Bandingkan kaedah

	Docking Molekular	Pemodelan Farmakofor	Topologi Rangkaian Saling Tindak Protein-Protein
Bidang	Bioinformatik	Bioinformatik	Bioinformatik
Keluarga	Process / pipeline	Process / pipeline	Process / pipeline
Tahun asal	1982	1977	2000
Pengasas	Irwin Kuntz	Peter Gund	Peter Uetz
Jenis	Binding prediction pipeline	Pattern-based virtual screening pipeline	Network analysis pipeline
Sumber perintis	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.
Alias	protein-ligand docking, binding prediction	pharmacophore pattern recognition, 3D pharmacophore	protein interaction networks, interactome analysis, network topology
Berkaitan	4	3	3
Ringkasan	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.