Protein Structure Initiative:Biology (PSI:Biology) is the third phase of PSI where protein structures are determined in high-throughput to characterize their biological functions. The transition to the third phase entailed the formation of PSI:Biology Partnerships which are composed of structural genomics centers and biomedical science laboratories. We present a method to examine the impact of protein structures determined under the auspices of PSI:Biology by measuring their rates of annotations. The mean numbers of annotations per structure and per residue are examined. These are designed to provide measures of the amount of structure to function connections that can be leveraged from each structure.
One result is that PSI:Biology structures are found to have a higher rate of annotations than structures determined during the first two phases of PSI. A second result is that the subset of PSI:Biology structures determined through PSI:Biology Partnerships have a higher rate of annotations than those determined exclusive of those partnerships. Both results hold when the annotation rates are examined either at the level of the entire protein or for annotations that are known to fall at specific residues within the portion of the protein that has a determined structure.
We conclude that PSI:Biology determines structures that are estimated to have a higher degree of biomedical interest than those determined during the first two phases of PSI based on a broad array of biomedical annotations. For the PSI:Biology Partnerships, we see that there is an associated added value that represents part of the progress toward the goals of PSI:Biology. We interpret the added value to mean that team-based structural biology projects that utilize the expertise and technologies of structural genomics centers together with biological laboratories in the community are conducted in a synergistic manner. We show that the annotation rates can be used in conjunction with established metrics, i.e. the numbers of structures and impact of publication records, to monitor the progress of PSI:Biology towards its goals of examining structure to function connections of high biomedical relevance. The metric provides an objective means to quantify the overall impact of PSI:Biology as it uses biomedical annotations from external sources.
Protein Structure Initiative; Structural genomics; Protein annotations; Protein annotation; Scientific partnerships; Structure to function relationships
The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years and has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe.
The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications.
structural genomics; Joint Center for Structural Genomics; Protein Structure Initiative
The software suite Xsolve semi-exhaustively explores key parameters of the X-ray structure-determination process to compute multiple three-dimensional protein structures independently and in parallel from a set of diffraction images. An optimal consensus model for subsequent manual refinement is computed from these structures.
The Joint Center for Structural Genomics (JCSG), one of four large-scale structure-determination centers funded by the US Protein Structure Initiative (PSI) through the National Institute for General Medical Sciences, has been operating an automated distributed structure-solution pipeline, Xsolve, for well over half a decade. During PSI-2, Xsolve solved, traced and partially refined 90% of the JCSG’s nearly 770 MAD/SAD structures at an average resolution of about 2 Å without human intervention. Xsolve executes many well established publicly available crystallography software programs in parallel on a commodity Linux cluster, resulting in multiple traces for any given target. Additional software programs have been developed and integrated into Xsolve to further minimize human effort in structure refinement. ConsensusModeler exploits complementarities in traces from Xsolve to compute a single optimal model for manual refinement. Xpleo is a powerful robotics-inspired algorithm to build missing fragments and qFit automatically identifies and fits alternate conformations.
distributed protein-structure determination; consensus models; parallel computing
Rational drug design relies on three-dimensional structures of biological macromolecules, especially proteins. Structural genomics high-throughput (HTP) structure determination platforms established by the NIH Protein Structure Initiative are uniquely suited to provide these structures. NMR plays a critical role since (i) many important protein targets do not form single crystals required for X-ray diffraction and (ii) NMR can provide valuable structural and dynamic information on proteins and their drug complexes that cannot be obtained with X-ray crystallography. In this article, recent advances of NMR driven by structural genomics projects are reviewed. These advances promise that future pharmaceutical discovery and design of drugs can increasingly rely on protocols for rapid and accurate NMR structure determination.
protein NMR; structural genomics; structural proteomics; drug discovery; protein interaction networks; structural bioinformatics
The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology.
Protein; Protein production; Structural biology; Structural databases; Structural genomics; Theoretical models
Protein X-ray crystallography recently celebrated its 50th anniversary. The structures of myoglobin and hemoglobin determined by Kendrew and Perutz provided the first glimpses into the complex protein architecture and chemistry. Since then, the field of structural molecular biology has experienced extraordinary progress and now over 53,000 proteins structures have been deposited into the Protein Data Bank. In the past decade many advances in macromolecular crystallography have been driven by world-wide structural genomics efforts. This was made possible because of third-generation synchrotron sources, structure phasing approaches using anomalous signal and cryo-crystallography. Complementary progress in molecular biology, proteomics, hardware and software for crystallographic data collection, structure determination and refinement, computer science, databases, robotics and automation improved and accelerated many processes. These advancements provide the robust foundation for structural molecular biology and assure strong contribution to science in the future. In this report we focus mainly on reviewing structural genomics high-throughput X-ray crystallography technologies and their impact.
This Perspective, arising from a workshop held in July 2008 in Buffalo NY, provides an overview of the role NMR has played in the United States Protein Structure Initiative (PSI), and a vision of how NMR will contribute to the forthcoming PSI-Biology program. NMR has contributed in key ways to structure production by the PSI, and new methods have been developed which are impacting the broader protein NMR community.
Future of structural genomics; Functional genomics; NMR; Crystallography; NMR methods; Protein Structure Initiative (PSI)
Despite continuing progress in X-ray crystallography and high-field NMR spectroscopy for determination of three-dimensional protein structures, the number of unsolved and newly discovered sequences grows much faster than that of determined structures. Protein modeling methods can possibly bridge this huge sequence-structure gap with the development of computational science. A grand challenging problem is to predict three-dimensional protein structure from its primary structure (residues sequence) alone. However, predicting residue contact maps is a crucial and promising intermediate step towards final three-dimensional structure prediction. Better predictions of local and non-local contacts between residues can transform protein sequence alignment to structure alignment, which can finally improve template based three-dimensional protein structure predictors greatly.
CNNcon, an improved multiple neural networks based contact map predictor using six sub-networks and one final cascade-network, was developed in this paper. Both the sub-networks and the final cascade-network were trained and tested with their corresponding data sets. While for testing, the target protein was first coded and then input to its corresponding sub-networks for prediction. After that, the intermediate results were input to the cascade-network to finish the final prediction.
The CNNcon can accurately predict 58.86% in average of contacts at a distance cutoff of 8 Å for proteins with lengths ranging from 51 to 450. The comparison results show that the present method performs better than the compared state-of-the-art predictors. Particularly, the prediction accuracy keeps steady with the increase of protein sequence length. It indicates that the CNNcon overcomes the thin density problem, with which other current predictors have trouble. This advantage makes the method valuable to the prediction of long length proteins. As a result, the effective prediction of long length proteins could be possible by the CNNcon.
One major objective of structural genomics efforts, including the NIH-funded Protein Structure Initiative (PSI), has been to increase the structural coverage of protein sequence space. Here, we present the target selection strategy used during the second phase of PSI (PSI-2). This strategy, jointly devised by the bioinformatics groups associated with the PSI-2 large-scale production centres, targets representatives from large, structurally uncharacterised protein domain families, and from structurally uncharacterised subfamilies in very large and diverse families with incomplete structural coverage. These very large families are extremely diverse both structurally and functionally, and are highly over-represented in known proteomes. On the basis of several metrics, we then discuss to what extent PSI-2, during its first three years, has increased the structural coverage of genomes, and contributed structural and functional novelty. Together, the results presented here suggest that PSI-2 is successfully meeting its objectives and provides useful insights into structural and functional space.
The ultimate goal of structural biology is to understand the structural basis of proteins in cellular processes. In structural biology, the most critical issue is the availability of high-quality samples. “Structural biology-grade” proteins must be generated in the quantity and quality suitable for structure determination using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The purification procedures must reproducibly yield homogeneous proteins or their derivatives containing marker atom(s) in milligram quantities. The choice of protein purification and handling procedures plays a critical role in obtaining high-quality protein samples. With structural genomics emphasizing a genome-based approach in understanding protein structure and function, a number of unique structures covering most of the protein folding space have been determined and new technologies with high efficiency have been developed. At the Midwest Center for Structural Genomics (MCSG), we have developed semi-automated protocols for high-throughput parallel protein expression and purification. A protein, expressed as a fusion with a cleavable affinity tag, is purified in two consecutive immobilized metal affinity chromatography (IMAC) steps: (i) the first step is an IMAC coupled with buffer-exchange, or size exclusion chromatography (IMAC-I), followed by the cleavage of the affinity tag using the highly specific Tobacco Etch Virus (TEV) protease;  the second step is IMAC and buffer exchange (IMAC-II) to remove the cleaved tag and tagged TEV protease. These protocols have been implemented on multidimensional chromatography workstations and, as we have shown, many proteins can be successfully produced in large-scale. All methods and protocols used for purification, some developed by MCSG, others adopted and integrated into the MCSG purification pipeline and more recently the Center for Structural Genomics of Infectious Diseases (CSGID) purification pipeline, are discussed in this chapter.
domain design; expression vectors; gene cloning; protein purification; crystallization screening; quality assessment
The field of Membrane Protein Structural Biology has grown significantly since its first landmark in 1985 with the first three-dimensional atomic resolution structure of a membrane protein. Nearly twenty-six years later, the crystal structure of the beta2 adrenergic receptor in complex with G protein has contributed to another landmark in the field leading to the 2012 Nobel Prize in Chemistry. At present, more than 350 unique membrane protein structures solved by X-ray crystallography (http://blanco.biomol.uci.edu/mpstruc/exp/list, Stephen White Lab at UC Irvine) are available in the Protein Data Bank. The advent of genomics and proteomics initiatives combined with high-throughput technologies, such as automation, miniaturization, integration and third-generation synchrotrons, has enhanced membrane protein structure determination rate. X-ray crystallography is still the only method capable of providing detailed information on how ligands, cofactors, and ions interact with proteins, and is therefore a powerful tool in biochemistry and drug discovery. Yet the growth of membrane protein crystals suitable for X-ray diffraction studies amazingly remains a fine art and a major bottleneck in the field. It is often necessary to apply as many innovative approaches as possible. In this review we draw attention to the latest methods and strategies for the production of suitable crystals for membrane protein structure determination. In addition we also highlight the impact that third-generation synchrotron radiation has made in the field, summarizing the latest strategies used at synchrotron beamlines for screening and data collection from such demanding crystals. This article is part of a Special Issue entitled: Structural and biophysical characterisation of membrane protein-ligand binding.
•Overview of the most recent advances regarding the growth of membrane protein crystals•Rational design of new crystallization screens for membrane proteins•New automated method for dehydration of membrane proteins•High-throughput approach in seeding of membrane protein crystals•Recent developments in membrane protein structure determination
Membrane protein; Crystal dehydration; Crystal seeding; Macromolecular crystallography; In situ data collection; XFEL
This review article surveys the protein structures determined by Joint Center for Structural Genomics and published in this special issue of Acta Crystallographica Section F.
During the past decade, the Protein Structure Initiative (PSI) centres have become major contributors of new families, superfamilies and folds to the Structural Classification of Proteins (SCOP) database. The PSI results have increased the diversity of protein structural space and accelerated our understanding of it. This review article surveys a selection of protein structures determined by the Joint Center for Structural Genomics (JCSG). It presents previously undescribed β-sheet architectures such as the double barrel and spiral β-roll and discusses new examples of unusual topologies and peculiar structural features observed in proteins characterized by the JCSG and other Structural Genomics centres.
structural genomics; protein folding; structural classification
Protein-biomineral interactions are paramount to materials production in biology, including the mineral phase of hard tissue. Unfortunately, the structure of biomineral-associated proteins cannot be determined by X-ray crystallography or solution NMR. Here we report a method for determining the structure of biomineral-associated proteins. The method combines solid-state NMR (ssNMR) and ssNMR-biased computational structure prediction. In addition, the algorithm is able to identify lattice geometries most compatible with ssNMR constraints, representing a quantitative, novel method for investigating crystal-face binding specificity. We use this new method to determine most of the structure of human salivary statherin interacting with the mineral phase of tooth enamel. Computation and experiment converge on an ensemble of related structures and identify preferential binding at three crystal surfaces. The work represents a significant advance toward determining structure of biomineral-adsorbed protein using experimentally biased structure prediction. This method is generally applicable to proteins that can be chemically synthesized.
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.
affinity chromatography; automation; protein purification; structural genomics
An abundance of protein structures emerging from structural genomics and the Protein Structure Initiative (PSI) are not amenable to ready functional assignment because of a lack of sequence and structural homology to proteins of known function. We describe a high-throughput NMR methodology (FAST-NMR) to annotate the biological function of novel proteins through the structural and sequence analysis of protein-ligand interactions. This is based on basic tenets of biochemistry where proteins with similar functions will have similar active sites and exhibit similar ligand binding interactions, despite global differences in sequence and structure. Protein-ligand interactions are determined through a tiered NMR screen using a library composed of compounds with known biological activity. A rapid co-structure is determined by combining the experimental identification of the ligand-binding site from NMR chemical shift perturbations with the protein-ligand docking program AutoDock. Our CPASS (Comparison of Protein Active Site Structures) software and database is then used to compare this active site with proteins of known function. The methodology is demonstrated using unannotated protein SAV1430 from Staphylococcus aureus.
NMR Screening; High-throughput NMR; Protein-Ligand Binding; Function Assignment; Hypothetical Protein; SAV1430
Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding.
structural biology; structural bioinformatics; structure-based drug design; high-throughput crystallography; virtual screening; multiprotein complexes
Ion mobility–mass spectrometry is often applied to the structural elucidation of multiprotein assemblies in cases where X-ray crystallography or NMR experiments have proved challenging. Such applications are growing steadily as we continue to probe regions of the proteome that are less-accessible to such high-resolution structural biology tools. Since ion mobility measures protein structure in the absence of bulk solvent, strategies designed to more-broadly stabilize native-like protein structures in the gas-phase would greatly enable the application of such measurements to challenging structural targets. Recently, we have begun investigating the ability of salt-based solution additives that remain bound to protein ions in the gas-phase to stabilize native-like protein structures. These experiments, which utilize collision induced unfolding and collision induced dissociation in a tandem mass spectrometry mode to measure protein stability, seek to develop a rank-order similar to the Hofmeister series that categorizes the general ability of different anions and cations to stabilize gas-phase protein structure. Here, we study magnesium chloride as a potential stabilizing additive for protein structures in vacuo, and find that the addition of this salt to solutions prior to nano-electrospray ionization dramatically enhances multiprotein complex structural stability in the gas-phase. Based on these experiments, we also refine the physical mechanism of cation-based protein complex ion stabilization by tracking the unfolding transitions experienced by cation-bound complexes. Upon comparison with unbound proteins, we find strong evidence that stabilizing cations act to tether protein complex structure. We conclude by putting the results reported here in context, and by projecting the future applications of this method.
Ion mobility-mass spectrometry; structural stabilization; multiprotein complex; collision induced unfolding; collision induced dissociation
Specific use cases of TOPSAN, an innovative collaborative platform for creating, sharing and distributing annotations and insights about protein structures, such as those determined by high-throughput structural genomics in the Protein Structure Initiative (PSI), are described. TOPSAN is the main annotation platform for JCSG structures and serves as a conduit for initiating collaborations with the biological community, as illustrated in this special issue of Acta Crystallographica Section F. Developed at the JCSG with the goal of opening a dialogue on the novel protein structures with the broader biological community, TOPSAN is a unique tool for fostering distributed collaborations and provides an efficient pathway to peer-reviewed publications.
The NIH Protein Structure Initiative centers, such as the Joint Center for Structural Genomics (JCSG), have developed highly efficient technological platforms that are capable of experimentally determining the three-dimensional structures of hundreds of proteins per year. However, the overwhelming majority of the almost 5000 protein structures determined by these centers have yet to be described in the peer-reviewed literature. In a high-throughput structural genomics environment, the process of structure determination occurs independently of any associated experimental characterization of function, which creates a challenge for the annotation and analysis of structures and the publication of these results. This challenge has been addressed by developing TOPSAN (‘The Open Protein Structure Annotation Network’), which enables the generation of knowledge via collaborations among globally distributed contributors supported by automated amalgamation of available information. TOPSAN currently provides annotations for all protein structures determined by the JCSG in addition to preliminary annotations on a large number of structures from the other PSI production centers. TOPSAN-enabled collaborations have resulted in insightful structure–function analysis for many proteins and have led to numerous peer-reviewed publications, as exemplified by the articles included in this issue of Acta Crystallographica Section F.
collaborative annotations; structural genomics; Protein Structure Initiative
China has a strong background in X-ray crystallography dating back to the 1920s. Protein crystallography research in China was first developed following the successful synthesis of insulin in China in 1966. The subsequent determination of the three-dimensional structure of porcine insulin made China one of the few countries which could determine macromolecular structures by X-ray diffraction methods in the late 1960s and early 1970s. After a slow period during the 1970s and 1980s, protein crystallography in China has reached a new climax with a number of outstanding accomplishments. Here, I review the history and progress of protein crystallography in China and detail some of the recent research highlights, including the crystal structures of two membrane proteins as well as the structural genomics initiative in China.
protein crystallography; history; structural biology; macromolecular structure
The Protein Structure Initiative:Biology-Materials Repository (PSI:Biology-MR; MR; http://psimr.asu.edu) sequence-verifies, annotates, stores, and distributes the protein expression plasmids and vectors created by the Protein Structure Initiative (PSI). The MR has developed an informatics and sample processing pipeline that manages this process for thousands of samples per month from nearly a dozen PSI centers. DNASU (http://dnasu.asu.edu), a freely searchable database, stores the plasmid annotations, which include the full-length sequence, vector information, and associated publications for over 130,000 plasmids created by our laboratory, by the PSI and other consortia, and by individual laboratories for distribution to researchers worldwide. Each plasmid links to external resources, including the PSI Structural Biology Knowledgebase (http://sbkb.org), which facilitates cross-referencing of a particular plasmid to additional protein annotations and experimental data. To expedite and simplify plasmid requests, the MR uses an expedited material transfer agreement (EP-MTA) network, where researchers from network institutions can order and receive PSI plasmids without institutional delays. Currently over 39,000 protein expression plasmids and 78 empty vectors from the PSI are available upon request from DNASU. Overall, the MR’s repository of expression-ready plasmids, its automated pipeline, and the rapid process for receiving and distributing these plasmids more effectively allows the research community to dissect the biological function of proteins whose structures have been studied by the PSI.
plasmid; structural biology; Protein Structure Initiative; PSI:Biology; protein expression
The Technology Portal of the Protein Structure Initiative Structural Biology Knowledgebase (PSI SBKB; http://technology.sbkb.org/portal/) is a web resource providing information about methods and tools that can be used to relieve bottlenecks in many areas of protein production and structural biology research. Several useful features are available on the web site, including multiple ways to search the database of over 250 technological advances, a link to videos of methods on YouTube, and access to a technology forum where scientists can connect, ask questions, get news, and develop collaborations. The Technology Portal is a component of the PSI SBKB (http://sbkb.org), which presents integrated genomic, structural, and functional information for all protein sequence targets selected by the Protein Structure Initiative. Created in collaboration with the Nature Publishing Group, the SBKB offers an array of resources for structural biologists, such as a research library, editorials about new research advances, a featured biological system each month, and a Functional Sleuth for searching protein structures of unknown function. An overview of the various features and examples of user searches highlight the information, tools, and avenues for scientific interaction available through the Technology Portal.
Database; Protein; Protein Production; Structural Biology; Structural Genomics; Technology
SCWRL and MolIDE are software applications for prediction of protein structures. SCWRL is designed specifically for the task of prediction of side-chain conformations given a fixed backbone usually obtained from an experimental structure determined by X-ray crystallography or NMR. SCWRL is a command-line program that typically runs in a few seconds. MolIDE provides a graphical interface for basic comparative (homology) modeling using SCWRL and other programs. MolIDE takes an input target sequence, and uses PSI-BLAST to identify and align templates for comparative modeling of the target. The sequence alignment to any template can be manually modified within a graphical window of the target-template alignment and visualization of the alignment on the template structure. MolIDE builds the model of the target structure based on the template backbone, predicted side-chain conformations with SCWRL, and a loop-modeling program for insertion-deletion regions with user-selected sequence segments. SCWRL and MolIDE can be obtained at http://dunbrack.fccc.edu/Software.php.
Computational methods; Protein structure prediction; Comparative (homology) modeling
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.
Protein structure determination; Structural genomics; Evolution; Protein universe
The New York Consortium on Membrane Protein Structure (NYCOMPS) was formed to accelerate the acquisition of structural information on membrane proteins by applying a structural genomics approach. NY-COMPS comprises a bioinformatics group, a centralized facility operating a high-throughput cloning and screening pipeline, a set of associated wet labs that perform high-level protein production and structure determination by x-ray crystallography and NMR, and a set of investigators focused on methods development. In the first three years of operation, the NYCOMPS pipeline has so far produced and screened 7,250 expression constructs for 8,045 target proteins. Approximately 600 of these verified targets were scaled up to levels required for structural studies, so far yielding 24 membrane protein crystals. Here we describe the overall structure of NYCOMPS and provide details on the high-throughput pipeline.
Membrane proteins; Structural genomics; High throughput; NMR; X-ray
Protein-RNA interactions play fundamental roles in many biological processes. Understanding the molecular mechanism of protein-RNA recognition and formation of protein-RNA complexes is a major challenge in structural biology. Unfortunately, the experimental determination of protein-RNA complexes is tedious and difficult, both by X-ray crystallography and NMR. For many interacting proteins and RNAs the individual structures are available, enabling computational prediction of complex structures by computational docking. However, methods for protein-RNA docking remain scarce, in particular in comparison to the numerous methods for protein-protein docking.
We developed two medium-resolution, knowledge-based potentials for scoring protein-RNA models obtained by docking: the quasi-chemical potential (QUASI-RNP) and the Decoys As the Reference State potential (DARS-RNP). Both potentials use a coarse-grained representation for both RNA and protein molecules and are capable of dealing with RNA structures with posttranscriptionally modified residues. We compared the discriminative power of DARS-RNP and QUASI-RNP for selecting rigid-body docking poses with the potentials previously developed by the Varani and Fernandez groups.
In both bound and unbound docking tests, DARS-RNP showed the highest ability to identify native-like structures. Python implementations of DARS-RNP and QUASI-RNP are freely available for download at http://iimcb.genesilico.pl/RNP/
RNA; protein; RNP; macromolecular docking; complex modeling; structural bioinformatics