Utılızıng Computatıonal Chemıstry To Unravel The Molecular Mechanısms of Cystıc Fıbrosıs Mutatıons And Develop Targeted Therapeutıcs

Year 2025, Volume: 8 Issue: 2, 158 - 170, 23.12.2025

Muhammad Tukur Ibrahim , Muhammad Suleiman Darma , Sanı Uba

https://doi.org/10.54565/jphcfum.1721789

Abstract

Cystic fibrosis (CF) is a life-shortening genetic disorder caused by mutations in the CFTR gene, leading to dysfunctional chloride ion transport and associated complications. This study employs computational chemistry to explore the molecular mechanisms underlying CF and to aid the development of targeted therapeutics. Twenty-seven ligand derivatives from 3-(2-benzyloxyphenyl) isoxazoles and isoxazolines previously reported as CFTR activators were analyzed and compared to genistein, a known CF therapeutic. Ligand structures were optimized using Density Functional Theory (DFT), and molecular descriptors were computed with PaDEL software. Using Genetic Function Approximation (GFA) via Material Studio, Quantitative Structure-Activity Relationship (QSAR) models were developed to correlate molecular features with biological activity (pIC₅₀). The top model (R² = 0.974) demonstrated high predictive power and reliability, validated through cross-validation and applicability domain analysis. Key descriptors such as SpDiam_Dt, GATS4v, and MATS7i significantly influenced model performance, offering insights into molecular traits critical for CF treatment efficacy. These findings highlight the potential of computational approaches in accelerating drug discovery for cystic fibrosis by identifying and optimizing promising lead compounds.

Keywords

Cystic Fibrosis (CF) , CFTR Mutations , Computational Chemistry , QSAR Modeling , and Density Functional Theory (DFT)

References

• [1] Allen J.L., Panitch H.B. and Rubenstein R.C. (2016). Cystic Fibrosis. CRC Press. p. 92. ISBN 9781439801826.
• [2] Massie J. and Delatycki M.B. (2013). "Cystic fibrosis carrier screening". Paediatric Respiratory Reviews. 14 (4): 270–275.
• [3] Nazareth D. and Walshaw M. (2013); "Coming of age in cystic fibrosis - transition from pediatric to adult care". Clinical Medicine. 13 (5): 482–486. doi:10.7861/clinmedicine.13-5-482.
• [4] Agrawal A., Mehta D., Sikachi R.R., Du D., and Wang J. (2017). "Nationwide trends of hospitalizations for cystic fibrosis in the United States from 2003 to 2013". Intractable & Rare Diseases Research. 6 (3): 191–198.
• [5] Padoan R., Cirilli N., Falchetti D. and Cesana B.M. (2019). "Risk factors for adverse outcome in infancy in meconium ileus cystic fibrosis infants: A multicentre Italian study". Journal of Cystic Fibrosis. 18 (6): 863–868. doi:10.1016/j.jcf.2019.07.003.
• [6] www.alilamedicalmedia.com/page/1?hits=2&per_page=100&search=Cystic+fibrosis#media00e94db2 -09e1-11e3-a807-dded242d5282
• [7] National Human Genome Research Institute (2020). Cystic fibrosis overview. Retrieved from www.genome.gov/Genetic-Disorders/Cystic-Fibrosis
• [8] Errol G. Lewars (2016) Introduction to Quantum Mechanics in Computational Chemistry Computational Chemistry. Springer ISBN: 978-3-319-30914-9 https://doi.org/10.1007/978-3-319-30916-3_4
• [9] Amico G., Brandas C., Moran O., and Baroni D. (2019); Unravelling the Regions of Mutant F508del-CFTR More Susceptible to the Action of Four Cystic Fibrosis Correctors. Int J Mol Sci.
• [10] Anjaneyulu B., Goswami S. and Banik P. (2024) Revolution of Artificial Intelligence in Computational Chemistry Breakthroughs. Chemistry Africa 7, 3443–3459.
• [11] Robert E. Sammelson, T. M, Luis J. V. Galietta, A. S. Verkman, and Mark J. Kurth. (2003). 3-(2-Benzyloxyphenyl) isoxazoles and Isoxazolines: Synthesis and Evaluation as CFTR Activators. Bioorganic & Medicinal Chemistry Letters 13 2509–2512.
• [12] Ibrahim, M. T., Uzairu, A., Uba, S., & Shallangwa, G. A. (2020). Computational modeling of novel quinazoline derivatives as potent epidermal growth factor receptor inhibitors. Heliyon, 6(2).
• [13] National Center for Biotechnology Information (2024). PubChem Bioassay Record for AID 47327, Source: ChEMBL. Retrieved December 23, 2024 from https://pubchem.ncbi.nlm.nih.gov/bioassay/47327.
• [14] Mustapha A., Shallangwa G., Ibrahim M.T., Bello A.U., Arthur D. and Uzairu A. (2018). QSAR studies on some C14-urea tetrandrine compounds as potent anti-cancer agents against Leukemia cell line (K562). JOTCSA. 5(3):1391–402.
• [15] Gideon A., S. and Shola E. A. (2021). Binding profile of protein-ligand inhibitor complex and structure-based design of new potent compounds via computer-aided virtual screening. Journal of Clinical Tuberculosis and Other Mycobacterial Diseases 24 (1) 1-18
• [16] Sagiru H. A., Adamu U., Muhammad T. I. and Abdullahi B. U. (2021); Chemo‑informatics activity prediction, ligand-based drug design, Molecular docking and pharmacokinetics studies of some series of 4, 6‑diaryl‑2‑pyrimidinamine derivatives as anti‑cancer agents. Bull Natl Res Cent 45:167 1-22.
• [17] Maryam I. U. (2024). ADME-TOX and Ligand-Protein Interaction of P-Substituted (E)-benzylidenchroman-4-ones Derivatives for the Treatment of Dementia. FRsCS Vol. 3 No. 4 pp17-30. https://doi.org/10.33003/frscs_2024_0304/02.
• [18] Muhammad Tukur Ibrahim, Adamu Uzairu, Gideon Adamu Shallangwa, and Abdulqadir Ibrahim (2020); In-silico studies of some oxadiazoles derivatives as anti-diabetic compounds. Journal of King Saud University – Science 32 423–432.
• [19] Lennart Eriksson, Joanna Jaworska, Andrew P. Worth, Mark T.D. Cronin, Robert M. McDowell, and Paola Gramatica. (2003). Methods for Reliability and Uncertainty Assessment and for Applicability Evaluations of Classification- and Regression-Based QSARs. Environmental Health Perspectives • Volume 111 | Number 10 | Page: 1361-1375.
• [20] Jonathan F. F., Luba A. A., Timothy J. J. Liying L. C., Joseph N. K., Lihua H., Andrei A. A., Drew S. G., John R. R. and James Z. C. (2018). Cryo-EM visualization of an active high open probability CFTR anion channel. Biochemistry 57, 43, 6234–6246.
• [21] Emanuela Pesce et. al., (2015). Synthesis and structure-activity relationship of aminoarylthiazole derivatives as correctors of the chloride transport defect in cystic fibrosis. European Journal of Medicinal Chemistry 99 14-35.
• [22] P. Ertl, B. Rohde, P. Selzer, Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. J.Med.Chem. 43, 3714-3717 (2000).
• [23] Andrea Mauri (2020). alvaDesc: A Tool to Calculate and Analyze Molecular Descriptors and Fingerprints. Methods in Pharmacology and Toxicology· Chapter 32. DOI: 10.1007/978-1-0716-0150-1_32.
• [24] Wanga Q. Tunzelmann N. (2000). Complexity and the functions of the firm: breadth and depth. Research Policy 29: 805–818.
• [25] Grigoriadis D. E., Hoare S. R., Lechner S. M., Slee D. H. and Williams J. A. (2009) Drugability of extracellular targets: discovery of small molecule drugs targeting allosteric, functional, and subunit-selective sites on GPCRs and ion channels. Neuropsychopharmacology. 34(1):106-25. doi: 10.1038/npp.2008.149. Epub 2008 Sep 17. PMID: 18800070.