Σύγκριση μεθόδων

	Μοντελοποίηση Ομολογίας	Μοντελοποίηση Φαρμακοφόρου	Τοπολογία Δικτύου Αλληλεπιδράσεων Πρωτεϊνών-Πρωτεϊνών
Πεδίο	Βιοπληροφορική	Βιοπληροφορική	Βιοπληροφορική
Οικογένεια	Process / pipeline	Process / pipeline	Process / pipeline
Έτος προέλευσης	1993	1977	2000
Δημιουργός	Andrej Sali	Peter Gund	Peter Uetz
Τύπος	Comparative structure prediction pipeline	Pattern-based virtual screening pipeline	Network analysis pipeline
Θεμελιώδης πηγή	Sali, A. & Blundell, T. L. (1993). Comparative protein modelling by satisfaction of spatial restraints. Journal of Molecular Biology, 234(3), 779-815.	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	comparative modeling, template-based modeling	pharmacophore pattern recognition, 3D pharmacophore	protein interaction networks, interactome analysis, network topology
Συναφείς	4	3	3
Σύνοψη	Homology modeling, also called comparative modeling, predicts the three-dimensional structure of a protein using an experimentally-solved structure of a homologous protein as a template. Introduced by Sali and Blundell in 1993, this method exploits the principle that homologous proteins share similar spatial structures despite differing in amino acid sequence.	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.