Letter to Editor
BibTex RIS Cite

In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors

Year 2026, Volume: 10 Issue: 1, 110 - 130

Abstract

The study investigates the promising role of new 1,3,4-oxadiazole and 1,3,4-thiadiazole derivatives (A1–A6) as potent epidermal growth factor receptor (EGFR) inhibitors, which is a crucial therapeutic target in non-small cell lung cancer (NSCLC). Using extensive in silico approaches, by combined molecular docking, molecular dynamics (MD) simulations, and ADMET profiling to assess the pharmacological potential of these compounds. Because EGFR is crucial in NSCLC, mutations in this receptor promote tumor growth and resistance to current tyrosine kinase inhibitors (TKIs) including Erlotinib. Although initially very effective, first-generation TKIs are often eventually rendered ineffective by resistance mechanisms such as T790M mutations, therefore innovative inhibitors with improved efficacy and stability are warranted. The process began with ligand preparation, which was performed through ChemDraw and Chem3D to minimize energy, and the computational evaluations were conducted using Schrödinger Suites. All compounds showed good adherence to Lipinski’s Rule of Five, indicating their drug-likeness, as shown by ADMET statistically analyzed data. The molecular docking showed that the derivatives have better binding affinities than Erlotinib and the compound A1 and A2 which have PLPfitness 90.61 and 83.77, respectively. Robust hydrogen bonding and hydrophobic interaction with the essential EGFR residues such as THR830 and THR766 was credited for these results. Molecular dynamics (MD) simulations further supported the stability of the complex, showing a 100-nanosecond trajectory with root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses confirming structural stability and stability of ligand binding in the A1-EGFR complex. Pharmacokinetic assessments highlighted the compounds' favorable absorption, distribution, and low cardiotoxicity risks. Candidate A1 (Caco-2, 2636.59 nm/sec, LogP, 4.19) showed the highest internal permeability as well as optimal lipophilicity and binding interactions, respectively. Specifically, Specifically, A1 shows a stable interaction with key residues in the EGFR active site during 100nm of simulation, thereby supporting its role as a selective inhibitor. Consequently, A1 emerges as a promising candidate for experimental validation and further drug development to treat EGFR-driven NSCLC. This study highlights the power of computational methods in the early stage of drug discovery.

References

  • [1] H. Sun, P. Saeedi, S. Karuranga, M. Pinkepank, K. Ogurtsova et al., IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045, Diabetes Research and Clinical Practice 183 (2022) 109119.
  • [2] J. Butayeva, Z. A. Ratan, S. Downie, and H. Hosseinzadeh, The impact of health literacy interventions on glycemic control and self-management outcomes among type 2 diabetes mellitus: A systematic review, Journal of Diabetes 15 (2023) 724-735.
  • [3] Z. Wang, R. Li, X. Chen, H. Ren, C. Wang et al., Network pharmacology, molecular docking and experimental validation to elucidate the anti-T2DM mechanism of Lanxangia tsaoko, Fitoterapia 178 (2024) 106117.
  • [4] P. Majety, F. A. Lozada Orquera, D. Edem, and O. Hamdy, Pharmacological approaches to the prevention of type 2 diabetes mellitus, (in English), Front Endocrinol 14 (2023) 1118848.
  • [5] J. Su, Y. Luo, S. Hu, L. Tang, and S. Ouyang, Advances in Research on Type 2 Diabetes Mellitus Targets and Therapeutic Agents, International Journal of Molecular Sciences 24 (2023) 13381.
  • [6] X. Meng, X. Liu, J. Tan, Q. Sheng, D. Zhang et al., From Xiaoke to diabetes mellitus: a review of the research progress in traditional Chinese medicine for diabetes mellitus treatment, Chinese Medicine 18 (2023) 75.
  • [7] A. K. Kandeda, S. Nodeina, and S. T. Mabou, An aqueous extract of Syzygium cumini protects against kainate-induced status epilepticus and amnesia: evidence for antioxidant and anti-inflammatory intervention, Metabolic Brain Disease 37 (2022) 2581-2602.
  • [8] M. Abdin, Y. S. Hamed, H. M. S. Akhtar, D. Chen, G. Chen et al., Antioxidant and anti-inflammatory activities of target anthocyanins di-glucosides isolated from Syzygium cumini pulp by high speed counter-current chromatography, Journal of Food Biochemistry 44 (2020) e13209.
  • [9] B. Singh, J. P. Singh, A. Kaur, and N. Singh, Insights into the phenolic compounds present in jambolan (Syzygium cumini) along with their health-promoting effects, International Journal of Food Science & Technology 53 (2018) 2431-2447.
  • [10] S. Srivastava and D. Chandra, Pharmacological potentials of Syzygium cumini: a review, Journal of the Science of Food and Agriculture 93 (2013) 2084-2093.
  • [11] S. Li and B. Zhang, Traditional Chinese medicine network pharmacology: theory, methodology and application, Chinese Journal of Natural Medicines 11 (2013) 110-120.
  • [12] S. R. Morais and A. K, Unlocking the therapeutic potential of nolatrexed in glioblastoma multiforme through quantum mechanics, network pharmacology, molecular docking and ADMET analysis, (in en), Turkish Computational and Theoretical Chemistry 9 96-110.
  • [13] M. S. Zubair, S. Maulana, A. Widodo, R. Pitopang, M. Arba, and M. Hariono, GC-MS, LC-MS/MS, docking and molecular dynamics approaches to identify potential SARS-CoV-2 3-chymotrypsin-like protease inhibitors from Zingiber officinale Roscoe, Molecules 26 (2021) 5230.
  • [14] A. Daina, O. Michielin, and V. Zoete, SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules, Scientific Reports 7 (2017) 42717.
  • [15] A. Daina, O. Michielin, and V. Zoete, SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules, Nucleic Acids Research 47 (2019) W357-W364.
  • [16] M. J. Keiser, B. L. Roth, B. N. Armbruster, P. Ernsberger, J. J. Irwin, and B. K. Shoichet, Relating protein pharmacology by ligand chemistry, Nature Biotechnology 25 (2007) 197-206.
  • [17] M. Rebhan, V. Chalifa-Caspi, J. Prilusky, and D. Lancet, GeneCards: a novel functional genomics compendium with automated data mining and query reformulation support, Bioinformatics 14 (1998) 656-664.
  • [18] J. S. Amberger, C. A. Bocchini, F. Schiettecatte, A. F. Scott, and A. Hamosh, OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders, Nucleic Acids Research 43 (2015) D789-D798.
  • [19] J. Piñero, J. Saüch, F. Sanz, and L. I. Furlong, The DisGeNET cytoscape app: Exploring and visualizing disease genomics data, Computational and Structural Biotechnology Journal 19 (2021) 2960-2967.
  • [20] L.-R. Jiang, Y. Qin, J.-L. Nong, and H. An, Network pharmacology analysis of pharmacological mechanisms underlying the anti-type 2 diabetes mellitus effect of guava leaf, Arabian Journal of Chemistry 14 (2021) 103143.
  • [21] P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang et al., Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks, Genome Research10.1101/gr.1239303 13 (2003) 2498-2504.
  • [22] M. Kanehisa, M. Furumichi, M. Tanabe, Y. Sato, and K. Morishima, KEGG: new perspectives on genomes, pathways, diseases and drugs, Nucleic Acids Research 45 (2017) D353-D361.
  • [23] Y. Zhou, B. Zhou, L. Pache, M. Chang, A. H. Khodabakhshi et al., Metascape provides a biologist-oriented resource for the analysis of systems-level datasets, Nature Communications 10 (2019) 1523.
  • [24] S. X. Ge, D. Jung, and R. Yao, ShinyGO: a graphical gene-set enrichment tool for animals and plants, Bioinformatics 36 (2020) 2628-2629.
  • [25] G. M. Sastry, M. Adzhigirey, T. Day, R. Annabhimoju, and W. Sherman, Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments, Journal of Computer-Aided Molecular Design 27 (2013) 221-34.
  • [26] M. Arba, S. T. Wahyudi, D. J. Brunt, N. Paradis, and C. Wu, Mechanistic insight on the remdesivir binding to RNA-Dependent RNA polymerase (RdRp) of SARS-cov-2, Computers in Biology and Medicine 129 (2021) 104156.
  • [27] D. C. Patel, K. R. Hausman, M. Arba, A. Tran, P. M. Lakernick, and C. Wu, Novel inhibitors to ADP ribose phosphatase of SARS-CoV-2 identified by structure-based high throughput virtual screening and molecular dynamics simulations, Computers in Biology and Medicine 140 (2022) 105084.
  • [28] S. Kumar, S., A. Sajeli Begum, K. Hira, S. Niazi, B. R. Prashantha Kumar et al., Structure-based design and synthesis of new 4-methylcoumarin-based lignans as pro-inflammatory cytokines (TNF-α, IL-6 and IL-1β) inhibitors, Bioorganic Chemistry 89 (2019) 102991.
  • [29] Q. Dong, G. Ren, Y. Li, and D. Hao, Network pharmacology analysis and experimental validation to explore the mechanism of kaempferol in the treatment of osteoporosis, Scientific Reports 14 (2024) 7088.
  • [30] S. W. Vetter, Chapter Five - Glycated Serum Albumin and AGE Receptors, in Advances in Clinical Chemistry, vol. 72, G. S. Makowski, Ed.: Elsevier, 2015, 205-275.
  • [31] D. Sanajou, A. Ghorbani Haghjo, H. Argani, and S. Aslani, AGE-RAGE axis blockade in diabetic nephropathy: Current status and future directions, European Journal of Pharmacology 833 (2018) 158-164.
  • [32] X. Wen, C. Lv, R. Zhou, Y. Wang, X. Zhou, and S. Qin, The Molecular Mechanism Underlying the Therapeutic Effect of Dihydromyricetin on Type 2 Diabetes Mellitus Based on Network Pharmacology, Molecular Docking, and Transcriptomics, Foods 13 20242. doi: 10.3390/foods13020344
  • [33] K. Taguchi and K. Fukami, RAGE signaling regulates the progression of diabetic complications, Frontiers in PharmacologyReview 14 (2023).
  • [34] T. Lanez, A. Yahiaoui, N. Benyza, A. Messai, and L. Elhafnaoui, In silico research on Novel Derivatives of N-(Acetylphenyl)-N-Ferrocenylmethyl-3-nitroaniline as DNA Binding Agents: Using Diverse Computational Methods, including Molecular Docking and ADME/Toxicity Assessment, (in en), Turkish Computational and Theoretical Chemistry 8 (2024) 93-102.
  • [35] O. Ünsalan, T. Ertan-bolelli, K. Bolelli, C. Altunayar-unsalan, and B. Yılmaz, Effects of flavonoids on SARS–CoV–2 main protease (6W63): A molecular docking study, (in en), Turkish Computational and Theoretical Chemistry 7 (2023) 34-57.
  • [36] M. Aswad, R. Nugraha, and R. Yulianty, Potency of Bisindoles from Caulerpa racemosa in Handling Diabetes-Related Complications: In silico ADMET Properties and Molecular Docking Simulations, (in en), Turkish Computational and Theoretical Chemistry 8 (2024) 99-107.
  • [37] E. Edache, A. Uzairu, P. A. Mamza, and G. A. Shallangwa, Investigation of salicylidene acylhydrazides derivatives: Molecular Docking, ADMET, and Molecular Dynamic Simulations were used in conjunction towards the design of new Yersinia pseudotuberculosis inhibitors, (in en), Turkish Computational and Theoretical Chemistry 6 (2022) 9-30.
There are 37 citations in total.

Details

Primary Language English
Subjects Molecular Imaging
Journal Section Research Article
Authors

Ahmed Haloob 0009-0008-1463-1782

Monther Faisal 0000-0002-2069-4121

Ayad Mr Raauf 0000-0002-8957-2093

Early Pub Date May 22, 2025
Publication Date
Submission Date January 10, 2025
Acceptance Date April 13, 2025
Published in Issue Year 2026 Volume: 10 Issue: 1

Cite

APA Haloob, A., Faisal, M., & Mr Raauf, A. (2025). In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors. Turkish Computational and Theoretical Chemistry, 10(1), 110-130.
AMA Haloob A, Faisal M, Mr Raauf A. In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors. Turkish Comp Theo Chem (TC&TC). May 2025;10(1):110-130.
Chicago Haloob, Ahmed, Monther Faisal, and Ayad Mr Raauf. “In Silico Design, Molecular Docking, Molecular Dynamics Simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives As Potential EGFR Inhibitors”. Turkish Computational and Theoretical Chemistry 10, no. 1 (May 2025): 110-30.
EndNote Haloob A, Faisal M, Mr Raauf A (May 1, 2025) In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors. Turkish Computational and Theoretical Chemistry 10 1 110–130.
IEEE A. Haloob, M. Faisal, and A. Mr Raauf, “In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors”, Turkish Comp Theo Chem (TC&TC), vol. 10, no. 1, pp. 110–130, 2025.
ISNAD Haloob, Ahmed et al. “In Silico Design, Molecular Docking, Molecular Dynamics Simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives As Potential EGFR Inhibitors”. Turkish Computational and Theoretical Chemistry 10/1 (May 2025), 110-130.
JAMA Haloob A, Faisal M, Mr Raauf A. In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors. Turkish Comp Theo Chem (TC&TC). 2025;10:110–130.
MLA Haloob, Ahmed et al. “In Silico Design, Molecular Docking, Molecular Dynamics Simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives As Potential EGFR Inhibitors”. Turkish Computational and Theoretical Chemistry, vol. 10, no. 1, 2025, pp. 110-3.
Vancouver Haloob A, Faisal M, Mr Raauf A. In Silico Design, Molecular Docking, Molecular dynamics simulations, and Pharmacokinetics Insights of Novel 1,3,4-Oxadiazole and 1,3,4-Thiadiazole Derivatives as Potential EGFR Inhibitors. Turkish Comp Theo Chem (TC&TC). 2025;10(1):110-3.

Journal Full Title: Turkish Computational and Theoretical Chemistry


Journal Abbreviated Title: Turkish Comp Theo Chem (TC&TC)