modifications are suggested herein to enhance their biological activity. In particular, compounds 22_1, 22_2, 9_1, and 9_2 are indicated as possible new, potent ellipticine derivatives to be synthesized and biologically tested.

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“…Quantitative structure activity relationship (QSAR) analysis is an important computer simulation method (Neves et al, 2018;Potemkin et al, 2018) and is mainly used to study the relationship between compound structure and physicochemical properties or biological activity (Brahmbhatt et al, 2018;Flores-Sumoza et al, 2018;Marquina et al, 2019;Toropov & Toropova, 2018). It was reported that QSAR was used to furnish relationship between molecular descriptors and the nitric oxide synthase inhibition activity, antiproliferative activity, or alpha-glucosidase inhibiting activity in order to the search of more potent drugs in the andrographolide derivative family of compounds (Prasana et al, 2019;Hazra et al, 2015;Moorthy et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Synthesis, extracorporeal nephrotoxicity, and 3D‐QSAR of andrographolide derivatives

Lü

et al. 2020

Chem Biol Drug Des

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Andrographolide is a traditional Chinese medicine monomer with many pharmacological activities, but has potential nephrotoxicity. Here, we aim to investigate the relationship between modification of andrographolide structure and its nephrotoxicity. Twenty-three andrographolide derivatives were synthesized, and their structures were confirmed by 1 H-NMR and HRMS. Nephrotoxicity of these compounds against human renal tubular epithelial (HK-2) cells was evaluated using the MTT assay. The results indicated that most of them had significantly reduced nephrotoxicity, especially compounds III, V, and IX c , with IC 50 values of 1,985, 1,300, and 806.9 μmol/L, respectively, which were obviously superior to andrographolide (IC 50 30.60 μmol/L). However, compounds I a-I f (IC 50 values < 30 μmol/L), the 14-OH derivatives of andrographolide, showed higher nephrotoxicity than that of andrographolide. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models of COMFA and COMSIA were established (COMFA: q 2 = 0.639, r 2 = 0.951; COMSIA: q 2 = 0.569, r 2 = 0.857). This model allowed proposing five new compounds with lower theoretical nephrotoxicity, which would be worthwhile to synthesize and evaluate. We believe that predicted models will help us to understand the structural modification requirements of andrographolide to reduce the nephrotoxicity, and further investigations will be needed to determine the mechanism involved in the effect of less nephrotoxic compounds.

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

Cited by 12 publications

References 37 publications

Computational Molecular Modeling of Pin1 Inhibition Activity of Quinazoline, Benzophenone, and Pyrimidine Derivatives

Computational Molecular Modeling of Pin1 Inhibition Activity of Quinazoline, Benzophenone, and Pyrimidine Derivatives

Modeling the Antileukemia Activity of Ellipticine-Related Compounds: QSAR and Molecular Docking Study

Synthesis, extracorporeal nephrotoxicity, and 3D‐QSAR of andrographolide derivatives

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