The 2002 Olympic Games of protein structure prediction

The summer of every even year is considered by the protein structure prediction community as the Olympic Games season, because in addition to a number of continuous benchmarking experiments such as LiveBench, much effort is invested in the blind prediction experiments CASP and CAFASP. Here we report the major advances registered in the field since the last Games of 2000, as measured by the recently completed LiveBench-4 experiment. These results provide a timely measure of the capabilities of current methods and of their expected performance in the upcoming CASP-5 and CAFASP-3 experiments. We also describe the initiation of the two new, community-wide experiments, PDB-CAFASP and MR-CAFASP. These new experiments extend the scope of previous efforts and may have important implications for structural genomics.     

Improving sequence-based fold recognition by using 3D model quality assessment

MOTIVATION: The ability of a simple method (MODCHECK) to determine the sequence-structure compatibility of a set of structural models generated by fold recognition is tested in a thorough benchmark analysis. Four Model Quality Assessment Programs (MQAPs) were tested on 188 targets from the latest LiveBench-9 automated structure evaluation experiment. We systematically test and evaluate whether the MQAP methods can successfully detect native-like models. RESULTS: We show that compared with the other three methods tested MODCHECK is the most reliable method for consistently performing the best top model selection and for ranking the models. In addition, we show that the choice of model similarity score used to assess a model's similarity to the experimental structure can influence the overall performance of these tools. Although these MQAP methods fail to improve the model selection performance for methods that already incorporate protein three dimension (3D) structural information, an improvement is observed for methods that are purely sequence-based, including the best profile-profile methods. This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information. CONTACT: d.jones@cs.ucl.ac.uk     

An algorithm for automated analysis of ultrasound images to measure tendon excursion in vivo

The accuracy of an algorithm for the automated tracking of tendon excursion from ultrasound images was tested in three experiments. Because the automated method could not be tested against direct measurements of tendon excursion in vivo, an indirect validation procedure was employed. In one experiment, a wire "phantom" was moved a known distance across the ultrasound probe and the automated tracking results were compared with the known distance. The excursion of the musculotendinous junction of the gastrocnemius during frontal and sagittal plane movement of the ankle was assessed in a single cadaver specimen both by manual tracking and with a cable extensometer sutured to the gastrocnemius muscle. A third experiment involved estimation of Achilles tendon excursion in vivo with both manual and automated tracking. Root mean squared (RMS) error was calculated between pairs of measurements after each test. Mean RMS errors of less than 1 mm were observed for the phantom experiments. For the in vitro experiment, mean RMS errors of 8-9% of the total tendon excursion were observed. Mean RMS errors of 6-8% of the total tendon excursion were found in vivo. The results indicate that the proposed algorithm accurately tracks Achilles tendon excursion, but further testing is necessary to determine its general applicability.     

Automated and assisted RNA resonance assignment using NMR chemical shift statistics

The three-dimensional structure determination of RNAs by NMR spectroscopy relies on chemical shift assignment, which still constitutes a bottleneck. In order to develop more efficient assignment strategies, we analysed relationships between sequence and ¹H and ¹³C chemical shifts. Statistics of resonances from regularly Watson–Crick base-paired RNA revealed highly characteristic chemical shift clusters. We developed two approaches using these statistics for chemical shift assignment of double-stranded RNA (dsRNA): a manual approach that yields starting points for resonance assignment and simplifies decision trees and an automated approach based on the recently introduced automated resonance assignment algorithm FLYA. Both strategies require only unlabeled RNAs and three 2D spectra for assigning the H2/C2, H5/C5, H6/C6, H8/C8 and H1′/C1′ chemical shifts. The manual approach proved to be efficient and robust when applied to the experimental data of RNAs with a size between 20 nt and 42 nt. The more advanced automated assignment approach was successfully applied to four stem-loop RNAs and a 42 nt siRNA, assigning 92–100% of the resonances from dsRNA regions correctly. This is the first automated approach for chemical shift assignment of non-exchangeable protons of RNA and their corresponding ¹³C resonances, which provides an important step toward automated structure determination of RNAs.     

Intelligent software for laboratory automation

The automation of laboratory techniques has greatly increased the number of experiments that can be carried out in the chemical and biological sciences. Until recently, this automation has focused primarily on improving hardware. Here we argue that future advances will concentrate on intelligent software to integrate physical experimentation and results analysis with hypothesis formulation and experiment planning. To illustrate our thesis, we describe the 'Robot Scientist' - the first physically implemented example of such a closed loop system. In the Robot Scientist, experimentation is performed by a laboratory robot, hypotheses concerning the results are generated by machine learning and experiments are allocated and selected by a combination of techniques derived from artificial intelligence research. The performance of the Robot Scientist has been evaluated by a rediscovery task based on yeast functional genomics. The Robot Scientist is proof that the integration of programmable laboratory hardware and intelligent software can be used to develop increasingly automated laboratories.     

Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection

Meta-predictors make predictions by organizing and processing the predictions produced by several other predictors in a defined problem domain. A proficient meta-predictor not only offers better predicting performance than the individual predictors from which it is constructed, but it also relieves experimentally researchers from making difficult judgments when faced with conflicting results made by multiple prediction programs. As increasing numbers of predicting programs are being developed in a large number of fields of life sciences, there is an urgent need for effective meta-prediction strategies to be investigated. We compiled four unbiased phosphorylation site datasets, each for one of the four major serine/threonine (S/T) protein kinase families-CDK, CK2, PKA and PKC. Using these datasets, we examined several meta-predicting strategies with 15 phosphorylation site predictors from six predicting programs: GPS, KinasePhos, NetPhosK, PPSP, PredPhospho and Scansite. Meta-predictors constructed with a generalized weighted voting meta-predicting strategy with parameters determined by restricted grid search possess the best performance, exceeding that of all individual predictors in predicting phosphorylation sites of all four kinase families. Our results demonstrate a useful decision-making tool for analysing the predictions of the various S/T phosphorylation site predictors. An implementation of these meta-predictors is available on the web at: http://MetaPred.umn.edu/MetaPredPS/.     

Reinvestigation of the N-terminal amino acid sequence of β-lipotropin from human pituitary glands

The N-terminal sequence of the first 60 amino acid residues of human β-LPH was reinvestigated by automated Edman degradation on the intact peptide. The result shows some differences with the recently proposed data. We have established the amino acid sequence of residues 9–26 to be Glu-Gly-Asp-Gly-Pro-Asp-Gly-Pro-Ala-Asp-Asp-Gly-Ala-Gly-Ala-Gln-Ala-Asp. From residues 1–8 and 27–60 the sequence is exactly identical with that of recently reported data.     

Structure–Activity Relationship of novel phenylacetic CXCR1 inhibitors

We reported recently the Structure–Activity Relationship (SAR) of a class of CXCL8 allosteric modulators. They invariably share a 2-arylpropionic moiety so far considered a key structural determinant of the biological activity. We show the results of recent SAR studies on a novel series of phenylacetic derivatives supported by a combined approach of mutagenesis experiments and conformational analysis. The results suggest novel insights on the fine role of the propionic/acetic chain in the modulation of CXCL8 receptors.     

High-throughput crystallization-to-structure pipeline at RIKEN SPring-8 Center

A high-throughput crystallization-to-structure pipeline for structural genomics was recently developed at the Advanced Protein Crystallography Research Group of the RIKEN SPring-8 Center in Japan. The structure determination pipeline includes three newly developed technologies for automating X-ray protein crystallography: the automated crystallization and observation robot system "TERA", the SPring-8 Precise Automatic Cryosample Exchanger "SPACE" for automated data collection, and the Package of Expert Researcher's Operation Network "PERON" for automated crystallographic computation from phasing to model checking. During the 5 years following April, 2002, this pipeline was used by seven researchers to determine 138 independent crystal structures (resulting from 437 purified proteins, 234 cryoloop-mountable crystals, and 175 diffraction data sets). The protocols used in the high-throughput pipeline are described in this paper.     

Towards automation of glycomic profiling of complex biological materials

Glycosylation is considered one of the most complex and structurally diverse post-translational modifications of proteins. Glycans play important roles in many biological processes such as protein folding, regulation of protein stability, solubility and serum half-life. One of the ways to study glycosylation is systematic structural characterizations of protein glycosylation utilizing glycomics methodology based around mass spectrometry (MS). The most prevalent bottleneck stages for glycomic analyses is laborious sample preparation steps. Therefore, in this study, we aim to improve sample preparations by automation. We recently demonstrated the successful application of an automated high-throughput (HT), glycan permethylation protocol based on 96-well microplates, in the analysis of purified glycoproteins. Therefore, we wanted to test if these developed HT methodologies could be applied to more complex biological starting materials. Our automated 96-well-plate based permethylation method showed very comparable results with established glycomic methodology. Very similar glycomic profiles were obtained for complex glycoprotein/protein mixtures derived from heterogeneous mouse tissues. Automated N-glycan release, enrichment and automated permethylation of samples proved to be convenient, robust and reliable. Therefore we conclude that these automated procedures are a step forward towards the development of a fully automated, fast and reliable glycomic profiling system for analysis of complex biological materials.     

Uniform standards for genome databases in forest and fruit trees

TreeGenes and tree fruit Genome Database Resources serve the international forestry and fruit tree genomics research communities, respectively. These databases hold similar sequence data and provide resources for the submission and recovery of this information in order to enable comparative genomics research. Large-scale genotype and phenotype projects have recently spawned the development of independent tools and interfaces within these repositories to deliver information to both geneticists and breeders. The increase in next generation sequencing projects has increased the amount of data as well as the scale of analysis that can be performed. These two repositories are now working towards a similar goal of archiving the diverse, independent data sets generated from genotype/phenotype experiments. This is achieved through focused development on data input standards (templates), pipelines for the storage and automated curation, and consistent annotation efforts through the application of widely accepted ontologies to improve the extraction and exchange of the data for comparative analysis. Efforts towards standardization are not limited to genotype/phenotype experiments but are also being applied to other data types to improve gene prediction and annotation for de novo sequencing projects. The resources developed towards these goals represent the first large-scale coordinated effort in plant databases to add informatics value to diverse genotype/phenotype experiments.     

Small-scale, semi-automated purification of eukaryotic proteins for structure determination

A simple approach that allows cost-effective automated purification of recombinant proteins in levels sufficient for functional characterization or structural studies is described. Studies with four human stem cell proteins, an engineered version of green fluorescent protein, and other proteins are included. The method combines an expression vector (pVP62K) that provides in vivo cleavage of an initial fusion protein, a factorial designed auto-induction medium that improves the performance of small-scale production, and rapid, automated metal affinity purification of His8-tagged proteins. For initial small-scale production screening, single colony transformants were grown overnight in 0.4 ml of auto-induction medium, produced proteins were purified using the Promega Maxwell 16, and purification results were analyzed by Caliper LC90 capillary electrophoresis. The yield of purified [U-15N]-His8-Tcl-1 was 7.5 microg/ml of culture medium, of purified [U-15N]-His8-GFP was 68 microg/ml, and of purified selenomethione-labeled AIA-GFP (His8 removed by treatment with TEV protease) was 172 microg/ml. The yield information obtained from a successful automated purification from 0.4 ml was used to inform the decision to scale-up for a second meso-scale (10-50 ml) cell growth and automated purification. 1H-15N NMR HSQC spectra of His8-Tcl-1 and of His8-GFP prepared from 50 ml cultures showed excellent chemical shift dispersion, consistent with well folded states in solution suitable for structure determination. Moreover, AIA-GFP obtained by proteolytic removal of the His8 tag was subjected to crystallization screening, and yielded crystals under several conditions. Single crystals were subsequently produced and optimized by the hanging drop method. The structure was solved by molecular replacement at a resolution of 1.7 A. This approach provides an efficient way to carry out several key target screening steps that are essential for successful operation of proteomics pipelines with eukaryotic proteins: examination of total expression, determination of proteolysis of fusion tags, quantification of the yield of purified protein, and suitability for structure determination.     

Integrated platform for manual and high‐throughput statistical validation of tandem mass spectra

As proteomic data sets increase in size and complexity, the necessity for database‐centric software systems able to organize, compare, and visualize all the proteomic experiments in a lab grows. We recently developed an integrated platform called high‐throughput autonomous proteomic pipeline (HTAPP) for the automated acquisition and processing of quantitative proteomic data, and integration of proteomic results with existing external protein information resources within a lab‐based relational database called PeptideDepot. Here, we introduce the peptide validation software component of this system, which combines relational database‐integrated electronic manual spectral annotation in Java with a new software tool in the R programming language for the generation of logistic regression spectral models from user‐supplied validated data sets and flexible application of these user‐generated models in automated proteomic workflows. This logistic regression spectral model uses both variables computed directly from SEQUEST output in addition to deterministic variables based on expert manual validation criteria of spectral quality. In the case of linear quadrupole ion trap (LTQ) or LTQ‐FTICR LC/MS data, our logistic spectral model outperformed both XCorr (242% more peptides identified on average) and the X!Tandem E‐value (87% more peptides identified on average) at a 1% false discovery rate estimated by decoy database approach.     

Comprehensive label-free method for the relative quantification of proteins from biological samples

Pharmaceutical companies and regulatory agencies are broadly pursuing biomarkers as a means to increase the productivity of drug development. Quantifying differential levels of proteins from complex biological samples such as plasma or cerebrospinal fluid is one specific approach being used to identify markers of drug action, efficacy, toxicity, etc. We have developed a comprehensive, fully automated, and label-free approach to relative protein quantification from LC-MS/MS experiments of proteolytic protein digests including: de-noising, mass and charge state estimation, chromatographic alignment, and peptide quantification via integration of extracted ion chromatograms. Results from a variance components study of the entire method indicate that most of the variability is attributable to the LC-MS injection, with a median peptide LC-MS injection coefficient of variation of 8% on a ThermoFinnigan LTQ mass spectrometer. Spiked recovery results suggest a quantifiable range of approximately 32-fold for a sample protein.     

Challenges and opportunities of automated protein-protein docking: HDOCK server vs human predictions in CAPRI Rounds 38-46

Protein-protein docking plays an important role in the computational prediction of the complex structure between two proteins. For years, a variety of docking algorithms have been developed, as witnessed by the critical assessment of prediction interactions (CAPRI) experiments. However, despite their successes, many docking algorithms often require a series of manual operations like modeling structures from sequences, incorporating biological information, and selecting final models. The difficulties in these manual steps have significantly limited the applications of protein-protein docking, as most of the users in the community are nonexperts in docking. Therefore, automated docking like a web server, which can give a comparable performance to human docking protocol, is pressingly needed. As such, we have participated in the blind CAPRI experiments for Rounds 38-45 and CASP13-CAPRI challenge for Round 46 with both our HDOCK automated docking web server and human docking protocol. It was shown that our HDOCK server achieved an “acceptable” or higher CAPRI-rated model in the top 10 submitted predictions for 65.5% and 59.1% of the targets in the docking experiments of CAPRI and CASP13-CAPRI, respectively, which are comparable to 66.7% and 54.5% for human docking protocol. Similar trends can also be observed in the scoring experiments. These results validated our HDOCK server as an efficient automated docking protocol for nonexpert users. Challenges and opportunities of automated docking are also discussed.     

Chemical synthesis, purification, and characterization of two inflammatory proteins, neutrophil activating peptide 1 (interleukin-8) and neutrophil activating peptide

Two recently identified pro-inflammatory proteins, namely, neutrophil activating peptide 1 (NAP-1) [also termed interleukin-8 (IL-8)] and NAP-2, were chemically synthesized, purified, and characterized. The fully protected NAP-1/IL-8 (72 residues) and NAP-2 (70 residues) peptide chains were assembled by automated solid-phase methods with average stepwise yields of 99.5 and 99.3%, resulting in overall chain assembly yields of 70 and 62%, respectively. Deprotection resulted in crude products, which were allowed to fold by air oxidation, and were purified by two cycles of reverse-phase high-pressure liquid chromatography, yielding 27 mg of NAP-1/IL-8 and 22 mg of NAP-2. Purity was established by reverse-phase high-pressure liquid chromatography and isoelectric focusing, and the primary structures of the purified products were verified by using mass spectrometry and Edman sequencing methods. Synthetic and recombinant NAP-1/IL-8 were equally active on human neutrophil granulocytes as determined by measuring the induction of cytosolic free calcium, elastase release, and chemotaxis. Synthetic NAP-2 was equivalent to purified natural NAP-2 in the elastase release and calcium mobilization assays, but it was consistently less potent (3-5-fold) as a stimulus of chemotaxis, perhaps indicative of additional chemotactic components in the natural preparation. The results indicate that by chemical synthesis these cytokines can be obtained in purity and quantities suitable for further structural analysis, as well as functional studies both in vivo and in vitro.(ABSTRACT TRUNCATED AT 250 WORDS)     

On the levels of phenylalanine, tyrosine and tetrahydrobiopterin in the blood of tumor-bearing organisms

The levels of free phenylalanine and free tyrosine (and m-tyrosine) as well as of protein-bound tyrosine were determined by means of automated aminoacid analysis and by reaction with 1-nitrosonaphthol(2). Their absolute values as well as their percentages relative to total aminoacids of the blood were markedly increased in all tumor patients tested, as well as in experimental tumor rats. Although tetrahydrobiopterin could scarcely be detected by fluorometric methods in the blood of control persons, it is accumulated blood of all tumor patients tested. The major part was found in the erythrocyte fraction. The results are discussed with respect to decreased phenylalanine hydroxylation rate and to depressed tyrosine catabolism recently found by means of in vivo experiments in tumor-bearing rats.     

A maternal Smad protein regulates early embryonic apoptosis in Xenopus laevis

We identified cDNAs encoding the Xenopus Smad proteins most closely related to mammalian Smad8, and we present a functional analysis of this activity (also referred to recently as xSmad11). Misexpression experiments indicate that xSmad8(11) regulates pathways distinct from those regulated by the closely related xSmad1. Embryos that develop from eggs depleted of xSmad8(11) mRNA fail to gastrulate; instead, at the time of gastrulation, they initiate a widespread program of apoptosis, via a CPP32/caspase 3 pathway. Embryos that avoid this fate display gastrulation defects. Activation of apoptosis is rescued by expression of xSmad8(11) but not xSmad1. Our results demonstrate an embryonic requirement for Smad8(11) activity and show that a maternally derived Smad signaling pathway is required for gastrulation and for mediating a cell survival program during early embryogenesis. We suggest that xSmad8(11) functions as part of a maternally derived mechanism shown previously by others to monitor Xenopus early embryonic cell cycles.