Computational Design and Pharmacokinetic Profiling of Novel Fe(II)-Peptide Complex

Authors

  • Rizal Irfandi Universitas Negeri Makassar

DOI:

https://doi.org/10.51574/hayyan.v3i1.5302

Keywords:

Fe(II)-peptide, proline-arginine, metal coordination, pharmacokinetics, drug-like properties

Abstract

Metal-peptide complexes represent a promising avenue in medicinal chemistry due to their unique coordination and biological properties. This study aimed to design and evaluate a Fe(II)-proline-arginine-dipeptide complex as a potential therapeutic agent. Computational modeling constructed the ligand and optimized the coordination geometry with Fe(II) and two chloride ligands, forming a stable distorted tetrahedral structure. 1H- and 13C-NMR spectra confirmed preservation of the dipeptide framework. Physicochemical assessment revealed a molecular weight of 396.056 g/mol, low LogP of 0.21947, balanced hydrogen-bond donors and acceptors, and a polar surface area of 139.047 Ų, supporting oral drug-likeness. ADMET analysis predicted moderate intestinal absorption (38.444%), low CNS penetration, minimal CYP enzyme interaction, and moderate clearance (1.11 log mL/min/kg). Toxicity prediction indicated no AMES mutagenicity, hepatotoxicity, or hERG inhibition, with an oral rat LD50 of 2.174 mol/kg. These results demonstrate that the Fe(II)-proline-arginine-dipeptide complex possesses structural stability, favorable pharmacokinetic behavior, and a broad safety profile, highlighting its potential as a therapeutic candidate. The study provides a framework for integrating peptide ligand design with metal coordination and in silico pharmacokinetic evaluation, suggesting avenues for experimental validation and future drug development.

References

Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7, 42717. https://doi.org/10.1038/srep42717

Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1–3), 3–25. https://doi.org/10.1016/S0169-409X(96)00423-1

Marinova, M., Ivanov, S., & Petrov, P. (2024). Metal-peptide complexes as emerging therapeutic agents: Design principles and biological implications. Journal of Medicinal Chemistry, 67(5), 2456–2475. https://doi.org/10.1021/acs.jmedchem.3c01712

Pires, D. E. V., Blundell, T. L., & Ascher, D. B. (2015). pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of Medicinal Chemistry, 58(9), 4066–4072. https://doi.org/10.1021/acs.jmedchem.5b00104

Veber, D. F., Johnson, S. R., Cheng, H. Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n

Wu, C., Liu, Z., & Yang, X. (2020). Computational approaches in metal-based drug design: Integration of structure, stability, and ADMET prediction. Frontiers in Chemistry, 8, 593. https://doi.org/10.3389/fchem.2020.00593

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Published

2026-02-28

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