Sammenlign metoder

	Kryo-EM Rekonstruktion	HMMER-profilsøgning	Molekylær docking
Fagområde	Bioinformatik	Bioinformatik	Bioinformatik
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Oprindelsesår	1975	1994	1982
Ophavsperson	Joachim Frank	Sean Eddy	Irwin Kuntz
Type	Image reconstruction pipeline	Probabilistic sequence search pipeline	Binding prediction pipeline
Oprindelig kilde	Frank, J. (2002). Single-particle imaging of macromolecules by cryo-electron microscopy. Annual Review of Biophysics and Biomolecular Structure, 31, 303-319.	Krogh, A., Brown, M., Mian, I. S., Sjölander, K., & Haussler, D. (1994). Hidden Markov models in computational biology: applications to protein modeling. Journal of Molecular Biology, 235(5), 1501-1531.	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.
Aliasser	cryo-electron microscopy, cryo-EM, single-particle cryo-EM	profile-hidden Markov model, HMM profile search, HMMER	protein-ligand docking, binding prediction
Relaterede	3	3	4
Resumé	Cryo-electron microscopy (cryo-EM) determines three-dimensional macromolecular structures at atomic or near-atomic resolution by imaging proteins frozen in vitreous ice. Pioneered by Frank, Henderson, and others, this technique has revolutionized structural biology by enabling visualization of large, non-crystallizable complexes and capturing functional conformational states.	HMMER profile search identifies distant protein sequence homologs using probabilistic models of protein families, known as profile Hidden Markov Models (HMMs). Developed by Eddy and colleagues, this method captures sequence variation patterns within protein families and detects homologs with far greater sensitivity than position-weight matrices or pairwise alignment.	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.