Exploration of potential drugs in treatment of hantavirus pulmonary syndrome using graph-theoretical QSPR modelingJabbar Ali, Yasir Ali, Mehar Ali Malik, Muhammad Imran, and Yilun Shang Department of Basic Sciences and Humanities, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Rawalpindi, Pakistan
E-mail: jali.bsh23ceme@student.nust.edu.pk Received: 17 December 2025 Accepted: 5 March 2026 Abstract: Hantavirus Pulmonary Syndrome (HPS) is a severe rodent-borne viral disease that can rapidly progress from influenza-like symptoms to life-threatening cardiopulmonary failure, while therapeutic options remain limited. This study develops a quantitative structure–property relationship (QSPR) framework for a curated set of fourteen HPS-related drug candidates using key physicochemical endpoints. Molecular structures are modeled as graphs, and degree-based topological descriptors are systematically derived via the M-polynomial techniques. Linear, quadratic, power, and logistic regression models are fitted to quantify structure–property relations, and model quality is assessed using R, \(R^{2}\), RMSE, SE, and F-statistics, with internal predictivity evaluated through leave-one-out cross-validation (LOOCV) using \(Q^{2}\). Results indicate that selected degree-based descriptors capture meaningful variation in the considered physicochemical properties and support reproducible, computation-driven screening of candidate compounds. In future directions, integrating pharmacokinetic and toxicity-oriented computational assessment is expected to further enhance the practical relevance of the proposed framework. Graphical Abstract Keywords: Hantavirus pulmonary syndrome; QSPR; Chemical graph theory; M-polynomial; Degree-based topological indices; Regression modeling; LOOCV Full paper is available at www.springerlink.com. DOI: 10.1007/s11696-026-04784-8
Chemical Papers 80 (6) 6543–6557 (2026) |
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