Docking simulations and multi-parameter ADMET profiling to decode quinapyramine sulfate’s strength and weakness

Quinapyramine sulfate (QS), a frontline trypanocide for haemoprotozoan Trypanosoma evansi infections, faces challenges like poor bioavailability and toxicity. Despite the economic importance of the disease, only limited drugs are available to combat trypanosomiasis and no study has been reported yet for determining the functionality of QS like ADMET, interactions and other prospects on its structural basis. One of the reasons is non-availability of any crystal structure or PDB for T. evansi for computational studies. As T. evansi shares high sequence identity with T. brucei , we adopted its co-crystal structure (5FUW, 2.20 Å) for computational studies. To our knowledge, this is the first work integrating molecular docking targets, comprehensive ADMET analysis, drug-likeness properties, toxicity risk assessment and molecular dynamic (MD) simulations for Quinapyramine, providing a blueprint for rational optimization of trypanocidal agents. Quinapyramine demonstrated moderate binding affinity, engaging key residues (Met214, Tyr370) with validated precision. A full protocol for MD trajectory analysis, including RMSD, RMSF, Rg and binding free energies (MM-PBSA) was employed to evaluate the stability of the Q-protein complex in comparison to Hydroxychloroquine (HCQ; reference drug). It revealed favourable metabolic stability without any CYP450/P-gp interactions. However, its high molecular weight resulted in poor absorption and multiple drug-likeness violations e.g., Lipinski’s, Ghose’s. Toxicity risks and mutagenicity alerts further underscored its limitations. Our study reveals QS’s target specificity versus pharmacokinetic drawbacks, advocating for structural optimization to enhance its therapeutic profile.

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Journal
In Silico Research in Biomedicine
Published
2025-11-30
DOI
https://doi.org/10.1016/j.insi.2025.100145
Primary Topic
Trypanosoma species research and implications
Type
article
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article

Docking simulations and multi-parameter ADMET profiling to decode quinapyramine sulfate’s strength and weakness

Anju Manuja, Rahul Goyal, Shalki Choudhary, Balvinder Kumar et al.
In Silico Research in Biomedicine
Trypanosoma species research and implications
article

Docking simulations and multi-parameter ADMET profiling to decode quinapyramine sulfate’s strength and weakness

Anju Manuja, Rahul Goyal, Shalki Choudhary, Balvinder Kumar, Kanish Manuja, Shalini Batheja
article en

Abstract

Quinapyramine sulfate (QS), a frontline trypanocide for haemoprotozoan Trypanosoma evansi infections, faces challenges like poor bioavailability and toxicity. Despite the economic importance of the disease, only limited drugs are available to combat trypanosomiasis and no study has been reported yet for determining the functionality of QS like ADMET, interactions and other prospects on its structural basis. One of the reasons is non-availability of any crystal structure or PDB for T. evansi for computational studies. As T. evansi shares high sequence identity with T. brucei , we adopted its co-crystal structure (5FUW, 2.20 Å) for computational studies. To our knowledge, this is the first work integrating molecular docking targets, comprehensive ADMET analysis, drug-likeness properties, toxicity risk assessment and molecular dynamic (MD) simulations for Quinapyramine, providing a blueprint for rational optimization of trypanocidal agents. Quinapyramine demonstrated moderate binding affinity, engaging key residues (Met214, Tyr370) with validated precision. A full protocol for MD trajectory analysis, including RMSD, RMSF, Rg and binding free energies (MM-PBSA) was employed to evaluate the stability of the Q-protein complex in comparison to Hydroxychloroquine (HCQ; reference drug). It revealed favourable metabolic stability without any CYP450/P-gp interactions. However, its high molecular weight resulted in poor absorption and multiple drug-likeness violations e.g., Lipinski’s, Ghose’s. Toxicity risks and mutagenicity alerts further underscored its limitations. Our study reveals QS’s target specificity versus pharmacokinetic drawbacks, advocating for structural optimization to enhance its therapeutic profile.

In Silico Research in BiomedicineVol. 2
National Research Centre on Equines (IN)
Openalex Percentile: Top 51%
Trypanosoma species research and implications
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