Structure-based functional inference in structural genomics

The dramatically increasing number of new protein sequences arising from genomics 4 proteomics requires the need for methods to rapidly and reliably infer the molecular and cellular functions of these proteins. One such approach, structural genomics, aims to delineate the total repertoire of protein folds in nature, thereby providing three-dimensional folding patterns for all proteins and to infer molecular functions of the proteins based on the combined information of structures and sequences. The goal of obtaining protein structures on a genomic scale has motivated the development of high throughput technologies and protocols for macromolecular structure determination that have begun to produce structures at a greater rate than previously possible. These new structures have revealed many unexpected functional inferences and evolutionary relationships that were hidden at the sequence level. Here, we present samples of structures determined at Berkeley Structural Genomics Center and collaborators laboratories to illustrate how structural information provides and complements sequence information to deduce the functional inferences of proteins with unknown molecular functions.Two of the major premises of structural genomics are to discover a complete repertoire of protein folds in nature and to find molecular functions of the proteins whose functions are not predicted from sequence comparison alone. To achieve these objectives on a genomic scale, new methods, protocols, and technologies need to be developed by multi-institutional collaborations worldwide. As part of this effort, the Protein Structure Initiative has been launched in the United States (PSI; www.nigms.nih.gov/funding/psi.html). Although infrastructure building and technology development are still the main focus of structural genomics programs [1–6], a considerable number of protein structures have already been produced, some of them coming directly out of semi-automated structure determination pipelines [6–10]. The Berkeley Structural Genomics Center (BSGC) has focused on the proteins of Mycoplasma or their homologues from other organisms as its structural genomics targets because of the minimal genome size of the Mycoplasmas as well as their relevance to human and animal pathogenicity (http://www.strgen.org). Here we present several protein examples encompassing a spectrum of functional inferences obtainable from their three-dimensional structures in five situations, where the inferences are new and testable, and are not predictable from protein sequence information alone.     

Solution NMR in structural genomics

Structural genomics (also known as structural proteomics) aims to generate accurate three-dimensional models for all folded, globular proteins and domains in the protein universe to understand the relationship between protein sequence, structure and function. NMR spectroscopy of small (<20 kDa) proteins has been used successfully within several large-scale structural genomics projects for more than six years now. Recent advances coming from traditional NMR structural biology laboratories as well as large scale centers and consortia using NMR for structural genomics promise to facilitate NMR analysis making it even a more efficient and increasingly automated procedure.     

Target selection of soluble protein complexes for structural proteomics studies

Background  

Protein expression in E. coli is the most commonly used system to produce protein for structural studies, because it is fast and inexpensive and can produce large quantity of proteins. However, when proteins from other species such as mammalian are produced in this system, problems of protein expression and solubility arise [1]. Structural genomics project are currently investigating proteomics pipelines that would produce sufficient quantities of recombinant proteins for structural studies of protein complexes. To investigate how the E. coli protein expression system could be used for this purpose, we purified apoptotic binary protein complexes formed between members of the Caspase Associated Recruitment Domain (CARD) family.     

Characterization of Chlorophyll–protein Complexes Isolated from Two Marine Green Algae, Bryopsis maxima and Ulva pertusa, Growing in the Intertidal Zone

Three Chl–protein complexes were isolated from thylakoid membranes of Bryopsis maxima and Ulva pertusa, marine green algae that inhabit the intertidal zone of the Pacific Ocean off the eastern coast of Japan by dodecyl-β-d-maltoside polyacrylamide gel electrophoresis. The slowest-moving fractions showed low Chl a/b and Chl/P-700 ratios, indicating that this fraction corresponds to complexes in PS I, which is large in both algae. The intermediate and fastest-moving fractions showed the traits of PS II complexes, with some associated Chl a/b–protein complexes and LHC II, respectively. The spectral properties of the separated Chl–proteins were also determined. The absorption spectra showed a shallow shoulder at 540 nm derived from siphonaxanthin in Bryopsis maxima, but not in Ulva pertusa. The 77 K emission spectra showed a single peak in Bryopsis maxima and two peaks in Ulva pertusa. Besides the excitation spectra indicated that the excitation energy transfer to the PS I complexes differed quite a lot higher plants. This suggested that the mechanisms of energy transfer in both of these algae differ from those of higher plants. Considering the light environment of this coastal area, the large size of the antennae of PS I complexes implies that the antennae are arranged so as to balance light absorption between the two photosystems. In addition, we discuss the relationships among the photosystem stoichiometry, the energy transfer, and the distribution between the two photosystems.     

Structural genomics is the largest contributor of novel structural leverage

The Protein Structural Initiative (PSI) at the US National Institutes of Health (NIH) is funding four large-scale centers for structural genomics (SG). These centers systematically target many large families without structural coverage, as well as very large families with inadequate structural coverage. Here, we report a few simple metrics that demonstrate how successfully these efforts optimize structural coverage: while the PSI-2 (2005-now) contributed more than 8% of all structures deposited into the PDB, it contributed over 20% of all novel structures (i.e. structures for protein sequences with no structural representative in the PDB on the date of deposition). The structural coverage of the protein universe represented by today’s UniProt (v12.8) has increased linearly from 1992 to 2008; structural genomics has contributed significantly to the maintenance of this growth rate. Success in increasing novel leverage (defined in Liu et al. in Nat Biotechnol 25:849–851, 2007) has resulted from systematic targeting of large families. PSI’s per structure contribution to novel leverage was over 4-fold higher than that for non-PSI structural biology efforts during the past 8 years. If the success of the PSI continues, it may just take another ~15 years to cover most sequences in the current UniProt database.     

Automated, high-throughput platform for protein solubility screening using a split-GFP system

Overproduction of soluble and stable proteins for functional and structural studies is a major bottleneck for structural genomics programs and traditional biochemistry laboratories. Many high-payoff proteins that are important in various biological processes are “difficult to handle” as protein reagents in their native form. We have recently made several advances in enabling biochemical technologies for improving protein stability (), allowing stratagems for efficient protein domain trapping, solubility-improving mutations, and finding protein folding partners. In particular split-GFP protein tags are a very powerful tool for detection of stable protein domains. Soluble, stable proteins tagged with the 15 amino acid GFP fragment (amino acids 216–228) can be detected in vivo and in vitro using the engineered GFP 1–10 “detector” fragment (amino acids 1–215). If the small tag is accessible, the detector fragment spontaneously binds resulting in fluorescence. Here, we describe our current and on-going efforts to move this process from the bench (manual sample manipulation) to an automated, high-throughput, liquid-handling platform. We discuss optimization and validation of bacterial culture growth, lysis protocols, protein extraction, and assays of soluble and insoluble protein in multiple 96 well plate format. The optimized liquid-handling protocol can be used for rapid determination of the optimal, compact domains from single ORFS, collections of ORFS, or cDNA libraries.     

Recognizing protein–protein interfaces with empirical potentials and reduced amino acid alphabets

Background  

In structural genomics, an important goal is the detection and classification of protein–protein interactions, given the structures of the interacting partners. We have developed empirical energy functions to identify native structures of protein–protein complexes among sets of decoy structures. To understand the role of amino acid diversity, we parameterized a series of functions, using a hierarchy of amino acid alphabets of increasing complexity, with 2, 3, 4, 6, and 20 amino acid groups. Compared to previous work, we used the simplest possible functional form, with residue–residue interactions and a stepwise distance-dependence. We used increased computational ressources, however, constructing 290,000 decoys for 219 protein–protein complexes, with a realistic docking protocol where the protein partners are flexible and interact through a molecular mechanics energy function. The energy parameters were optimized to correctly assign as many native complexes as possible. To resolve the multiple minimum problem in parameter space, over 64000 starting parameter guesses were tried for each energy function. The optimized functions were tested by cross validation on subsets of our native and decoy structures, by blind tests on series of native and decoy structures available on the Web, and on models for 13 complexes submitted to the CAPRI structure prediction experiment.     

Structural genomics

Structural genomics can be defined as structural biology on a large number of target proteins in parallel. This approach plays an important role in modern structure-based drug design. Although a number of structural genomics initiatives have been initiated, relatively few are associated with integral membrane proteins. This indicates the difficulties in expression, purification, and crystallization of membrane proteins, which has also been confirmed by the existence of some 100 high-resolution structures of membrane proteins among the more than 30,000 entries in public databases. Paradoxically, membrane proteins represent 60–70% of current drug targets and structural knowledge could both improve and speed up the drug discovery process. In order to improve the sucess rate for structure resolution of membrane proteins structural genomics networks have been established.     

The success of structural genomics

The International Conference on Structural Genomics (ICSG 2011, ), held in Toronto Canada May 10–14, 2011 was a rich and exciting demonstration of how far structural genomics has come. Structural genomics has now matured into a field that includes both structure and the biology that structure enables. This has allowed targeting based on systematic approaches and on known biological importance and allows biochemical studies to be closely tied to structure determination. The wealth of purified proteins, clones, and chemical probes produced by structural genomics groups will enable a vast amount of follow-on research. The technologies, the structures, and the biology that were described at the meeting were at the cutting edge of science. Structural genomics has become a success.     

结构基因组学研究与核磁共振

各种生物的基因组DNA测序计划的完成,将结构生物学带入了结构基因组学时代.结构基因组学是对所有基因组产物结构的系统性测定,它运用高通量的选择、表达、纯化以及结构测定和计算分析手段,为基因组的每个蛋白质产物提供实验测定的结构或较好的理论模型,这将加速生命科学各个领域的研究.生物信息学、基因工程、结构测定技术等的发展为结构基因组学研究提供了保证.近年来核磁共振在技术方法上的进展,使其成为结构基因组学高通量结构分析中的一个关键方法.     

Strategies to maximize heterologous protein expression in Escherichia coli with minimal cost

Automation and miniaturization are key issues of high-throughput research projects in the post-genomic era. The implementation of robotics and parallelization has enabled researchers to process large numbers of protein targets for structural studies in a short time with reasonable cost efficiency. However, the cost of implementing the robotics and parallelization often prohibit their use in the traditional academic laboratory. Fortunately, multiple groups have made significant efforts to minimize the cost of heterologous protein expression for the production of protein samples in quantities suitable for high resolution structural studies. In this review, we describe recent efforts to continue to minimize the cost for the parallel processing of multiple protein targets and focus on those materials and strategies that are highly suitable for the traditional academic laboratory.     

Structural genomics and drug discovery: all in the family

Structural genomics is starting to have an impact on the early stages of drug discovery and target validation through the contribution of new structures of known and potential drug targets, their complexes with ligands and protocols and reagents for additional structural work within a drug discovery program. Recent progress includes structures of targets from bacterial, viral and protozoan human pathogens, and human targets from known or potential druggable protein families such as, kinases, phosphatases, dehydrogenases/oxidoreductases, sulfo-, acetyl- and methyl-transferases, and a number of other key metabolic enzymes. Importantly, many of these structures contained ligands in the active sites, including for example, the first structures of target-bound therapeutics. Structural genomics of protein families combined with ligand discovery holds particular promise for advancing early stage discovery programs.     

Characterizing weak protein–protein complexes by NMR residual dipolar couplings

Protein–protein interactions occur with a wide range of affinities from tight complexes characterized by femtomolar dissociation constants to weak, and more transient, complexes of millimolar affinity. Many of the weak and transiently formed protein–protein complexes have escaped characterization due to the difficulties in obtaining experimental parameters that report on the complexes alone without contributions from the unbound, free proteins. Here, we review recent developments for characterizing the structures of weak protein–protein complexes using nuclear magnetic resonance spectroscopy with special emphasis on the utility of residual dipolar couplings.     

Structural Genomics of Minimal Organisms and Protein Fold Space

The initial aim of the Berkeley Structural Genomics Center is to obtain a near-complete structural complement of two minimal organisms, closely related pathogens Mycoplasma genitalium and M. pneumoniae. The former has fewer than 500 genes and the latter fewer than 700 genes. To achieve this goal, the current protein targets have been selected starting with those predicted to be most tractable and likely to yield new structural and functional information. During the past 3 years, the semi-automated structural genomics pipeline has been set up from cloning, expression, purification, and ultimately to structural determination. The results from the pipeline substantially increased the coverage of the protein fold space of M. pneumoniae and M. genitalium. Furthermore, about 1/2 of the structures of ‘unique’ protein sequences revealed new and novel folds, and over 2/3 of the structures of previously annotated ‘hypothetical proteins’ inferred their molecular functions.     

From gene to protein: a review of new and enabling technologies for multi-parallel protein expression

In the post-genomic era, increasingly greater demands and expectations are being placed on protein production laboratories to produce more proteins and in faster timelines. This has been coupled with an exponential increase in the number of requests for the production of proteins which lack structural and functional information. No longer can groups use literature available in the public domain solely to drive their expression strategy, and moreover current expression and concomitant purification strategies clearly do not meet modern-day demands for protein production. This review will therefore attempt to provide a definitive review of current 'best in class' cloning, expression and purification systems, and the adaptations and developments that have been made by laboratories, both academic and industrial, to enhance protein production throughput.     

Optimization of resolution and sensitivity of 4D NOESY using Multi-dimensional Decomposition

Highly resolved multi-dimensional NOE data are essential for rapid and accurate determination of spatial protein structures such as in structural genomics projects. Four-dimensional spectra contain almost no spectral overlap inherently present in lower dimensionality spectra and are highly amenable to application of automated routines for spectral resonance location and assignment. However, a high resolution 4D data set using conventional uniform sampling usually requires unacceptably long measurement time. Recently we have reported that the use of non-uniform sampling and multi-dimensional decomposition (MDD) can remedy this problem. Here we validate accuracy and robustness of the method, and demonstrate its usefulness for fully protonated protein samples. The method was applied to 11 kDa protein PA1123 from structural genomics pipeline. A systematic evaluation of spectral reconstructions obtained using 15–100% subsets of the complete reference 4D ¹H–¹³C–¹³C–¹H NOESY spectrum has been performed. With the experimental time saving of up to six times, the resolution and the sensitivity per unit time is shown to be similar to that of the fully recorded spectrum. For the 30% data subset we demonstrate that the intensities in the reconstructed and reference 4D spectra correspond with a correlation coefficient of 0.997 in the full range of spectral amplitudes. Intensities of the strong, middle and weak cross-peaks correlate with coefficients 0.9997, 0.9965, and 0.83. The method does not produce false peaks. 2% of weak peaks lost in the 30% reconstruction is in line with theoretically expected noise increase for the shorter measurement time. Together with good accuracy in the relative line-widths these translate to reliable distance constrains derived from sparsely sampled, high resolution 4D NOESY data.     

Doing more than just the structure-structural genomics in kinase drug discovery

Structural genomics (SG) has significantly increased the number of novel protein structures of targets with medical relevance. In the protein kinase area, SG has contributed >50% of all novel kinases structures during the past three years and determined more than 30 novel catalytic domain structures. Many of the released structures are inhibitor complexes and a number of them have identified new inhibitor binding modes and scaffolds. In addition, generated reagents, assays, and inhibitor screening data provide a diversity of chemogenomic data that can be utilized for early drug development. Here we discuss the currently available structural data for the kinase family considering novel structures as well as inhibitor complexes. Our analysis revealed that the structural coverage of many kinases families is still rather poor, and inhibitor complexes with diverse inhibitors are only available for a few kinases. However, we anticipate that with the current rate of structure determination and high throughput technologies developed by SG programs these gaps will be closed soon. In addition, the generated reagents will put SG initiatives in a unique position providing data beyond protein structure determination by identifying chemical probes, determining their binding modes and target specificity.     

Automation of protein purification for structural genomics

A critical issue in structural genomics, and in structural biology in general, is the availability of high-quality samples. The additional challenge in structural genomics is the need to produce high numbers of proteins with low sequence similarities and poorly characterized or unknown properties. 'Structural-biology-grade' proteins must be generated in a quantity and quality suitable for structure determination experiments using X-ray crystallography or nuclear magnetic resonance (NMR). The choice of protein purification and handling procedures plays a critical role in obtaining high-quality protein samples. The purification procedure must yield a homogeneous protein and must be highly reproducible in order to supply milligram quantities of protein and/or its derivative containing marker atom(s). At the Midwest Center for Structural Genomics we have developed protocols for high-throughput protein purification. These protocols have been implemented on AKTA EXPLORER 3D and AKTA FPLC 3D workstations capable of performing multidimensional chromatography. The automated chromatography has been successfully applied to many soluble proteins of microbial origin. Various MCSG purification strategies, their implementation, and their success rates are discussed in this paper.     

Primitive Defence: The MiAMP1 Antimicrobial Peptide Family

The founder of the MiAMP1 protein family was originally isolated from Macadamia integrifolia and had antimicrobial activity in vitro. MiAMP1 was the first plant protein with a structure containing a βγ-crystallin precursor fold, a structural superfamily associated with antimicrobial proteins in other kingdoms. In recent times, expanding plant genomics information has revealed that genes encoding homologues of MiAMP1 are conserved across the plant kingdom from lycophytes, gymnosperms to early angiosperms (e.g. Amborella, Papaver) and some monocots (e.g. Zantedeschia, Zea, Sorghum). Many studies of plant–pathogen interactions in gymnosperms have demonstrated a potential role for MiAMP1 family members in defence against fungal pathogens. This commentary describes the discovery and diversity of this protein family and considers current evidence supporting, and future opportunities for substantiating, a role in defence in primitive plants, and why this role may have diminished in higher plants.