Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Фармакофорное моделирование× | QSAR× | |
|---|---|---|
| Область | Биоинформатика | Биоинформатика |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1977 | 1964 |
| Автор метода≠ | Peter Gund | Corwin Hansch |
| Тип≠ | Pattern-based virtual screening pipeline | Regression-based predictive modeling pipeline |
| Основополагающий источник≠ | Wermuth, C. G., Ganellin, C. R., Lindberg, P., & Mitscher, L. A. (1998). Glossary of terms used in medicinal chemistry. Pure and Applied Chemistry, 70(5), 1129-1143. DOI ↗ | Hansch, C. & Fujita, T. (1964). Rho-sigma-pi analysis. A method for the correlation of biological activity and chemical structure. Journal of the American Chemical Society, 86(8), 1616-1626. DOI ↗ |
| Другие названия | pharmacophore pattern recognition, 3D pharmacophore | QSAR model, quantitative structure-activity relationship |
| Связанные | 3 | 3 |
| Сводка≠ | Pharmacophore modeling identifies the spatial arrangement of molecular features (hydrogen bond donors, acceptors, aromatic rings) that are essential for biological activity. Introduced by Gund in 1977, this ligand-based method creates a three-dimensional pattern that can screen chemical libraries and design new active compounds without requiring receptor structure. | Quantitative Structure-Activity Relationship (QSAR) modeling predicts biological activity from molecular structure using statistical or machine learning models. Pioneered by Hansch in 1964, QSAR correlates numerical molecular descriptors with measured bioactivity, enabling prediction of activity for untested compounds and rational lead optimization. |
| ScholarGateНабор данных ↗ |
|
|