A series of novel Schiff bases (1A–1I) was synthesized from 5-(1H-indol-2-yl)-1,3,4-thiadiazol-2-amine (ITA) through condensation with substituted aromatic aldehydes and acetophenones under reflux conditions. The synthesized compounds were characterized by melting point, FT-IR, 1H NMR, and EI-MS analyses. Formation of the Schiff bases was confirmed by the characteristic C=N stretching absorption at 1611–1636 cm?¹. Among the synthesized derivatives, the 2-chlorophenyl analogue 1H exhibited the most promising antibacterial activity, particularly against E. coli and S. typhi, whereas compounds 1B and 1D showed comparatively better activity against Gram-positive bacteria. Compound 1E also demonstrated notable activity against Gram-negative strains. Pharmacophore modelling following MMFF94 minimization revealed important hydrophobic/lipophilic, hydrogen-bond donor, and hydrogen-bond acceptor features. Overall, structural modification of the Schiff-base aryl moiety influenced both antibacterial activity and pharmacophoric characteristics, with compound 1H identified as the most promising candidate for further optimization.
Introduction
This study focuses on the design, synthesis, characterization, antibacterial evaluation, and pharmacophore modelling of indole-containing Schiff bases based on a 1,3,4-thiadiazole scaffold. The 1,3,4-thiadiazole ring is an important pharmacophore in medicinal chemistry because of its electronic properties, hydrogen-bonding capability, structural flexibility, and reported antibacterial, antifungal, antiviral, and anti-inflammatory activities. A series of nine Schiff bases (1A–1I) was developed to investigate how different substituents influence antibacterial activity and pharmacophoric features.
The key intermediate, 5-(1H-indol-2-yl)-1,3,4-thiadiazol-2-amine (ITA), was synthesized by reacting indole-2-carboxylic acid with thiosemicarbazide and POCl?, giving a 64% yield. ITA was subsequently condensed with substituted aromatic aldehydes and acetophenones in glacial acetic acid to produce Schiff bases 1A–1I, with yields ranging from 57% to 70%. Structural characterization was performed using FT-IR, ¹H NMR, GC-MS, melting-point analysis, and TLC. The characteristic imine C=N bands and N=CH proton signals confirmed Schiff-base formation, while additional spectral signals verified hydroxyl, methoxy, nitro, chloro, and methyl substituents.
Preliminary antibacterial activity was evaluated using the disc diffusion method at 40 μg/disc against E. coli, S. typhi, S. aureus, and P. acnes, with tetracycline as the reference drug. Among the synthesized compounds, compound 1H showed the strongest overall antibacterial activity, producing inhibition zones of approximately 24–25 mm against the Gram-negative bacteria and 22–23 mm against the Gram-positive bacteria. Compound 1E also showed notable activity against E. coli and S. typhi, while phenolic derivatives such as 1B and 1D demonstrated comparatively stronger activity against Gram-positive organisms. These results suggest that substituent type and hydrogen-bonding characteristics influence antibacterial performance; however, inhibition-zone measurements alone cannot establish MIC values or the precise mechanism of action.
Pharmacophore models were developed using ChemSketch, Avogadro, Open3Dalign, and PyMOL with the LIQUID plugin. The models identified hydrophobic/lipophilic, hydrogen-bond donor (HBD), and hydrogen-bond acceptor (HBA) regions and were used to relate molecular structure to antibacterial activity. The analysis indicated that phenolic and nitro substituents increase hydrogen-bond donor/acceptor characteristics, whereas the 2-chlorophenyl substituent in compound 1H provides a favorable combination of hydrophobicity, molecular shape, and retained HBD/HBA functionality.
Conclusion
A series of indole -linked 1,3,4-thiadiazole Schiff base of aromatic aldehyde/ketone was synthesized and characterized by FT-IR, 1HNMR and mass spectrometry. The presence of imine, indole NH, and substituent -specific functional group were identified successfully. Disc-diffusion screening showed that derivative 2H was the most active against both gram positive and negative bacteria. Compound 2E showed good antibacterial activity against gram negative bacteria, whereas 2B and 2D showed promising activity against Gram-positive bacteria. Pharmacophore analysis indicated a common hydrophobic aromatic–thiadiazole framework with substitution-dependent donor and acceptor features.
Overall, Schiff base derivative 2H showed the highest biological activity and can be consider a promising lead compound for further study. Further research, including MIC determination, evaluation of additional compounds, and molecular modelling, is useful to better understand the structure-activity relationship
References
[1] Matysiak, J. (2015). Biological and pharmacological activities of 1, 3, 4-thiadiazole based compounds. Mini reviews in medicinal chemistry, 15(9), 762-775.
[2] Han, X., Yu, Y. L., Hu, Y. S., & Liu, X. H. (2021). 1, 3, 4-thiadiazole: A privileged scaffold for drug design and development. Current Topics in Medicinal Chemistry, 21(28), 2546-2573.
[3] Bala, M., Piplani, P., Ankalgi, A., Jain, A., & Chandel, L. (2023). 1, 3, 4-Thiadiazole: A versatile pharmacophore of medicinal significance. Medicinal Chemistry, 19(8), 730-756.
[4] Kumar, D., Aggarwal, N., Kumar, V., Chopra, H., Marwaha, R. K., & Sharma, R. (2024). Emerging synthetic strategies and pharmacological insights of 1, 3, 4-thiadiazole derivatives: a comprehensive review. Future Medicinal Chemistry, 16(6), 563-581.
[5] Jain, A. K., Sharma, S., Vaidya, A., Ravichandran, V., & Agrawal, R. K. (2013). 1,3,4-Thiadiazole and its derivatives: A review on recent progress in biological activities. Chemical Biology & Drug Design, 81(5), 557–576.
[6] Sawarkar, H. S., Singh, M., Shrivastav, B., & Bakal, R. L. (2021). 1, 3, 4-Thiadiazole Derivatives as an Antimicrobial: An Update. Journal of Pharmaceutical Research International, 33(62A), 232-257.
[7] Anthwal, T., Paliwal, S., & Nain, S. (2022). Diverse biological activities of 1, 3, 4-thiadiazole scaffold. Chemistry, 4(4).
[8] Senthilraja, M. (2022). A review on thiadiazoles.
[9] Obakachi, V. A., Kushwaha, B., Kushwaha, N. D., Mokoena, S., Ganai, A. M., Pathan, T. K., ... & Karpoormath, R. (2021). Synthetic and anti-cancer activity aspects of 1, 3, 4-thiadiazole containing bioactive molecules: A concise review. Journal of Sulfur Chemistry, 42(6), 670-691.
[10] Szeliga, M. (2020). Thiadiazole derivatives as anticancer agents: M. Szeliga. Pharmacological Reports, 72(5), 1079-1100.
[11] Lu, X., Yang, H., Chen, Y., Li, Q., He, S. Y., Jiang, X., ... & Sun, H. (2018). The development of pharmacophore modeling: Generation and recent applications in drug discovery. Current pharmaceutical design, 24(29), 3424-3439.
[12] Qing, X., Yin Lee, X., De Raeymaeker, J., RH Tame, J., YJ Zhang, K., De Maeyer, M., & RD Voet, A. (2014). Pharmacophore modeling: advances, limitations, and current utility in drug discovery. Journal of Receptor, Ligand and Channel Research, 81-92.
[13] Kaserer, T., Beck, K. R., Akram, M., Odermatt, A., & Schuster, D. (2015). Pharmacophore models and pharmacophore-based virtual screening: concepts and applications exemplified on hydroxysteroid dehydrogenases. Molecules, 20(12), 22799-22832.
[14] Wolber, G., & Langer, T. (2005). LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. Journal of Chemical Information and Computer Sciences, 45(1), 160-169.
[15] Masand, V. H., Mahajan, D. T., Maldhure, A. K., & Rastija, V. (2016). Quantitative structure–activity relationships (QSARs) and pharmacophore modeling for human African trypanosomiasis (HAT) activity of pyridyl benzamides and 3-(oxazolo [4, 5-b] pyridin-2-yl) anilides. Medicinal chemistry research, 25(10), 2324-2334.
[16] Martin, Y. C., Abagyan, R., Ferenczy, G. G., Gillet, V. J., Oprea, T. I., Ulander, J., Winkler, D., & Zefirov, N. S. (2016). Glossary of terms used in computational drug design, Part II (IUPAC Recommendations 2015). Pure and Applied Chemistry, 88(3), 239–264.
[17] Yuan, S., Chan, H. S., & Hu, Z. (2017). Using PyMOL as a platform for computational drug design. Wiley Interdisciplinary Reviews: Computational Molecular Science, 7(2), e1298.
[18] Masand, V. H., & Rastija, V. (2017). PyDescriptor: A new PyMOL plugin for calculating thousands of easily understandable molecular descriptors. Chemometrics and Intelligent Laboratory Systems, 169, 12-18.
[19] Masand, V. H., El-Sayed, N. N., Mahajan, D. T., & Rastija, V. (2017). QSAR analysis for 6-arylpyrazine-2-carboxamides as Trypanosoma brucei inhibitors. SAR and QSAR in Environmental Research, 28(2), 165-177.
[20] Masand, V. H., El-Sayed, N. N., Mahajan, D. T., Mercader, A. G., Alafeefy, A. M., & Shibi, I. G. (2017). QSAR modelling for anti-human African trypanosomiasis activity of substituted 2-Phenylimidazopyridines. Journal of Molecular Structure, 1130, 711-718.
[21] Raj, V., Aboumanei, M. H., Rai, A., Verma, S. P., Singh, A. K., Keshari, A. K., & Saha, S. (2020). Pharmacophore and 3d-Qsar Modeling of New 1, 3, 4-Thiadiazole Derivatives: Specificity to Colorectal Cancer. Pharmaceutical Chemistry Journal, 54(1), 12-25.
[22] Khedkar, S. A., Malde, A. K., Coutinho, E. C., & Srivastava, S. (2007). Pharmacophore modeling in drug discovery and development: an overview. Medicinal Chemistry, 3(2), 187-197.
[23] Yadav, A., & Mohite, S. (2020). Pharmacophore Mapping and Virtual Screening. Int J Sci Res Chemi, 5(5), 77-80.
[24] Ghosh, R., Roy, S., Rakshit, G., Singh, N. K., & Maiti, N. J. (2025). Pharmacophore modeling in drug design. Computational Methods for Rational Drug Design, 167-194.