Metronidazol Aldehit Türevinin ADMET Değerlendirilmesi

Öz

Metronidazol, yaygın olarak kullanılan nitroimidazol türevi bir antimikrobiyal ajandır ve bu yapı iskeletinin kimyasal olarak modifiye edilmesi ilaç geliştirme çalışmalarında önemli bir stratejidir. Bu çalışmada, oksidasyon yoluyla daha önce sentezlenmiş metronidazol aldehit türevi ile metronidazolün absorpsiyon, dağılım, metabolizma, atılım ve toksisite (ADMET) özellikleri in silico yöntemlerle karşılaştırmalı olarak değerlendirilmiştir. ADMET tahminleri, ADMETlab 3.0 platformu kullanılarak gerçekleştirilmiştir. Elde edilen sonuçlar, aldehit türevinin lipofilisitesinde hafif bir artış ve buna bağlı olarak tahmin edilen membran geçirgenliğinde sınırlı bir değişim olabileceğini göstermektedir. Bununla birlikte, her iki bileşik benzer sınıflandırma aralıklarında yer almaktadır. Buna karşılık, aldehit türevinin daha düşük metabolik stabilite, daha kısa tahmini yarı ömür ve özellikle deri duyarlılığı ile ilişkili daha fazla toksisite uyarısı ile ilişkili olabileceği öngörülmüştür. Her iki bileşik de temel ilaç benzerliği kurallarını sağlamış ve başlıca sitokrom P450 enzimleri için substrat olarak tahmin edilmiş olup belirgin inhibitör etkiler göstermemiştir. Sonuçlar, aldehit modifikasyonunun ADMET profili üzerinde etkili olabileceğini ve geçirgenlik ile ilişkili sınırlı değişimlere karşılık metabolik ve güvenlik açısından bazı olumsuzluklar ile ilişkili olabileceğini düşündürmektedir. Bununla birlikte, bu bulgular yalnızca in silico tahminlere dayanmaktadır ve dikkatle yorumlanmalıdır. Bu çalışma, aldehit modifikasyonunun etkilerine ilişkin ön değerlendirme niteliğinde olup, ileri çalışmalar için temel oluşturabilir.

Anahtar Kelimeler

• Metronidazol
• in silico ADMET analizi
• ilaç benzerliği
• farmakokinetik özellikler

ADMET Evaluation of a Metronidazole Aldehyde Derivative

Öz

Metronidazole is a widely used nitroimidazole-based antimicrobial agent, and structural modification of this scaffold remains an important strategy in drug development. In this study, an in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation of metronidazole and its aldehyde derivative, previously synthesized via oxidation, was performed. ADMET predictions were carried out using the ADMETlab 3.0 platform to assess physicochemical properties, drug-likeness, pharmacokinetic behaviour, metabolic stability, and toxicity profiles. The aldehyde derivative exhibited a slight increase in lipophilicity and a corresponding change in predicted membrane permeability compared to metronidazole, although both compounds remained within similar classification ranges. However, the derivative showed reduced metabolic stability, a shorter predicted half-life, and an increased number of toxicity-related alerts, particularly in terms of skin sensitization and medicinal chemistry warnings. Both compounds satisfied major drug-likeness rules and were predicted to be substrates of key cytochrome P450 enzymes, without significant inhibitory effects. The results suggest that aldehyde functionalization may influence the ADMET profile of metronidazole, introducing a balance between minor changes in permeability-related parameters and increased metabolic and safety-related concerns. However, these findings are based solely on in silico predictions and should be interpreted with caution. The present study offers a preliminary comparative assessment of aldehyde modification, which may serve as a basis for further experimental and computational investigations.

Anahtar Kelimeler

• Metronidazole
• in silico ADMET analysis
• drug-likeness
• pharmacokinetic properties.

Teşekkür

Thans you.

Kaynakça

1. 1. Kalinin S, Vedekhina T, Paramonova P, Krasavin M. Antimicrobial activity of 5-membered nitroheteroaromatic compounds beyond nitrofurans and nitroimidazoles: recent progress. Curr Med Chem. 2021;28(29):5926–5982.
2. 2. Chua KYL. Metronidazole. In: Kucers’ the use of antibiotics. Boca Raton: CRC Press; 2017. p. 1807–1849.
3. 3. Santos HLC, Rebello KM. An overview of mucosa-associated protozoa: challenges in chemotherapy and future perspectives. Front Cell Infect Microbiol. 2022;12:860442.
4. 4. Edwards DI. Mechanisms of selective toxicity of metronidazole and other nitroimidazole drugs. Sex Transm Infect. 1980;56(5):285–290.
5. 5. Ettadili FE, Azriouil M, Matrouf M, et al. Materials framework-based bio/sensors for the detection of ornidazole and metronidazole antibiotics in environment and foodstuffs. Inorg Chem Commun. 2022;140:109416.
6. 6. Ceban E, Earar K, Nechita LC, Oleg S, Zaharescu A, Jinga V. Impact of metronidazole on urine chromatics, mechanisms and medical relevance. Rom J Oral Rehabil. 2025;17(1).
7. 7. Wu Q, Wu F, Jiang H, et al. Safety evaluation of nitroimidazole antibiotics based on the FAERS database. Clin Exp Pharmacol Physiol. 2025;52(12):e70084.
8. 8. Kumar S, Thakur M, Kumari S, Sharma S, Kanwar SS, Devi S. Chromium-based itaconic acid-functionalized MOF: a microcarrier for sustained drug release, synergistic antibacterial effect with metronidazole, and enhanced infection control. J Sol-Gel Sci Technol. 2025;114(3):742–761.

9. 9. Lanez T, Lanez M, Lanez R, Laanez E, Talbi-Lanez B. Computational screening of novel nitroimidazole candidates: targeting key enzymes of oral anaerobes for anti-parasitic potential. Curr Drug Discov Technol. 2025;22(4):E15701638326365.
10. 10. Gupta R, Sharma S, Singh R, Vishwakarma RA, Mignani S, Singh PP. Functionalized nitroimidazole scaffold construction and their pharmaceutical applications: a 1950–2021 comprehensive overview. Pharmaceuticals. 2022;15(5):561.
11. 11. Vichi-Ramírez MM, López-López E, Soriano-Correa C, Barrientos-Salcedo C. Using 5-nitroimidazole derivatives against neglected tropical protozoan diseases: systematic review. Future Pharmacol. 2024;4(1):222–255.
12. 12. Fura A, Shu YZ, Zhu M, Hanson RL, Roongta V, Humphreys WG. Discovering drugs through biological transformation: role of pharmacologically active metabolites in drug discovery. J Med Chem. 2004;47(18):4339–4351.
13. 13. Gampe C, Verma VA. Curse or cure? A perspective on the developability of aldehydes as active pharmaceutical ingredients. J Med Chem. 2020;63(23):14357–14381.
14. 14. Grimsrud PA, Xie H, Griffin TJ, Bernlohr DA. Oxidative stress and covalent modification of proteins with bioactive aldehydes. J Biol Chem. 2008;283(32):21837–21841.
15. 15. Bandyopadhyay A, Gao J. Targeting biomolecules with reversible covalent chemistry. Curr Opin Chem Biol. 2016;34:110–116.
16. 16. Gampe C, Verma VA. Curse or cure? A perspective on the developability of aldehydes as active pharmaceutical ingredients. J Med Chem. 2020;63(23):14357–14381.
17. 17. Delmas C, Sager E, Henry C, Hassiepen U, Skaanderup PR, Kerschgens I. Reversible covalent reactions of aldehydes and salicylaldehydes using a lysine-model substrate. Chimia. 2025;79(3):152–157.
18. 18. Fritz KS, Petersen DR. An overview of the chemistry and biology of reactive aldehydes. Free Radic Biol Med. 2013;59:85–91.
19. 19. Manevski N, King L, Pitt WR, Lecomte F, Toselli F. Metabolism by aldehyde oxidase: drug design and complementary approaches to challenges in drug discovery. J Med Chem. 2019;62(24):10955–10994.
20. 20. Daoud NEH, Borah P, Deb PK, et al. ADMET profiling in drug discovery and development: perspectives of in silico, in vitro and integrated approaches. Curr Drug Metab. 2021;22(7):503–522.
21. 21. Fan N, Chen J, Wang J, Chen ZS, Yang Y. Bridging data and drug development: machine learning approaches for next-generation ADMET prediction. Drug Discov Today. 2025;104487.
22. 22. Bhatkhande K, Vysyaraju NN, Alavala RR, Gokhale KM. Recent advances in drug-likeness screening by using the software and online tools. In: Applications of computational tools in drug design and development. 2025. p. 683–717.
23. 23. Ghani S, Khan N, Sable H, Yao F, Shafiq M. Computational techniques for enhancing PK/PD modeling and simulation and ADMET prediction. In: Computational methods in medicinal chemistry, pharmacology, and toxicology. Academic Press; 2025. p. 153–174.
24. 24. Mahajan B, Gawarkar-Patil P, Adnaik P, et al. Applications of computational tools in the prediction of toxicity. In: Biosystems, biomedical & drug delivery systems: characterization, restoration and optimization. Singapore: Springer Nature Singapore; 2024. p. 311–326.
25. 25. Meanwell NA. Improving drug design: an update on recent applications of efficiency metrics, strategies for replacing problematic elements, and compounds in nontraditional drug space. Chem Res Toxicol. 2016;29(4):564–616.
26. 26. Young DC. Computational drug design: a guide for computational and medicinal chemists. Hoboken: John Wiley & Sons; 2009.
27. 27. Bingül AA, Pirinççioğlu N. The virtual screening and molecular docking study of new inhibitors for SARS-CoV-2 papain-like protease (PLpro). Ata-Kimya Dergisi. 2025;5(1):28–37.
28. 28. Ma Z, He S, Yuan Y, et al. Design, synthesis, and characterization of TNP-2198, a dual-targeted rifamycin–nitroimidazole conjugate with potent activity against microaerophilic and anaerobic bacterial pathogens. J Med Chem. 2022;65(6):4481–4495.
29. 29. Gökmen Karakaya M. A Different Method for Synthesis of 2-(2-Methyl-5-nitro-1H-imidazol-1-yl)acetaldehyde. J Nat Appl Sci. 2023;27(2):291-296.
30. 30. Adeoye MD, Oyebamiji AK, Ashiru MA, Adigun RA, Olalere OH, Semire B. Biological evaluation of selected metronidazole derivatives as anti-nitroreductase via in silico approach. Eclet Quim. 2022;47(4):27–36.
31. 31. Parveen S, Khalil R, Shafiq N, et al. Therapeutic switching of metronidazole anti-cancerous compounds as anti SARS-CoV-2 inhibitors: integration of QSAR, molecular docking, MD simulation and ADMET analysis. Discover Life. 2024;54(1):10.
32. 32. Merimi C, Benabbou A, Fraj E, et al. Valorization of imidazolium-based salts as next-generation antimicrobials: integrated biological evaluation, ADMET, molecular docking, and dynamics studies. ASEAN J Sci Eng. 2025;6(1):11–34.
33. 33. Fu L, Shi S, Yi J, et al. ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support. Nucleic Acids Res. 2024;52(W1):W422–W431.
34. 34. ADMETlab 3.0, accessed at https://admetlab3.scbdd.com (accessed 20.12.2025).
35. 35. Daoui O, Elkhattabi S, Chtita S, Elkhalabi R, Zgou H, Benjelloun AT. QSAR, molecular docking and ADMET properties in silico studies of novel 4,5,6,7-tetrahydrobenzo[d]thiazol-2-yl derivatives derived from dimedone as potent anti-tumor agents through inhibition of c-Met receptor tyrosine kinase. Heliyon. 2021;7(7).
36. 36. Xiong G, Wu Z, Yi J, et al. ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Res. 2021;49(W1):W5–W14.
37. 37. Pattanayak P. SwissADME predictions of drug-likeness of 5-nitroimidazole derivatives as potential antimicrobial and antifungal agents. Russ J Bioorg Chem. 2022;48(5):949–957.
38. 38. Rodríguez MA, Mijoba A, Parra-Giménez NJ, et al. Synthesis and biological evaluation against Trypanosoma cruzi and Leishmania donovani: preliminary in silico ADMET studies of 5-nitroimidazole derivatives. Eur J Med Chem Rep. 2025;13:100248.