Σύγκριση μεθόδων

	Μοριακή Προσδέση	Μοντελοποίηση Φαρμακοφόρου	Τοπολογία Δικτύου Αλληλεπιδράσεων Πρωτεϊνών-Πρωτεϊνών
Πεδίο	Βιοπληροφορική	Βιοπληροφορική	Βιοπληροφορική
Οικογένεια	Process / pipeline	Process / pipeline	Process / pipeline
Έτος προέλευσης	1982	1977	2000
Δημιουργός	Irwin Kuntz	Peter Gund	Peter Uetz
Τύπος	Binding prediction pipeline	Pattern-based virtual screening pipeline	Network analysis pipeline
Θεμελιώδης πηγή	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.	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.	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.
Εναλλακτικές ονομασίες	protein-ligand docking, binding prediction	pharmacophore pattern recognition, 3D pharmacophore	protein interaction networks, interactome analysis, network topology
Συναφείς	4	3	3
Σύνοψη	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.