Porovnať metódy

	Homologické modelovanie	Molekulárne dokovanie	Topológia sietí proteín-proteínových interakcií
Odbor	Bioinformatika	Bioinformatika	Bioinformatika
Rodina	Process / pipeline	Process / pipeline	Process / pipeline
Rok vzniku	1993	1982	2000
Tvorca	Andrej Sali	Irwin Kuntz	Peter Uetz
Typ	Comparative structure prediction pipeline	Binding prediction pipeline	Network analysis pipeline
Pôvodný zdroj	Sali, A. & Blundell, T. L. (1993). Comparative protein modelling by satisfaction of spatial restraints. Journal of Molecular Biology, 234(3), 779-815.	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.	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.
Ďalšie názvy	comparative modeling, template-based modeling	protein-ligand docking, binding prediction	protein interaction networks, interactome analysis, network topology
Príbuzné	4	4	3
Zhrnutie	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.	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.	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.