title: Visual proteomics.
abstract: Visual proteomics attempts to generate molecular atlases by providing the position and angular orientation of protein complexes inside of cells. This is accomplished by template matching (pattern recognition), a cross-correlation-based process that matches the structure of a specific protein complex to the densities of the whole volume or subvolume of a cell, that is typically acquired by cryoelectron tomography. Thereby, a search is performed that scans the entire volume for structural templates contained in a database. In this chapter, we primarily describe the practical experiences gained with visual proteomics during the Leptospira interrogans proteome project [Beck et al. (2009). Visual proteomics of the human pathogen Leptospira interrogans. Nat. Methods 6, 817.]. We give a practical guide how to implement the method and review critical experimental and computational aspects in detail. Based on a survey that has been undertaken for protein complexes from Desulfovibrio vulgaris, we review the difficulty of generating reference structures in detail. Finally, we discuss the high yield targets for technical improvements.
authors.affiliation: Max Planck Institute of Biochemistry, Martinsried, Germany.
authors.forename: Friedrich
authors.initials: F
authors.lastname: Förster
authors.forename: Bong-Gyoon
authors.initials: BG
authors.lastname: Han
authors.forename: Martin
authors.initials: M
authors.lastname: Beck
mesh_terms: D001426:Bacterial Proteins / Q000737:chemistry*; D018834:Chaperonin 60 / Q000737:chemistry; D019295:Computational Biology / Q000379:methods; D020285:Cryoelectron Microscopy / Q000379:methods; D016969:Desulfovibrio vulgaris / Q000737:chemistry / Q000648:ultrastructure; D007921:Leptospira interrogans / Q000737:chemistry / Q000648:ultrastructure; D020836:Protein Structure, Quaternary; D040901:Proteomics / Q000379:methods*; D012984:Software; D014054:Tomography / Q000379:methods
chemical_list: D001426:Bacterial Proteins; D018834:Chaperonin 60