Structural validation and assessment of AlphaFold2 predictions for centrosomal and centriolar proteins and their complexes

Obtaining the high-resolution structures of proteins and their complexes is a crucial aspect of understanding the mechanisms of life. Experimental structure determination methods are time-consuming, expensive and cannot keep pace with the growing number of protein sequences available through genomic DNA sequencing. Thus, the ability to accurately predict the structure of proteins from their sequence is a holy grail of structural and computational biology that would remove a bottleneck in our efforts to understand as well as rationally engineer living systems. Recent advances in protein structure prediction, in particular the breakthrough with the AI-based tool AlphaFold2 (AF2), hold promise for achieving this goal, but the practical utility of AF2 remains to be explored. Focusing on proteins with essential roles in centrosome and centriole biogenesis, we demonstrate the quality and usability of the AF2 prediction models and we show that they can provide important insights into the modular organization of two key players in this process, CEP192 and CEP44. Furthermore, we used the AF2 algorithm to elucidate and then experimentally validate previously unknown prime features in the structure of TTBK2 bound to CEP164, as well as the Chibby1-FAM92A complex for which no structural information was available to date. These findings have important implications in understanding the regulation and function of these complexes. Finally, we also discuss some practical limitations of AF2 and anticipate the implications for future research approaches in the centriole/centrosome field.

Molecular modeling and molecular dynamic simulation of the effects of variants in the TGFBR2 kinase domain as a paradigm for interpretation of variants obtained by next generation sequencing

Variants in the TGFBR2 kinase domain cause several human diseases and can increase propensity for cancer. The widespread application of next generation sequencing within the setting of Individualized Medicine (IM) is increasing the rate at which TGFBR2 kinase domain variants are being identified. However, their clinical relevance is often uncertain. Consequently, we sought to evaluate the use of molecular modeling and molecular dynamics (MD) simulations for assessing the potential impact of variants within this domain. We documented the structural differences revealed by these models across 57 variants using independent MD simulations for each. Our simulations revealed various mechanisms by which variants may lead to functional alteration; some are revealed energetically, while others structurally or dynamically. We found that the ATP binding site and activation loop dynamics may be affected by variants at positions throughout the structure. This prediction cannot be made from the linear sequence alone. We present our structure-based analyses alongside those obtained using several commonly used genomics-based predictive algorithms. We believe the further mechanistic information revealed by molecular modeling will be useful in guiding the examination of clinically observed variants throughout the exome, as well as those likely to be discovered in the near future by clinical tests leveraging next-generation sequencing through IM efforts.

Automated harvesting and processing of protein crystals through laser photoablation

Currently, macromolecular crystallography projects often require the use of highly automated facilities for crystallization and X-ray data collection. However, crystal harvesting and processing largely depend on manual operations. Here, a series of new methods are presented based on the use of a low X-ray-background film as a crystallization support and a photoablation laser that enable the automation of major operations required for the preparation of crystals for X-ray diffraction experiments. In this approach, the controlled removal of the mother liquor before crystal mounting simplifies the cryocooling process, in many cases eliminating the use of cryoprotectant agents, while crystal-soaking experiments are performed through diffusion, precluding the need for repeated sample-recovery and transfer operations. Moreover, the high-precision laser enables new mounting strategies that are not accessible through other methods. This approach bridges an important gap in automation and can contribute to expanding the capabilities of modern macromolecular crystallography facilities.

The role of protein structural analysis in the next generation sequencing era

Proteins are macromolecules that serve a cell’s myriad processes and functions in all living organisms via dynamic interactions with other proteins, small molecules and cellular components. Genetic variations in the protein-encoding regions of the human genome account for >85% of all known Mendelian diseases, and play an influential role in shaping complex polygenic diseases. Proteins also serve as the predominant target class for the design of small molecule drugs to modulate their activity. Knowledge of the shape and form of proteins, by means of their three-dimensional structures, is therefore instrumental to understanding their roles in disease and their potentials for drug development. In this chapter we outline, with the wide readership of non-structural biologists in mind, the various experimental and computational methods available for protein structure determination. We summarize how the wealth of structure information, contributed to a large extent by the technological advances in structure determination to date, serves as a useful tool to decipher the molecular basis of genetic variations for disease characterization and diagnosis, particularly in the emerging era of genomic medicine, and becomes an integral component in the modern day approach towards rational drug development.

CrystalDirect™: a novel approach for automated crystal harvesting based on photoablation of thin films

The last years have seen a major development in automation for protein production, crystallization, and X-ray diffraction data collection, which has contributed to accelerate the pace of structure solution and to facilitate the study of ever more challenging targets through macromolecular crystallography. This has led to a considerable increase in the numbers of crystals produced and analyzed. However the process of recovering crystals from crystallization supports and mounting them in X-ray data collection pins remains a manual and delicate operation. Here we present a novel approach enabling full automation of the crystal mounting process and describe the operation of the first-automated CrystalDirect harvesting unit. Implications for crystallography applications and for the future operational integration of automated crystallization and data collection resources are discussed.

Structural genomics of human proteins

Structural genomics efforts focused on the human proteome have had three aims: to understand the structural and functional variations within protein families; to understand the structural basis of disease and genetic variation; and to determine the structures of human integral membrane proteins. The overarching theme is to advance the understanding of human health and to provide a structural platform to aid in the development of therapeutics. A decade or more of work in this field has identified optimal experimental strategies that can be used to expedite expression and crystallization of human proteins-and we provide some guidance to this end.

A microfluidic, high throughput protein crystal growth method for microgravity

The attenuation of sedimentation and convection in microgravity can sometimes decrease irregularities formed during macromolecular crystal growth. Current terrestrial protein crystal growth (PCG) capabilities are very different than those used during the Shuttle era and that are currently on the International Space Station (ISS). The focus of this experiment was to demonstrate the use of a commercial off-the-shelf, high throughput, PCG method in microgravity. Using Protein BioSolutions' microfluidic Plug Maker™/CrystalCard™ system, we tested the ability to grow crystals of the regulator of glucose metabolism and adipogenesis: peroxisome proliferator-activated receptor gamma (apo-hPPAR-γ LBD), as well as several PCG standards. Overall, we sent 25 CrystalCards™ to the ISS, containing ~10,000 individual microgravity PCG experiments in a 3U NanoRacks NanoLab (1U = 10(3) cm.). After 70 days on the ISS, our samples were returned with 16 of 25 (64%) microgravity cards having crystals, compared to 12 of 25 (48%) of the ground controls. Encouragingly, there were more apo-hPPAR-γ LBD crystals in the microgravity PCG cards than the 1g controls. These positive results hope to introduce the use of the PCG standard of low sample volume and large experimental density to the microgravity environment and provide new opportunities for macromolecular samples that may crystallize poorly in standard laboratories.

Cross-link guided molecular modeling with ROSETTA

Chemical cross-links identified by mass spectrometry generate distance restraints that reveal low-resolution structural information on proteins and protein complexes. The technology to reliably generate such data has become mature and robust enough to shift the focus to the question of how these distance restraints can be best integrated into molecular modeling calculations. Here, we introduce three workflows for incorporating distance restraints generated by chemical cross-linking and mass spectrometry into ROSETTA protocols for comparative and de novo modeling and protein-protein docking. We demonstrate that the cross-link validation and visualization software Xwalk facilitates successful cross-link data integration. Besides the protocols we introduce XLdb, a database of chemical cross-links from 14 different publications with 506 intra-protein and 62 inter-protein cross-links, where each cross-link can be mapped on an experimental structure from the Protein Data Bank. Finally, we demonstrate on a protein-protein docking reference data set the impact of virtual cross-links on protein docking calculations and show that an inter-protein cross-link can reduce on average the RMSD of a docking prediction by 5.0 Å. The methods and results presented here provide guidelines for the effective integration of chemical cross-link data in molecular modeling calculations and should advance the structural analysis of particularly large and transient protein complexes via hybrid structural biology methods.

Kinome Render: a stand-alone and web-accessible tool to annotate the human protein kinome tree

Human protein kinases play fundamental roles mediating the majority of signal transduction pathways in eukaryotic cells as well as a multitude of other processes involved in metabolism, cell-cycle regulation, cellular shape, motility, differentiation and apoptosis. The human protein kinome contains 518 members. Most studies that focus on the human kinome require, at some point, the visualization of large amounts of data. The visualization of such data within the framework of a phylogenetic tree may help identify key relationships between different protein kinases in view of their evolutionary distance and the information used to annotate the kinome tree. For example, studies that focus on the promiscuity of kinase inhibitors can benefit from the annotations to depict binding affinities across kinase groups. Images involving the mapping of information into the kinome tree are common. However, producing such figures manually can be a long arduous process prone to errors. To circumvent this issue, we have developed a web-based tool called Kinome Render (KR) that produces customized annotations on the human kinome tree. KR allows the creation and automatic overlay of customizable text or shape-based annotations of different sizes and colors on the human kinome tree. The web interface can be accessed at: http://bcb.med.usherbrooke.ca/kinomerender. A stand-alone version is also available and can be run locally.

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases.

The role of targeted chemical proteomics in pharmacology

Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the 'hidden' proteome) from complex mixtures of wide dynamic range (the 'deep' proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets.

Identification of binding specificity-determining features in protein families

We present a new approach for identifying features of ligand-protein binding interfaces that predict binding selectivity and demonstrate its effectiveness for predicting kinase inhibitor specificity. We analyzed a large set of human kinases and kinase inhibitors using clustering of experimentally determined inhibition constants (to define specificity classes of kinases and inhibitors) and virtual ligand docking (to extract structural and chemical features of the ligand-protein binding interfaces). We then used statistical methods to identify features characteristic of each class. Machine learning was employed to determine which combinations of characteristic features were predictive of class membership and to predict binding specificities and affinities of new compounds. Experiments showed predictions were 70% accurate. These results show that our method can automatically pinpoint on the three-dimensional binding interfaces pharmacophore-like features that act as "selectivity filters". The method is not restricted to kinases, requires no prior hypotheses about specific interactions, and can be applied to any protein families for which sets of structures and ligand binding data are available.

Formulating a fluorogenic assay to evaluate S-adenosyl-L-methionine analogues as protein methyltransferase cofactors

Protein methyltransferases (PMTs) catalyze arginine and lysine methylation of diverse histone and nonhistone targets. These posttranslational modifications play essential roles in regulating multiple cellular events in an epigenetic manner. In the recent process of defining PMT targets, S-adenosyl-L-methionine (SAM) analogues have emerged as powerful small molecule probes to label and profile PMT targets. To examine efficiently the reactivity of PMTs and their variants on SAM analogues, we transformed a fluorogenic PMT assay into a ready high throughput screening (HTS) format. The reformulated fluorogenic assay is featured by its uncoupled but more robust character with the first step of accumulation of the commonly-shared reaction byproduct S-adenosyl-L-homocysteine (SAH), followed by SAH-hydrolase-mediated fluorogenic quantification. The HTS readiness and robustness of the assay were demonstrated by its excellent Z' values of 0.83-0.95 for the so-far-examined 8 human PMTs with SAM as a cofactor (PRMT1, PRMT3, CARM1, SUV39H2, SET7/9, SET8, G9a and GLP1). The fluorogenic assay was further implemented to screen the PMTs against five SAM analogues (allyl-SAM, propargyl-SAM, (E)-pent-2-en-4-ynyl-SAM (EnYn-SAM), (E)-hex-2-en-5-ynyl-SAM (Hey-SAM) and 4-propargyloxy-but-2-enyl-SAM (Pob-SAM)). Among the examined 8 × 5 pairs of PMTs and SAM analogues, native SUV39H2, G9a and GLP1 showed promiscuous activity on allyl-SAM. In contrast, the bulky SAM analogues, such as EnYn-SAM, Hey-SAM and Pob-SAM, are inert toward the panel of human PMTs. These findings therefore provide the useful structure-activity guidance to further evolve PMTs and SAM analogues for substrate labeling. The current assay format is ready to screen methyltransferase variants on structurally-diverse SAM analogues.

Integrating energy calculations with functional assays to decipher the specificity of G protein-RGS protein interactions

The diverse Regulator of G protein Signaling (RGS) family sets the timing of G protein signaling. To understand how the structure of RGS proteins determines their common ability to inactivate G proteins and their selective G protein recognition, we combined structure-based energy calculations with biochemical measurements of RGS activity. We found a previously unidentified group of variable 'Modulatory' residues that reside at the periphery of the RGS domain-G protein interface and fine-tune G protein recognition. Mutations of Modulatory residues in high-activity RGS proteins impaired RGS function, whereas redesign of low-activity RGS proteins in critical Modulatory positions yielded complete gain of function. Therefore, RGS proteins combine a conserved core interface with peripheral Modulatory residues to selectively optimize G protein recognition and inactivation. Finally, we show that our approach can be extended to analyze interaction specificity across other large protein families.

High-throughput structural biology of metabolic enzymes and its impact on human diseases

The Structural Genomics Consortium (SGC) is a public-private partnership that aims to determine the three-dimensional structures of human proteins of medical relevance and place them into the public domain without restriction. To date, the Oxford Metabolic Enzyme Group at SGC has deposited the structures of more than 140 human metabolic enzymes from diverse protein families such as oxidoreductases, hydrolases, oxygenases and fatty acid transferases. A subset of our target proteins are involved in the inherited disorders of carbohydrate, fatty acid, amino acid and vitamin metabolism. This article will provide an overview of the structural data gathered from our high-throughput efforts and the lessons learnt in the structure-function relationship of these enzymes, small molecule development and the molecular basis of disease mutations.

The Therapeutic Target Database: an internet resource for the primary targets of approved, clinical trial and experimental drugs

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets. A challenge in drug discovery is to decide which targets to pursue from an increasing pool of potential targets, given the fact that few innovative targets have made it to the approval list each year. Knowledge of existing drug targets (both approved and within clinical trials) is highly useful for facilitating target discovery, selection, exploration and tool development. The Therapeutic Target Database (TTD) has been developed and updated to provide information on 358 successful targets, 251 clinical trial targets and 1254 research targets in addition to 1511 approved drugs, 1118 clinical trials drugs and 2331 experimental drugs linked to their primary targets (3257 drugs with available structure data). This review briefly describes the TTD database and illustrates how its data can be explored for facilitating target and drug searches, the study of the mechanism of multi-target drugs and the development of in silico target discovery tools.

Overview: the maturing of proteomics in cardiovascular research

Proteomic technologies are used to study the complexity of proteins, their roles, and biological functions. It is based on the premise that the diversity of proteins, comprising their isoforms, and posttranslational modifications (PTMs) underlies biology. Based on an annotated human cardiac protein database, 62% have at least one PTM (phosphorylation currently dominating), whereas ≈25% have more than one type of modification. The field of proteomics strives to observe and quantify this protein diversity. It represents a broad group of technologies and methods arising from analytic protein biochemistry, analytic separation, mass spectrometry, and bioinformatics. Since the 1990s, the application of proteomic analysis has been increasingly used in cardiovascular research. Technology development and adaptation have been at the heart of this progress. Technology undergoes a maturation, becoming routine and ultimately obsolete, being replaced by newer methods. Because of extensive methodological improvements, many proteomic studies today observe 1000 to 5000 proteins. Only 5 years ago, this was not feasible. Even so, there are still road blocks. Nowadays, there is a focus on obtaining better characterization of protein isoforms and specific PTMs. Consequently, new techniques for identification and quantification of modified amino acid residues are required, as is the assessment of single-nucleotide polymorphisms in addition to determination of the structural and functional consequences. In this series, 4 articles provide concrete examples of how proteomics can be incorporated into cardiovascular research and address specific biological questions. They also illustrate how novel discoveries can be made and how proteomic technology has continued to evolve.

The design of macromolecular crystallography diffraction experiments

The measurement of X-ray diffraction data from macromolecular crystals for the purpose of structure determination is the convergence of two processes: the preparation of diffraction-quality crystal samples on the one hand and the construction and optimization of an X-ray beamline and end station on the other. Like sample preparation, a macromolecular crystallography beamline is geared to obtaining the best possible diffraction measurements from crystals provided by the synchrotron user. This paper describes the thoughts behind an experiment that fully exploits both the sample and the beamline and how these map into everyday decisions that users can and should make when visiting a beamline with their most precious crystals.

Biophysical characterization of recombinant proteins: a key to higher structural genomics success

Hundreds of genomes have been successfully sequenced to date, and the data are publicly available. At the same time, the advances in large-scale expression and purification of recombinant proteins have paved the way for structural genomics efforts. Frequently, however, little is known about newly expressed proteins calling for large-scale protein characterization to better understand their biochemical roles and to enable structure-function relationship studies. In the Structural Genomics Consortium (SGC), we have established a platform to characterize large numbers of purified proteins. This includes screening for ligands, enzyme assays, peptide arrays and peptide displacement in a 384-well format. In this review, we describe this platform in more detail and report on how our approach significantly increases the success rate for structure determination. Coupled with high-resolution X-ray crystallography and structure-guided methods, this platform can also be used toward the development of chemical probes through screening families of proteins against a variety of chemical series and focused chemical libraries.

Unmet challenges of structural genomics

Structural genomics (SG) programs have developed during the last decade many novel methodologies for faster and more accurate structure determination. These new tools and approaches led to the determination of thousands of protein structures. The generation of enormous amounts of experimental data resulted in significant improvements in the understanding of many biological processes at molecular levels. However, the amount of data collected so far is so large that traditional analysis methods are limiting the rate of extraction of biological and biochemical information from 3D models. This situation has prompted us to review the challenges that remain unmet by SG, as well as the areas in which the potential impact of SG could exceed what has been achieved so far.

High-throughput production of human proteins for crystallization: the SGC experience

Producing purified human proteins with high yield and purity remains a considerable challenge. We describe the methods utilized in the Structural Genomics Consortium (SGC) in Oxford, resulting in successful purification of 48% of human proteins attempted; of those, the structures of approximately 40% were solved by X-ray crystallography. The main driver has been the parallel processing of multiple (typically 9-20) truncated constructs of each target; modest diversity in vectors and host systems; and standardized purification procedures. We provide method details as well as data on the properties of the constructs leading to crystallized proteins and the impact of methodological variants. These can be used to formulate guidelines for initial approaches to expression of new eukaryotic proteins.

Generating recombinant antibodies to the complete human proteome

In vitro antibody generation technologies have now been available for two decades. Research reagents prepared via phage display are becoming available and several recent studies have demonstrated that these technologies are now sufficiently advanced to facilitate generation of a comprehensive renewable resource of antibodies for any protein encoded by the approximately 22,500 human protein-coding genes. Antibody selection in vitro offers properties not available in animal-based antibody generation methods. By adjusting the biochemical milieu during selection, it is possible to control the antigen conformation recognized, the antibody affinity or unwanted cross-reactivity. For larger-scale antibody generation projects, the handling, transport and storage logistics and bacterial production offer cost benefits. Because the DNA sequence encoding the antibody is available, modifications, such as site-specific in vivo biotinylation and multimerization, are only a cloning step away. This opinion article summarizes opportunities for the generation of antibodies for proteome research using in vitro technologies.

Understanding specificity in metabolic pathways--structural biology of human nucleotide metabolism

Interactions are the foundation of life at the molecular level. In the plethora of activities in the cell, the evolution of enzyme specificity requires the balancing of appropriate substrate affinity with a negative selection, in order to minimize interactions with other potential substrates in the cell. To understand the structural basis for enzyme specificity, the comparison of structural and biochemical data between enzymes within pathways using similar substrates and effectors is valuable. Nucleotide metabolism is one of the largest metabolic pathways in the human cell and is of outstanding therapeutic importance since it activates and catabolises nucleoside based anti-proliferative drugs and serves as a direct target for anti-proliferative drugs. In recent years the structural coverage of the enzymes involved in human nucleotide metabolism has been dramatically improved and is approaching completion. An important factor has been the contribution from the Structural Genomics Consortium (SGC) at Karolinska Institutet, which recently has solved 33 novel structures of enzymes and enzyme domains in human nucleotide metabolism pathways and homologs thereof. In this review we will discuss some of the principles for substrate specificity of enzymes in human nucleotide metabolism illustrated by a selected set of enzyme families where a detailed understanding of the structural determinants for specificity is now emerging.

Structural genomics-impact on biomedicine and drug discovery

The field of structural genomics emerged as one of many 'omics disciplines more than a decade ago, and a multitude of large scale initiatives have been launched across the world. Development and implementation of methods for high-throughput structural biology represents a common denominator among different structural genomics programs. From another perspective a distinction between "biology-driven" versus "structure-driven" approaches can be made. This review outlines the general themes of structural genomics, its achievements and its impact on biomedicine and drug discovery. The growing number of high resolution structures of known and potential drug target proteins is expected to have tremendous value for future drug discovery programs. Moreover, the availability of large numbers of purified proteins enables generation of tool reagents, such as chemical probes and antibodies, to further explore protein function in the cell.

Open access chemical and clinical probes to support drug discovery

Drug discovery resources in academia and industry are not used efficiently, to the detriment of industry and society. Duplication could be reduced, and productivity could be increased, by performing basic biology and clinical proofs of concept within open access industry-academia partnerships. Chemical biologists could play a central role in this effort.

Update of TTD: Therapeutic Target Database

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved and clinical trial drugs. Knowledge of these targets and corresponding drugs, particularly those in clinical uses and trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has been developed to provide information about therapeutic targets and corresponding drugs. In order to accommodate increasing demand for comprehensive knowledge about the primary targets of the approved, clinical trial and experimental drugs, numerous improvements and updates have been made to TTD. These updates include information about 348 successful, 292 clinical trial and 1254 research targets, 1514 approved, 1212 clinical trial and 2302 experimental drugs linked to their primary targets (3382 small molecule and 649 antisense drugs with available structure and sequence), new ways to access data by drug mode of action, recursive search of related targets or drugs, similarity target and drug searching, customized and whole data download, standardized target ID, and significant increase of data (1894 targets, 560 diseases and 5028 drugs compared with the 433 targets, 125 diseases and 809 drugs in the original release described in previous paper). This database can be accessed at http://bidd.nus.edu.sg/group/cjttd/TTD.asp.

Towards proteome scale antibody selections using phage display

In vitro antibody generation by panning a large universal gene library with phage display was employed to generate antibodies to more than 60 different antigens. Of particular interest was a comparison of pannings on 20 different SH2 domains provided by the Structural Genomics Consortium (SGC). Streamlined methods for high throughput antibody generation developed within the 'Antibody Factory' of the German National Genome Research Network (NGFN) were demonstrated to minimise effort and provide a reliable and robust source for antibodies. For the SH2 domains, in two successive series of selections, 2668 clones were analysed, resulting in 347 primary hits in ELISA. Half of these hits were further analysed, and more than 90 different scFv antibodies to all antigens were identified. The validation of selected antibodies by cross-reactivity ELISA, western blot and on protein microarrays demonstrated the versatility of the in vitro antibody selection pipeline to generate a renewable resource of highly specific monoclonal binders in proteome scale numbers with substantially reduced effort and time.

Lessons from structural genomics

A decade of structural genomics, the large-scale determination of protein structures, has generated a wealth of data and many important lessons for structural biology and for future large-scale projects. These lessons include a confirmation that it is possible to construct large-scale facilities that can determine the structures of a hundred or more proteins per year, that these structures can be of high quality, and that these structures can have an important impact. Technology development has played a critical role in structural genomics, the difficulties at each step of determining a structure of a particular protein can be quantified, and validation of technologies is nearly as important as the technologies themselves. Finally, rapid deposition of data in public databases has increased the impact and usefulness of the data and international cooperation has advanced the field and improved data sharing.