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Updated: Jun 9, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
In silico molecular targets, docking, dynamics simulation and physiologically based pharmacokinetics modeling of
Toluwase Hezekiah Fatoki1,2, Tosin Christianah Balogun3, Adebayo Emmanuel Ojewuyi3
1Applied Bioinformatics Laboratory, Department of Biochemistry, Federal University Oye-Ekiti, Oye-Ekiti, Ekiti State, Nigeria. toluwase.fatoki@fuoye.edu.ng.
Introduction:
Oritavancin is a semi-synthetic lipoglycopeptide antibiotic primarily used to treat serious infections caused by Gram-positive bacteria. The aim of this study was to elucidate possible molecular targets of oritavancin in human and microbes in relevance to its mechanism of action and model its pharmacokinetics for optimal dose selection in clinical practice.
Methods:
Computational methods were used in this study which include target prediction, molecular docking, molecular dynamics simulation, pharmacokinetics prediction, and physiological-based pharmacokinetics (PBPK) modeling.
Results:
Oritavancin was moderately soluble in water and did not permeate the blood-brain barrier. Seven molecular targets were identified in humans. Molecular docking results showed highest binding affinity of oritavancin with PI3-kinase p110-gamma subunit (-10.34 kcal/mol), followed by Acyl-CoA desaturase (-10.07 kcal/mol) and Cytochrome P450 2C19 (-8.384 kcal/mol). Oritavancin PBPK modelling in adult human showed that infusion has lower peak concentrations (Cmax) compared to bolus administration, with 1200 mg dose yielded Cmax of 16.559 mg/L, 800 mg dose yielded Cmax of 11.258 mg/L, and 200 mg over 3 days dose yielded Cmax of 7.526 mg/L. Notably, infusion gave extended half-life (t1/2) for all doses and slightly higher clearance rates compared to bolus, particularly for the 1200 mg and 800 mg doses. The results corroborated existing clinical pharmacokinetic data, and confirmed the model's accuracy and predictive capability.
Conclusion:
This comprehensive computational study has provided invaluable insights into the pharmacological profile of Oritavancin, aiding its further development and optimization for clinical use.
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