Work

Predictive modeling of influenza strain drugs using temperature-based topological indices and regression analysis via multi-criteria decision making techniques

Year: 2026

Type: article

Abstract: The proposed study is an integrated graph-theoretical and statistical model of predictive modeling and ranking of influenza strain drugs based on temperature-based topological indices. Chemical graphs were used to model drug molecules and regression models that estimated important physicochemical properties were derived. The cubic models had the best predictive ability with coefficients of determination up to [Formula: see text] of molar refractivity and polarity and [Formula: see text] of molar volume and moderate correlation of boiling and flash points ([Formula: see text]). Moreover, the multi-criteria decision-making methods (WSM and WPM) reported Azithromycin (81.25), Ritonavir (77.46), and Indinavir (72.82) as the best ranked ones. The presented solution will offer a cost-effective, interpretable, and reliable instrument of antiviral drug prioritization.

Source: Scientific Reports

DOI: 10.1038/s41598-026-45284-9

Authors: Hasnain Hayat, Sarfraz Ahmad, Muhammad Kamran Siddiqui, Fikre Bogale Petros

Institutions: COMSATS University Islamabad, Imam Mohammad ibn Saud Islamic University, Addis Ababa University

Language: English

Topic: Graph theory and applications

Subfield: Geometry and Topology

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,690