Topological indices and QSPR analysis of drug molecules from different therapeutic classes
Zeeshan Saleem Mufti, Umm e Rubab, Aiedh Mrisi Alharthi, Gamachu Adugna Ganati · 2026
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Description
Zeeshan Saleem Mufti and co-authors test graph math in 2026 for predicting drug traits across unlike drug families. Ten drugs from seven care areas were drawn as graphs, with atoms as nodes and bonds as links. Neighborhood link counts fed three curve styles to predict nine lab-measured traits. Fit quality was judged by how much trait variance the curves explained.
Graph counts captured core structural facts even across very different drugs. Predictions held up for traits from boiling point to surface tension. Past work usually limited such models to one drug family at a time. Broad-scope graph models could screen new compounds faster.
Catalog record
| CREATOR | Zeeshan Saleem Mufti, Umm e Rubab, Aiedh Mrisi Alharthi, Gamachu Adugna Ganati |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 120988 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |