RESUMO
The TB Structural Genomics Consortium is an organization devoted to encouraging, coordinating, and facilitating the determination and analysis of structures of proteins from Mycobacterium tuberculosis. The Consortium members hope to work together with other M. tuberculosis researchers to identify M. tuberculosis proteins for which structural information could provide important biological information, to analyze and interpret structures of M. tuberculosis proteins, and to work collaboratively to test ideas about M. tuberculosis protein function that are suggested by structure or related to structural information. This review describes the TB Structural Genomics Consortium and some of the proteins for which the Consortium is in the progress of determining three-dimensional structures.
Assuntos
Genômica/organização & administração , Mycobacterium tuberculosis/genética , Sequência de Aminoácidos , Proteínas de Bactérias/genética , Genoma Bacteriano , Humanos , Cooperação Internacional , Dados de Sequência Molecular , Mycobacterium tuberculosis/metabolismo , Conformação Proteica , Alinhamento de SequênciaRESUMO
A general strategy is described for designing proteins that self assemble into large symmetrical nanomaterials, including molecular cages, filaments, layers, and porous materials. In this strategy, one molecule of protein A, which naturally forms a self-assembling oligomer, A(n), is fused rigidly to one molecule of protein B, which forms another self-assembling oligomer, B(m). The result is a fusion protein, A-B, which self assembles with other identical copies of itself into a designed nanohedral particle or material, (A-B)(p). The strategy is demonstrated through the design, production, and characterization of two fusion proteins: a 49-kDa protein designed to assemble into a cage approximately 15 nm across, and a 44-kDa protein designed to assemble into long filaments approximately 4 nm wide. The strategy opens a way to create a wide variety of potentially useful protein-based materials, some of which share similar features with natural biological assemblies.
Assuntos
Proteínas/química , Sequência de Aminoácidos , Biopolímeros , CristalizaçãoRESUMO
An empirical function is developed to measure the protein-like character of electron-density maps. The function is based upon a systematic analysis of numerous local and global map properties or descriptors. Local descriptors measure the occurrence throughout the unit cell of unique patterns on various defined templates, while global descriptors enumerate topological characteristics that define the connectivity and complexity of electron-density isosurfaces. We examine how these quantitative descriptors vary as error is introduced into the phase sets used to generate maps. Informative descriptors are combined in an optimal fashion to arrive at a predictive function. When the topological and geometrical analysis is applied to protein maps generated from phase sets with varying amounts of error, the function is able to estimate changes in average phase error with an accuracy of better than 10 degrees. Additionally, when used to monitor maps generated with experimental phases from different heavy-atom models, the analysis clearly distinguishes between the correct heavy-atom substructure solution and incorrect heavy-atom solutions. The function is also evaluated as a tool to monitor changes in map quality and phase error before and after density-modification procedures.
Assuntos
Elétrons , Estudos de Avaliação como AssuntoRESUMO
BACKGROUND: The ycaC gene comprises a 621 base pair open reading frame in Escherichia coli. The ycaC gene product (ycaCgp) is uncharacterized and has no assigned function. The closest sequence homologs with an assigned function belong to a family of bacterial hydrolases that catalyze isochorismatase-like reactions, but these have only low sequence similarity to ycaCgp (approximately 20% amino acid identity). The ycaCgp was obtained and identified during crystallization trials of an unrelated E. coli protein with which it co-purified. RESULTS: The 1.8 A crystal structure of ycaCgp reveals an octameric complex comprised of two tetrameric rings. A large three-layer (alphabetaalpha) sandwich domain and a small helical domain form the folded structure of the monomeric unit. Comparisons with sequence and structure databases suggest that ycaCgp belongs to a diverse family of bacterial hydrolases. The most closely related three-dimensional structure is that of the D2 tetrameric N-carbamoylsarcosine amidohydrolase (CSHase) from an Arthrobacter species. A conspicuous cleft between two ycaCgp subunits contains several conserved residues including Cys118, which we propose to be catalytic. In the active site, a nonprolyl cis peptide bond precedes Val114 and coincides with a cis peptide bond in CSHase in a region of dissimilar sequence. The crystal structure reveals a probable error or mutation relative to the reported genomic sequence. CONCLUSIONS: Although the specific function of ycaCgp is not yet known, structural studies solidify the relationship of this protein to other hydrolases and illuminate its active site and key elements of the catalytic mechanism.
Assuntos
Proteínas de Bactérias/química , Proteínas de Escherichia coli , Escherichia coli/enzimologia , Hidrolases/química , Conformação Proteica , Amidoidrolases/química , Sequência de Aminoácidos , Arthrobacter/enzimologia , Proteínas de Bactérias/metabolismo , Cristalografia por Raios X , Hidrolases/metabolismo , Substâncias Macromoleculares , Dados de Sequência Molecular , Estrutura Secundária de Proteína , Alinhamento de Sequência , Homologia de Sequência de Aminoácidos , Especificidade por SubstratoRESUMO
A novel method for differentiating between correctly and incorrectly determined regions of protein structures based on characteristic atomic interaction is described. Different types of atoms are distributed nonrandomly with respect to each other in proteins. Errors in model building lead to more randomized distributions of the different atom types, which can be distinguished from correct distributions by statistical methods. Atoms are classified in one of three categories: carbon (C), nitrogen (N), and oxygen (O). This leads to six different combinations of pairwise noncovalently bonded interactions (CC, CN, CO, NN, NO, and OO). A quadratic error function is used to characterize the set of pairwise interactions from nine-residue sliding windows in a database of 96 reliable protein structures. Regions of candidate protein structures that are mistraced or misregistered can then be identified by analysis of the pattern of nonbonded interactions from each window.