title: Systematic bioinformatics and experimental validation of yeast complexes reduces the rate of attrition during structural investigations.
abstract: For high-throughput structural studies of protein complexes of composition inferred from proteomics data, it is crucial that candidate complexes are selected accurately. Herein, we exemplify a procedure that combines a bioinformatics tool for complex selection with in vivo validation, to deliver structural results in a medium-throughout manner. We have selected a set of 20 yeast complexes, which were predicted to be feasible by either an automated bioinformatics algorithm, by manual inspection of primary data, or by literature searches. These complexes were validated with two straightforward and efficient biochemical assays, and heterologous expression technologies of complex components were then used to produce the complexes to assess their feasibility experimentally. Approximately one-half of the selected complexes were useful for structural studies, and we detail one particular success story. Our results underscore the importance of accurate target selection and validation in avoiding transient, unstable, or simply nonexistent complexes from the outset.
authors.affiliation: IBBMC-CNRS UMR8619, IFR 115, Bât. 430, Université Paris-Sud, 91405 Orsay, France.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Brooks
authors.forename: Kamil
authors.initials: K
authors.lastname: Gewartowski
authors.forename: Eirini
authors.initials: E
authors.lastname: Mitsiki
authors.forename: Juliette
authors.initials: J
authors.lastname: Létoquart
authors.forename: Roland A
authors.initials: RA
authors.lastname: Pache
authors.forename: Ysaline
authors.initials: Y
authors.lastname: Billier
authors.forename: Michela
authors.initials: M
authors.lastname: Bertero
authors.forename: Margot
authors.initials: M
authors.lastname: Corréa
authors.forename: Mariusz
authors.initials: M
authors.lastname: Czarnocki-Cieciura
authors.forename: Michal
authors.initials: M
authors.lastname: Dadlez
authors.forename: Véronique
authors.initials: V
authors.lastname: Henriot
authors.forename: Noureddine
authors.initials: N
authors.lastname: Lazar
authors.forename: Lila
authors.initials: L
authors.lastname: Delbos
authors.forename: Dorothée
authors.initials: D
authors.lastname: Lebert
authors.forename: Jan
authors.initials: J
authors.lastname: Piwowarski
authors.forename: Pascal
authors.initials: P
authors.lastname: Rochaix
authors.forename: Bettina
authors.initials: B
authors.lastname: Böttcher
authors.forename: Luis
authors.initials: L
authors.lastname: Serrano
authors.forename: Bertrand
authors.initials: B
authors.lastname: Séraphin
authors.forename: Herman
authors.initials: H
authors.lastname: van Tilbeurgh
authors.forename: Patrick
authors.initials: P
authors.lastname: Aloy
authors.forename: Anastassis
authors.initials: A
authors.lastname: Perrakis
authors.forename: Andrzej
authors.initials: A
authors.lastname: Dziembowski
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D040901:Proteomics; D012441:Saccharomyces cerevisiae / Q000737:chemistry / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D029701:Saccharomyces cerevisiae Proteins