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| Modelowanie molekularne× | Modelowanie farmakoforowe× | Topologia sieci PPI× | |
|---|---|---|---|
| Dziedzina | Bioinformatyka | Bioinformatyka | Bioinformatyka |
| Rodzina | Process / pipeline | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 1982 | 1977 | 2000 |
| Twórca≠ | Irwin Kuntz | Peter Gund | Peter Uetz |
| Typ≠ | Binding prediction pipeline | Pattern-based virtual screening pipeline | Network analysis pipeline |
| Źródło pierwotne≠ | Kuntz, I. D., Blaney, J. M., Oatley, S. J., Langridge, R., & Ferrin, T. E. (1982). A geometric approach to macromolecule-ligand interactions. Journal of Molecular Biology, 161(2), 269-288. DOI ↗ | 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 ↗ | Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., ... & Lomax, J. (2000). A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae. Nature, 403(6770), 623-627. DOI ↗ |
| Inne nazwy≠ | protein-ligand docking, binding prediction | pharmacophore pattern recognition, 3D pharmacophore | protein interaction networks, interactome analysis, network topology |
| Pokrewne≠ | 4 | 3 | 3 |
| Podsumowanie≠ | Molecular docking predicts the preferred binding orientation and affinity of a ligand (small molecule) within a protein binding pocket. Pioneered by Kuntz and colleagues in 1982, this computational method searches conformational space to find energetically favorable ligand-protein complexes, enabling rapid screening of chemical libraries for drug discovery. | 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. | Protein-protein interaction network analysis identifies and characterizes the structural properties of cellular interaction networks. Pioneered by Uetz and colleagues through large-scale yeast two-hybrid screening, this approach reveals topological features like hubs, modules, and motifs that encode functional organization and disease associations. |
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