Chemical Insights into Psoriasis Drugs via Entropy and Quantitative Structure-Property Relationship Analysis for the Applications of Environmental Nanotechnology
J. Environ. Nanotechnol., Volume 14, No 4 (December 2025) pp. 401-422
Abstract
Pharmaceutical residues released into aquatic and environmental systems are emerging contaminants of concern, creating a need for efficient computational approaches to characterize their molecular properties and support environmental assessment. This study investigates ten commonly prescribed drugs used in psoriasis treatment through degree-based topological indices and entropy measures within a quantitative structure–property relationship (QSPR) framework. The molecular structures of the selected pharmaceuticals were represented as molecular graphs, and degree-based entropy descriptors were calculated to quantify structural connectivity, molecular complexity and information content. Linear, quadratic, cubic and logarithmic regression models were developed to examine the relationships between these descriptors and selected physicochemical properties relevant to the environmental behaviour and molecular characterization of pharmaceutical compounds. The results demonstrate meaningful associations between several degree-based entropy measures and the investigated physicochemical properties, while cubic regression models generally exhibited improved predictive performance for several properties. The findings highlight the potential of graph-theoretical and entropy-based descriptors as computational tools for predicting molecular characteristics of pharmaceutical contaminants. Such approaches can contribute to preliminary environmental risk assessment, contaminant characterization and the rational evaluation of pharmaceutical molecules relevant to advanced environmental monitoring and nano-enabled remediation strategies. The study demonstrates how molecular graph descriptors can complement conventional approaches for computational assessment of emerging pharmaceutical contaminants in environmental systems
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Reference
Abubakar, M. S., Aremu, K. O., Aphane, M. and Amusa, L. B., A QSPR analysis of physical properties of antituberculosis drugs using neighbourhood degree-based topological indices and support vector regression, Heliyon., 10(7), e28260(2024).
https://doi.org/10.1016/j.heliyon.2024.e28260
Armstrong, A. W. and Read, C., Pathophysiology, clinical presentation, and treatment of psoriasis: a review, Jama., 323(19), 1945-1960(2020).
https://doi.org/10.1001/jama.2020.4006
Arockiaraj, M., Fiona, J. C. and Balasubramanian, K., Degree based hybridtopological indices and entropies of hydrogen bonded benzo-trisimidazole frameworks, J. Mol. Struct., 1314, 138740(2024).
https://doi.org/10.1016/j.molstruc.2024.138740
Awan, N. U. H., Ghaffar, A., Tawfiq, F. M., Mustafa, G., Bilal, M. and Inc, M., QSPR analysis for physiochemical properties of new potential antimalarial compounds involving topological indices, Int. J. Quantum Chem., 124(11), e27391(2024).
https://doi.org/10.1002/qua.27391
Awan, N. U. H., Ghani, M. U., Bibi, S., Kirmani, S. A. K. and Abdalla, M. E. M., A Paradigmatic Approach to the Topological Measure of Babesiosis Drugs and Estimating Physical Properties via QSPR Analysis, Heliyon., 11(1), e41615(2025).
https://doi.org/10.1016/j.heliyon.2024.e41615
Chen, Z., Dehmer, M. and Shi, Y., A note on distance-based graph entropies, Entropy., 16(10), 5416-5427(2014).
https://doi.org/10.3390/e16105416
Elder, J. T., Nair, R. P., Guo, S. W., Henseler, T., Christophers, E. and Voorhees, J. J., The genetics of psoriasis, Arch. Dermatol., 130(2), 216-224(1994).
Farooq, F. B., Parveen, S., Awan, N. U. H. and Fanja, R., Topological Descriptors and QSPR Modelling of HIV/AIDS Disease Treatment Drugs, Discrete Dyn. Nat. Soc., 2023(1), 9963241(2023).
https://doi.org/10.1155/2023/9963241
Farooq, F.B., Awan, N. U. H., Parveen, S., Idrees, N., Kanwal, S. and Abdelhaleem, T. A., Topological Indices of Novel Drugs Used in Cardiovascular Disease Treatment and Its QSPR Modeling, J. Chem., 2022(1), 9749575(2022).
https://doi.org/10.1155/2022/9749575
Gnanaraj, L. R. M., Ganesan, D. and Siddiqui, M. K., Topological indices and QSPR analysis of NSAID drugs, Polycyclic Aromat. Compd., 43(10), 9479-9495(2023).
https://doi.org/10.1080/10406638.2022.2164315
Griffiths, C. E. and Barker, J. N., Pathogenesis and clinical features of psoriasis, Lancet., 370(9583), 263-271(2007).
https://doi.org/10.1016/S0140-6736(07)61128-3
Henseler, T. and Christophers, E., Disease concomitance in psoriasis, J. Am. Acad. Dermatol., 32(6), 982-986(1995).
https://doi.org/10.1016/0190-9622(95)91336-x
Imran, M., Siddiqui, M. K., Ahmad, S., Hanif, M. F., Muhammad, M. H. and Farahani, M. R., Topological properties of benzenoid, phenylenes and nanostar dendrimers, J. Discrete Math. Sci. Cryptogr., 22(7), 1229-1248(2019).
https://doi.org/10.1080/09720529.2019.1701267
Kamiya, K., Kishimoto, M., Sugai, J., Komine, M. and Ohtsuki, M., Risk factors for the development of psoriasis, Int. J. Mol. Sci., 20(18), 4347(2019).
https://doi.org/10.3390/ijms20184347
Kirmani, S. A. K., Ali, P. and Azam, F., Topological indices and QSPR/QSAR analysis of some antiviral drugs being investigated for the treatment of COVID‐19 patients, Int. J. Quantum Chem., 121(9), e26594(2021).
https://doi.org/10.1002/qua.26594
Koam, A. N., Azeem, M., Jamil, M. K., Ahmad, A. and Hakami, K. H., Entropy measures of Y-junction based nanostructures, Ain Shams Eng. J., 14(4), 101913(2023).
https://doi.org/10.1016/j.asej.2022.101913
Kulli, V. R., Chaluvaraju, B. and Asha, T. V., Computation of Nirmala indices of some chemical networks, J. Ultra Sci. Phys. Sci A., 33(4), 30-41(2021).
https://doi.org/10.22147/jusps-A/330401
Lowes, M. A., Bowcock, A. M. and Krueger, J. G., Pathogenesis and therapy of psoriasis, Nat., 445(7130), 866-873(2007).
https://doi.org/10.1038/nature05663
Menter, A. and Griffiths, C. E., Current and future management of psoriasis, Lancet., 370(9583), 272-284(2007).
https://doi.org/10.1016/S0140-6736(07)61129-5
Nasir, S., Farooq, F. B., Awan, N. U. H. and Parveen, S., Topological indices of novel drugs used in blood cancer treatment and its QSPR modeling, AIMS Math., 7(7), 11829-11850(2022).
https://doi.org/10.3934/math.2022660
Nasir, S., Topological Descriptors of Colorectal Cancer Drugs and Characterizing Physical Properties Via QSPR Analysis, Int. J. Anal. Chem., 2025(1), 5512172(2025).
https://doi.org/10.1155/ianc/5512172
Sultana, S., Chemical application of topological indices in infertility treatment drugs and QSPR analysis, Int. J. Anal. Chem., 2023(1), 6928167(2023).
https://doi.org/10.1155/2023/6928167
Wei, J., Hanif, M. F., Mahmood, H., Siddiqui, M. K. and Hussain, M., QSPR analysis of diverse drugs using linear regression for predicting physical properties, Polycyclic Aromat. Compd., 44(7), 4850-4870(2024).
https://doi.org/10.1080/10406638.2023.2257848
Zaman, S., Yaqoob, H. S. A., Ullah, A. and Sheikh, M., QSPR analysis of some novel drugs used in blood cancer treatment via degree based topological indices and regression models, Polycyclic Aromat. Compd., 44(4), 2458-2474(2024).
https://doi.org/10.1080/10406638.2023.2217990
Zhang, X., Saif, M. J., Idrees, N., Kanwal, S., Parveen, S. and Saeed, F., QSPR analysis of drugs for treatment of schizophrenia using topological indices, ACS omega., 8(44), 41417-41426(2023).
https://doi.org/10.1021/acsomega.3c05000
Zhou, H., Mahboob, A., Rasheed, M. W., Ovais, A., Siddiqui, M. K. and Cheema, I. Z., On QSPR analysis of molecular descriptor and thermodynamic features of narcotic drugs, Polycyclic Aromat. Compd., 44(5), 3079-3099(2024).
