Contribution of structural genomics to understanding the biology of Escherichia coli

Update on the pfam5000 strategy for selection of structural genomics targets

Structural Genomics is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy that is medically and biologically relevant, of good financial value, and tractable. In 2003, we presented the "Pfam5000" strategy, which involves selecting the 5,000 most important families from the Pfam database as sources for targets. In this update, we show that although both the Pfam database and the number of sequenced genomes have increased in size, the expected benefits of the Pfam5000 strategy have not changed substantially. Solving the structures of proteins from the 5,000 largest Pfam families would allow accurate fold assignment for approximately 65% of all prokaryotic proteins (covering 54% of residues) and 63% of eukaryotic proteins (42% of residues). Fewer than 2,300 of the largest families on this list remain to be solved, making the project feasible in the next five years given the expected throughput to be achieved in the production phase of the Protein Structure Initiative.

From protein sequences to 3D-structures and beyond: the example of the UniProt knowledgebase

With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website ( http://www.uniprot.org/ ). It also evokes precautions that are necessary for successful predictions and extrapolations.

Targeting the human cancer pathway protein interaction network by structural genomics

Structural genomics provides an important approach for characterizing and understanding systems biology. As a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology, we have constructed a Human Cancer Pathway Protein Interaction Network (HCPIN) by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. Many well known cancer-associated proteins play central roles as "hubs" or "bottlenecks" in the HCPIN. At least half of HCPIN proteins are either directly associated with or interact with multiple signaling pathways. Although some 45% of residues in these proteins are in sequence segments that meet criteria sufficient for approximate homology modeling (Basic Local Alignment Search Tool (BLAST) E-value <10(-6)), only approximately 20% of residues in these proteins are structurally covered using high accuracy homology modeling criteria (i.e. BLAST E-value <10(-6) and at least 80% sequence identity) or by actual experimental structures. The HCPIN Website provides a comprehensive description of this biomedically important multipathway network together with experimental and homology models of HCPIN proteins useful for cancer biology research. To complement and enrich cancer systems biology, the Northeast Structural Genomics Consortium is targeting >1000 human proteins and protein domains from the HCPIN for sample production and 3D structure determination. The long range goal of this effort is to provide a comprehensive 3D structure-function database for human cancer-associated proteins and protein complexes in the context of their interaction networks. The network-based target selection (BioNet) approach described here is an example of a general strategy for targeting co-functioning proteins by structural genomics projects.

Bacterial structural genomics initiative: overview of methods and technologies applied to the process of structure determination

The focus over the last several years on increasing the number of three-dimensional structures of macromolecules by implementation of high throughput methodology has led to the establishment of dedicated structural genomics programs around the world. These worldwide efforts have in turn led to development of novel, parallelized approaches to cloning, expression, purification, and crystallization of proteins. This chapter describes in some detail the approaches and protocols that have been implemented in the Bacterial Structural Genomics Initiative.

Cloning, production, and purification of proteins for a medium-scale structural genomics project

The South-Paris Yeast Structural Genomics Pilot Project (http://www.genomics.eu.org) aims at systematically expressing, purifying, and determining the three-dimensional structures of Saccharomyces cerevisiae proteins. We have already cloned 240 yeast open reading frames in the Escherichia coli pET system. Eighty-two percent of the targets can be expressed in E. coli, and 61% yield soluble protein. We have currently purified 58 proteins. Twelve X-ray structures have been solved, six are in progress, and six other proteins gave crystals. In this chapter, we present the general experimental flowchart applied for this project. One of the main difficulties encountered in this pilot project was the low solubility of a great number of target proteins. We have developed parallel strategies to recover these proteins from inclusion bodies, including refolding, coexpression with chaperones, and an in vitro expression system. A limited proteolysis protocol, developed to localize flexible regions in proteins that could hinder crystallization, is also described.

Implications of structural genomics target selection strategies: Pfam5000, whole genome, and random approaches

Structural genomics is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy that is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the "Pfam5000" strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These strategies include complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at the European Bioinformatics Institute (EBI). Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68% of all prokaryotic proteins (covering 59% of residues) and 61% of eukaryotic proteins (40% of residues). More fine-grained coverage that would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example, to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: A significant fraction (about 30-40% of the proteins and 40-60% of the residues) of each proteome is classified in small families, which may have little overlap with other species of interest. Random selection of targets from one or more genomes is similar to the Pfam5000 strategy in that proteins from larger families are more likely to be chosen, but substantial effort would be spent on small families.

Target selection and deselection at the Berkeley Structural Genomics Center

At the Berkeley Structural Genomics Center (BSGC), our goal is to obtain a near-complete structural complement of proteins in the minimal organisms Mycoplasma genitalium and M. pneumoniae, two closely related pathogens. Current targets for structure determination have been selected in six major stages, starting with those predicted to be most tractable to high throughput study and likely to yield new structural information. We report on the process used to select these proteins, as well as our target deselection procedure. Target deselection reduces experimental effort by eliminating targets similar to those recently solved by the structural biology community or other centers. We measure the impact of the 69 structures solved at the BSGC as of July 2004 on structure prediction coverage of the M. pneumoniae and M. genitalium proteomes. The number of Mycoplasma proteins for which the fold could first be reliably assigned based on structures solved at the BSGC (24 M. pneumoniae and 21 M. genitalium) is approximately 25% of the total resulting from work at all structural genomics centers and the worldwide structural biology community (94 M. pneumoniae and 86 M. genitalium) during the same period. As the number of structures contributed by the BSGC during that period is less than 1% of the total worldwide output, the benefits of a focused target selection strategy are apparent. If the structures of all current targets were solved, the percentage of M. pneumoniae proteins for which folds could be reliably assigned would increase from approximately 57% (391 of 687) at present to around 80% (550 of 687), and the percentage of the proteome that could be accurately modeled would increase from around 37% (254 of 687) to about 64% (438 of 687). In M. genitalium, the percentage of the proteome that could be structurally annotated based on structures of our remaining targets would rise from 72% (348 of 486) to around 76% (371 of 486), with the percentage of accurately modeled proteins would rise from 50% (243 of 486) to 58% (283 of 486). Sequences and data on experimental progress on our targets are available in the public databases TargetDB and PEPCdb.