Comparative Molecular Dynamics of Benzimidazole Scaffolds Against CDK4 and NUDT1: A Dual-Target Binding Study
Keywords:
benzimidazole, CDK4, NUDT1, molecular dynamics, MM/GBSA, dual-target inhibitorAbstract
Background: Single-target optimisation can overlook structurally distinct interactions that permit one scaffold to modulate complementary cancer pathways.
Objective: We compared the dynamic behaviour of six benzimidazole derivatives bound to CDK4 and NUDT1 to identify scaffolds with balanced dual-target potential.
Methods: Each derivative was independently docked into crystallographic binding sites of CDK4 and NUDT1. Twelve complexes were simulated for 100 ns under identical force-field settings. Binding stability was judged using ligand RMSD, protein RMSF, hydrogen-bond occupancy, solvent exposure and MM/GBSA energy.
Results: Derivative BZ-D4 showed the most balanced performance, with docking scores of -8.9 kcal/mol for CDK4 and -9.1 kcal/mol for NUDT1. It maintained at least two high-occupancy polar interactions in both targets and displayed narrow ligand-RMSD distributions throughout the final 60 ns. Mean MM/GBSA values were -34.9±4.7 kcal/mol for CDK4 and -37.1±5.0 kcal/mol for NUDT1. By contrast, BZ-D1 achieved stronger static docking to CDK4 but showed progressive loss of hinge interactions during simulation, and BZ-D6 was penalised by unstable orientation in NUDT1. Principal-component analysis demonstrated lower conformational dispersion for BZ-D4 complexes than for the comparator ligands.
Conclusion: Dynamic evaluation changed the ranking produced by docking alone and identified BZ-D4 as the most credible dual-target scaffold. The work supports simulation-based triage before synthesis and emphasises that balanced residence behaviour across two targets may be more informative than a single favourable docking score.
Publication format: research abstract. No full-text manuscript accompanies this record.
References
Miah R, Issahaku AR, Uddin MN, Hamali MA, Miah MM, Kassim K, Wilhelm A, Mohd Aluwi MFF. Benzimidazole Derivative as a Promising Targeted Therapeutic for Lung Cancer: In-Silico Approaches. J Pharm Innov. 2026;21:409. doi:10.1007/s12247-026-10615-w.
Tasnim J, Hasan MM, Hossain A, Miah MM, Hossain KR, Molla MTH, Ahmed Z, Reza AFGM, Alam MT. In silico identification of a potential NUDT1 inhibitor for cancer treatment. Sci Rep. 2026. doi:10.1038/s41598-026-66781-x.
Huang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1-13.
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607-D613.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498-2504.
Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol. 2014;8(Suppl 4):S11.
Day PJ, Cleasby A, Tickle IJ, O'Reilly M, Coyle JE, Holding FP, et al. Crystal structure of human CDK4 in complex with a D-type cyclin. Proc Natl Acad Sci U S A. 2009;106(11):4166-4170.
Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C. ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput. 2015;11(8):3696-3713.
Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA. Development and testing of a general AMBER force field. J Comput Chem. 2004;25(9):1157-1174.
Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:42717.
Banerjee P, Kemmler E, Dunkel M, Preissner R. ProTox 3.0: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 2024;52(W1):W513-W520.
Rácz A, Mihalovits LM, Bajusz D, Héberger K, Miranda-Quintana RA. Molecular dynamics simulations and diversity selection by extended continuous similarity indices. J Chem Inf Model. 2022;62(14):3415-3425.
Moukengue B, Brown HK, Charrier C, Battaglia S, Baud'Huin M, Quillard T, et al. TH1579, MTH1 inhibitor, delays tumour growth and inhibits metastases development in osteosarcoma model. EBioMedicine. 2020;53:102704.
Zhou W, Ma L, Yang J, Qiao H, Li L, Guo Q, et al. Potent and specific MTH1 inhibitors targeting gastric cancer. Cell Death Dis. 2019;10(6):434.
Zhan D, Zhang X, Li J, Ding X, Cui Y, Jia J. MTH1 inhibitor TH287 suppresses gastric cancer development through the regulation of PI3K/AKT signaling. Cancer Biother Radiopharm. 2020;35(3):223-232.
Kang N, Ma J, Hu Y, Di R, Wang L, Zhang X, et al. Targeting MutT Homolog 1 (MTH1) for breast cancer suppression by using a novel MTH1 inhibitor MA-24 with tumor-selective toxicity. Pharmaceuticals. 2024;17(3):291.
Azuaje F. Computational models for predicting drug responses in cancer research. Brief Bioinform. 2017;18(5):820-829.
Beckers M, Sturm N, Sirockin F, Fechner N, Stiefl N. Prediction of small-molecule developability using large-scale in silico ADMET models. J Med Chem. 2023;66(20):14047-14060.
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235-242.
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-461.
Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793-795.
Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discov. 2022;12(1):31-46.
Aftab H, Islam M, Şenol H, Batool Z, Ateşoğlu Ş, Çakır F, Shafiq Z. Synthesis, antiproliferative activity targeting lung cancer and in silico studies of hydroxypiperidine substituted thiosemicarbazones. Sci Rep. 2025;15(1):33402.
Ait Elmachkouri Y, Irrou E, Mague JT, Oubella A, Rehman MT, AlAjmi MF, Taha ML. Design, synthesis, and crystal structure of new C5-substituted pyrazolopyranopyrimidines: in silico studies based on network pharmacology as promising anticancer candidates for lung cancer. J Mol Struct. 2025;1324:142800.
Ferlay J, Laversanne M, Ervik M, Lam F, Colombet M, Mery L, et al. Global Cancer Observatory: Cancer Today. Lyon: International Agency for Research on Cancer; 2024.
Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74(3):229-263.
Ashrafi A, Akter Z, Modareszadeh P, Berisha E, Alemi PS, Zhang L. Current landscape of therapeutic resistance in lung cancer and promising strategies to overcome resistance. Cancers. 2022;14(19):4562.
Rivera-Concepcion J, Uprety D, Adjei AA. Challenges in the use of targeted therapies in non-small cell lung cancer. Cancer Res Treat. 2022;54(2):315-329.
Kang DH, Lee J, Im S, Chung C. Navigating the complexity of resistance in lung cancer therapy: mechanisms, organoid models, and strategies for overcoming treatment failure. Cancers. 2024;16(23):3996.
Lv S, Yang J, Lin J, Huang X, Zhao H, Zhao C, Yang L. CDK4/6 inhibitors in lung cancer: current practice and future directions. Eur Respir Rev. 2024;33:171.
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