Computational design, molecular properties, ADME, and toxicological analysis of substituted 2,6-diarylidene cyclohexanone analogs as potent pyridoxal kinase inhibitors

Abstract

Leishmaniasis is one of the tropical diseases which affects over 12 million people mainly in the tropical regions of the world and is caused by the leishmanial parasites transmitted by the female sand fly. The lack of vaccines to prevent leishmaniasis, as well as limitations of existing therapies necessitated this study which was focused on a combined virtual docking screening and 3-D QSAR modeling approach to design some diarylidene cyclohexanone analogs, while also performing pharmacokinetic analysis and Molecular Dynamic (MD) simulation to ascertain their drug-ability. As a result, the built 3-D QSAR model was found to satisfy the requirement of a good model with R² = 0.9777, SDEC = 0.0593, F-test = 105.028, and Q² _LOO = 0.6592. The template (compound 9, MolDock score = - 161.064) and all seven newly designed analogs were found to possess higher docking scores than the reference drug (Pentamidine, Moldock score = - 137.827). The results of the pharmacokinetic analysis suggest 9 and the new molecules (9a, b, c, e, and f) as orally bioavailable with good ADME and safe toxicological profiles. These molecules also showed good binding interactions with the receptor (pyridoxal kinase). Additionally, the MD simulation result confirmed the stability of the tested protein-ligand complexes, with an estimated ∆G binding (MM/GBSA) of - 65.2177 kcal/mol and - 58.433 kcal/mol for 9_6K91 and 9a_6K91 respectively. Hence, the new compounds, especially 9a could be considered potential anti-leishmanial inhibitors.

Keywords: 3-D QSAR; ADMET; Diarylidene cyclohexanone; Leishmaniasis; Molecular docking; Molecular dynamics.

Fig. 1

3D representation of PdxK showing the binding site

Fig. 2

3D representation of compound 9 in the active site of PdxK

Fig. 3

Molecular alignment of structures for the QSAR modeling A Alignment template (compound 9 with the highest O3A_Score of 4002.51). B All structures aligned

Fig. 4

Correlation between predicted and observed pIC₅₀ for training and test sets

Fig. 5

Steric field contour maps of compound 9 A Red contours showing regions of unfavorable steric bulk. B Blue contours represent regions of favorable steric bulk

Fig. 6

Electrostatic field contour maps of compound 9 A Yellow contours represent regions favored by high electron density or unfavorable to electron-withdrawing substituents. B Green contours showing regions of unfavorable high electron density or favorable to electron-withdrawing groups

Fig. 7

Binding interactions of PdxK with A Compound 9. B Pentamidine

Fig. 8

Binding interactions of PdxK with A 9a, B 9c C, 9e, and D 9f

Fig. 9

RMSD plot for MD simulation of Compound 9 and 9a with PdxK

Fig. 10

RMSF plot for MD simulation of Compound 9 and 9a with PdxK

Fig. 11

Plot of Radius of gyration (Rg) versus time for MD simulation of Compound 9 and 9a with PdxK

Fig. 12

3D structural orientation of the ligand–protein complexes. A Non-simulated 9_6K91, B Simulated 9_6K91, C Non-simulated 9a_6K91, D Simulated 9a_6K91

Fig. 13

2D representation of binding interactions of the simulated complexes A 9_6K91, B 9a_6K91