Pharmacophore modeling, 2D-QSAR, drug likeness and toxicity prediction of 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives as multifunctional agents for the treatment of malaria parasite, Plasmodium falcipar

Pharmacophore modeling, QSAR, molecular docking, in silico ADME, and toxicity prediction have been conducted on 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate-based malaria parasite inhibitors. In this study, we aim to clarify the binding mode and drug-likeness of these derivatives. Ultimately, 63 compounds were utilized to develop a model. The model was statistically significant, exhibiting a high correlation coefficient (R² = 0.8066), a cross-validation coefficient (Q² loo = 0.7559), and an F value of 43.3149. The results from external validation also demonstrate strong predictive power (R² ext = 0.7325). In addition to passing Tropsha's test for predictive ability, the resulting model also successfully passed the Y-randomization test. The model’s applicability domain (AD) was clearly defined, indicating that in the case of a new prediction, it is evident whether that prediction can be safely made. To assess the impact of the docking protocol, a co-crystallized ligand from the protein's ligand-binding domain was selected and re-docked. The results after redocking and the co-crystallized ligand were aligned, with a mean root-mean-square deviation along their lines of 1.703 Å. Using the DTM protein co-crystal ligand (PDB ID: 1MVT ) as a template, the pharmacophore hypotheses were produced. A screening of PubChem databases resulted in 40 hits that passed the screening requirements for docking against the DTM receptor through the Pharmit server. The top two docked compounds having the highest binding affinities from -11.5 to -11.1 kcal/mol were selected. A further ADMET analysis showed that the selected compounds have values within the acceptable range. Molecular dynamics simulation analysis of inhibitor potentials against the malaria enzyme, compound 18 has strong inhibitory potential in treating malaria diseases. Findings from this study inform on possible ways of designing new inhibitors for malaria parasites.

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Journal
NAM journal.
Published
2025-01-01
DOI
https://doi.org/10.1016/j.namjnl.2025.100019
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

Pharmacophore modeling, 2D-QSAR, drug likeness and toxicity prediction of 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives as multifunctional agents for the treatment of malaria parasite, Plasmodium falcipar

Emmanuel Israel Edache, Aqel Albutti, Fabian Audu Ugbe, Adebiyi Adedayo et al.
1 citations
NAM journal.
Computational Drug Discovery Methods
1.50
article

Pharmacophore modeling, 2D-QSAR, drug likeness and toxicity prediction of 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives as multifunctional agents for the treatment of malaria parasite, Plasmodium falcipar

Emmanuel Israel Edache, Aqel Albutti, Fabian Audu Ugbe, Adebiyi Adedayo, Hadiza Adamu Dawi, Ahmed Umar
article en
1 citations

Abstract

Pharmacophore modeling, QSAR, molecular docking, in silico ADME, and toxicity prediction have been conducted on 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate-based malaria parasite inhibitors. In this study, we aim to clarify the binding mode and drug-likeness of these derivatives. Ultimately, 63 compounds were utilized to develop a model. The model was statistically significant, exhibiting a high correlation coefficient (R² = 0.8066), a cross-validation coefficient (Q² loo = 0.7559), and an F value of 43.3149. The results from external validation also demonstrate strong predictive power (R² ext = 0.7325). In addition to passing Tropsha's test for predictive ability, the resulting model also successfully passed the Y-randomization test. The model’s applicability domain (AD) was clearly defined, indicating that in the case of a new prediction, it is evident whether that prediction can be safely made. To assess the impact of the docking protocol, a co-crystallized ligand from the protein's ligand-binding domain was selected and re-docked. The results after redocking and the co-crystallized ligand were aligned, with a mean root-mean-square deviation along their lines of 1.703 Å. Using the DTM protein co-crystal ligand (PDB ID: 1MVT ) as a template, the pharmacophore hypotheses were produced. A screening of PubChem databases resulted in 40 hits that passed the screening requirements for docking against the DTM receptor through the Pharmit server. The top two docked compounds having the highest binding affinities from -11.5 to -11.1 kcal/mol were selected. A further ADMET analysis showed that the selected compounds have values within the acceptable range. Molecular dynamics simulation analysis of inhibitor potentials against the malaria enzyme, compound 18 has strong inhibitory potential in treating malaria diseases. Findings from this study inform on possible ways of designing new inhibitors for malaria parasites.

NAM journal.Vol. 1
Qassim University (SA), National Institute for Pharmaceutical Research and Development (NG), University of Maiduguri (NG), University of Abuja (NG)
Good health and well-being
Openalex Percentile: Top 18%
Computational Drug Discovery Methods
1.50
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