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1.  CASP10 results compared to those of previous CASP experiments 
Proteins  2013;82(0 2):164-174.
We compare results of the community efforts in modeling protein structures in the tenth CASP experiment, with those in earlier CASPs, particularly in CASP5, a decade ago. There is a substantial improvement in template based model accuracy as reflected in more successful modeling of regions of structure not easily derived from a single experimental structure template, most likely reflecting intensive work within the modeling community in developing methods that make use of multiple templates, as well as the increased number of experimental structures available. Deriving structural information not obvious from a template is the most demanding as well as one of the most useful tasks that modeling can perform. Thus this is gratifying progress. By contrast, overall backbone accuracy of models appears little changed in the last decade. This puzzling result is explained by two factors – increased database size in some ways makes it harder to choose the best available templates, and the increased intrinsic difficulty of CASP targets, as experimental work has progressed to larger and more unusual structures. There is no detectable recent improvement in template free modeling, but again, this may reflect the changing nature of CASP targets.
doi:10.1002/prot.24448
PMCID: PMC4180100  PMID: 24150928
Protein Structure Prediction; Community Wide Experiment; CASP
2.  CASP9 results compared to those of previous CASP experiments 
Proteins  2011;79(0 10):196-207.
The quality of structure models submitted to CASP9 is analyzed in the context of previous CASPs. Comparison methods are similar to those used in previous papers in this series, with the addition of new methods for looking at model quality in regions not covered by a single best structural template, alignment accuracy, and progress for template free models. Progress in this CASP was again modest, and statistically hard to validate. Nevertheless, there are several positive trends. There is an indication of improvement in overall model quality for the mid-range of template based modeling difficulty, methods for identifying the best model from a set generated have improved, and there are strong indications of progress in the quality of template free models of short proteins. In addition, the new examination of model quality in regions of model not covered by the best available template reveals better performance than had previously been apparent.
doi:10.1002/prot.23182
PMCID: PMC4180080  PMID: 21997643
Protein Structure Prediction; Community Wide Experiment; CASP
3.  Critical Assessment of Methods of Protein Structure Prediction (CASP) - Round IX 
Proteins  2011;79(0 10):1-5.
This paper is an introduction to the special issue of the journal PROTEINS, dedicated to the ninth CASP experiment to assess the state of the art in protein structure modeling. The paper describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Methods for modeling protein structure continue to advance, although at a more modest pace than in the early CASP experiments. Developments of note are indications of improvement in model accuracy for some classes of target, an improved ability to choose the most accurate of a set of generated models, and evidence of improvement in accuracy for short ‘new fold’ models. In addition, a new analysis of regions of models not derivable from the most obvious template structure has revealed better performance than expected.
doi:10.1002/prot.23200
PMCID: PMC4180088  PMID: 21997831
Protein Structure Prediction; Community Wide Experiment; CASP
4.  Definition and Classification of Evaluation Units for CASP10 
Proteins  2013;82(0 2):14-25.
For the 10th experiment on Critical Assessment of the techniques of protein Structure Prediction (CASP) the prediction target proteins were broken into independent evaluation units (EUs), which were then classified into template-based modeling (TBM) or free modeling (FM) categories. We describe here how the EUs were defined and classified, what issues arose in the process, and how we resolved them. Evaluation units are frequently not the whole target proteins but the constituting structural domains. However, the assessors from CASP7 on combined more than one domain into one evaluation unit for some targets, which implied that the assessment also included evaluation of the prediction of the relative position and orientation of these domains. In CASP10, we followed and expanded this notion by defining multi-domain evaluation units for a number of targets. These included three EUs, each made of two domains of familiar fold but arranged in a novel manner and for which the focus of evaluation was the inter-domain arrangement. An EU was classified to the TBM category if a template could be found by sequence similarity searches and to FM if a structural template could not be found by structural similarity searches. The EUs that did not fall cleanly in either of these cases were classified case-by-case, often including consideration of the overall quality and characteristics of the predictions.
doi:10.1002/prot.24434
PMCID: PMC4133092  PMID: 24123179
CASP; CASP10; protein structure; structure prediction; domain definition; evaluation unit; assessment unit; classification
5.  Target Highlights in CASP9: Experimental Target Structures for the Critical Assessment of Techniques for Protein Structure Prediction 
Proteins  2011;79(0 10):6-20.
One goal of the CASP Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction is to identify the current state of the art in protein structure prediction and modeling. A fundamental principle of CASP is blind prediction on a set of relevant protein targets, i.e. the participating computational methods are tested on a common set of experimental target proteins, for which the experimental structures are not known at the time of modeling. Therefore, the CASP experiment would not have been possible without broad support of the experimental protein structural biology community. In this manuscript, several experimental groups discuss the structures of the proteins which they provided as prediction targets for CASP9, highlighting structural and functional peculiarities of these structures: the long tail fibre protein gp37 from bacteriophage T4, the cyclic GMP-dependent protein kinase Iβ (PKGIβ) dimerization/docking domain, the ectodomain of the JTB (Jumping Translocation Breakpoint) transmembrane receptor, Autotaxin (ATX) in complex with an inhibitor, the DNA-Binding J-Binding Protein 1 (JBP1) domain essential for biosynthesis and maintenance of DNA base-J (β-D-glucosyl-hydroxymethyluracil) in Trypanosoma and Leishmania, an so far uncharacterized 73 residue domain from Ruminococcus gnavus with a fold typical for PDZ-like domains, a domain from the Phycobilisome (PBS) core-membrane linker (LCM) phycobiliprotein ApcE from Synechocystis, the Heat shock protein 90 (Hsp90) activators PFC0360w and PFC0270w from Plasmodium falciparum, and 2-oxo-3-deoxygalactonate kinase from Klebsiella pneumoniae.
doi:10.1002/prot.23196
PMCID: PMC3692002  PMID: 22020785
CASP; protein structure; X-ray crystallography; NMR; structure prediction
6.  Evaluation of model quality predictions in CASP9 
Proteins  2011;79(Suppl 10):91-106.
CASP has been assessing the state of the art in the a priori estimation of accuracy of protein structure prediction since 2006. The inclusion of model quality assessment category in CASP contributed to a rapid development of methods in this area. In the last experiment forty six quality assessment groups tested their approaches to estimate the accuracy of protein models as a whole and/or on a per-residue basis. We assessed the performance of these methods predominantly on the basis of the correlation between the predicted and observed quality of the models on both global and local scales. The ability of the methods to identify the models closest to the best one, to differentiate between good and bad models, and to identify well modeled regions was also analyzed. Our evaluations demonstrate that even though global quality assessment methods seem to approach perfection point (weighted average per-target Pearson's correlation coefficients as high as 0.97 for the best groups), there is still room for improvement. First, all top-performing methods use consensus approaches to generate quality estimates and this strategy has its own limitations and deficiencies. Second, the methods that are based on the analysis of individual models lag far behind clustering methods and need a boost in performance. The methods for estimating per-residue accuracy of models are less accurate than global quality assessment methods with an average weighted per-model correlation coefficient in the range of 0.63–0.72 for the best 10 groups.
doi:10.1002/prot.23180
PMCID: PMC3226935  PMID: 21997462
CASP; QA; model quality assessment; protein structure modeling; protein structure prediction
7.  Evaluation of residue-residue contact predictions in CASP9 
Proteins  2011;79(Suppl 10):119-125.
This paper presents the results of the assessment of the intramolecular residue-residue contact predictions submitted to CASP9. The methodology for the assessment does not differ from that used in previous CASPs, with two basic evaluation measures being the precision in recognizing contacts and the difference between the distribution of distances in the subset of predicted contact pairs versus all pairs of residues in the structure. The emphasis is placed on the prediction of long-range contacts (i.e. contacts between residues separated by at least twenty-four residues along sequence) in target proteins that cannot be easily modeled by homology. Although there is considerable activity in the field, the current analysis reports no discernable progress since CASP8.
doi:10.1002/prot.23160
PMCID: PMC3226919  PMID: 21928322
CASP; intramolecular contacts; residue-residue contact prediction; protein structure modeling
8.  Evaluation of disorder predictions in CASP9 
Proteins  2011;79(S10):107-118.
Lack of stable three-dimensional structure, or intrinsic disorder, is a common phenomenon in proteins. Naturally unstructured regions are proven to be essential for carrying function by many proteins and therefore identification of such regions is an important issue. CASP has been assessing the state of the art in predicting disorder regions from amino acid sequence since 2002. Here we present the results of the evaluation of the disorder predictions submitted to CASP9. The assessment is based on the evaluation measures and procedures used in previous CASPs. The balanced accuracy and the Matthews correlation coefficient were chosen as basic measures for evaluating the correctness of binary classifications. The area under the receiving operating characteristic curve was the measure of choice for evaluating probability-based predictions of disorder. The CASP9 methods are shown to perform slightly better than the CASP7 methods but not better than the methods in CASP8. It was also shown that capability of most CASP9 methods to predict disorder decreases with increasing minimum disorder segment length.
doi:10.1002/prot.23161
PMCID: PMC3212657  PMID: 21928402
CASP; intrinsically disordered proteins; unstructured proteins; rediction of disordered regions; assessment of disorder prediction
9.  Using multi-data hidden Markov models trained on local neighborhoods of protein structure to predict residue–residue contacts 
Bioinformatics  2009;25(10):1264-1270.
Motivation:Correct prediction of residue–residue contacts in proteins that lack good templates with known structure would take ab initio protein structure prediction a large step forward. The lack of correct contacts, and in particular long-range contacts, is considered the main reason why these methods often fail.
Results: We propose a novel hidden Markov model (HMM)-based method for predicting residue–residue contacts from protein sequences using as training data homologous sequences, predicted secondary structure and a library of local neighborhoods (local descriptors of protein structure). The library consists of recurring structural entities incorporating short-, medium- and long-range interactions and is general enough to reassemble the cores of nearly all proteins in the PDB. The method is tested on an external test set of 606 domains with no significant sequence similarity to the training set as well as 151 domains with SCOP folds not present in the training set. Considering the top 0.2 · L predictions (L=sequence length), our HMMs obtained an accuracy of 22.8% for long-range interactions in new fold targets, and an average accuracy of 28.6% for long-, medium- and short-range contacts. This is a significant performance increase over currently available methods when comparing against results published in the literature.
Availability: http://predictioncenter.org/Services/FragHMMent/
Contact: torgeir.hvidsten@plantphys.umu.se
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btp149
PMCID: PMC2677742  PMID: 19289446
10.  PROTEIN STRUCTURE PREDICTION CENTER IN CASP8 
Proteins  2009;77(Suppl 9):5-9.
We present an outline of the Critical Assessment of Protein Structure Prediction (CASP) infrastructure implemented at the University of California, Davis, Protein Structure Prediction Center. The infrastructure supports selection and validation of prediction targets, collection of predictions, standard evaluation of submitted predictions, and presentation of results. The Center also supports information exchange relating to CASP experiments and structure prediction in general. Technical aspects of conducting the CASP8 experiment and relevant statistics are also provided.
doi:10.1002/prot.22517
PMCID: PMC2863353  PMID: 19722263
CASP; protein structure prediction
11.  Protein structure prediction and model quality assessment 
Drug discovery today  2009;14(7-8):386-393.
Protein structures have proven to be a crucial piece of information for biomedical research. Of the millions of currently sequenced proteins only a small fraction is experimentally solved for structure and the only feasible way to bridge the gap between sequence and structure data is computational modeling. Half a century has passed since it was shown that the amino acid sequence of a protein determines its shape, but a method to translate the sequence code reliably into the 3D structure still remains to be developed. This review summarizes modern protein structure prediction techniques with the emphasis on comparative modeling, and describes the recent advances in methods for theoretical model quality assessment.
doi:10.1016/j.drudis.2008.11.010
PMCID: PMC2808711  PMID: 19100336
protein structure prediction; CASP; comparative modeling; model quality assessment
12.  Outcome of a Workshop on Applications of Protein Models in Biomedical Research 
Summary
We describe the proceedings and conclusions from a “Workshop on Applications of Protein Models in Biomedical Research” that was held at University of California at San Francisco on 11 and 12 July, 2008. At the workshop, international scientists involved with structure modeling explored (i) how models are currently used in biomedical research, (ii) what the requirements and challenges for different applications are, and (iii) how the interaction between the computational and experimental research communities could be strengthened to advance the field.
doi:10.1016/j.str.2008.12.014
PMCID: PMC2739730  PMID: 19217386
13.  A Comprehensive Analysis of the Structure-Function Relationship in Proteins Based on Local Structure Similarity 
PLoS ONE  2009;4(7):e6266.
Background
Sequence similarity to characterized proteins provides testable functional hypotheses for less than 50% of the proteins identified by genome sequencing projects. With structural genomics it is believed that structural similarities may give functional hypotheses for many of the remaining proteins.
Methodology/Principal Findings
We provide a systematic analysis of the structure-function relationship in proteins using the novel concept of local descriptors of protein structure. A local descriptor is a small substructure of a protein which includes both short- and long-range interactions. We employ a library of commonly reoccurring local descriptors general enough to assemble most existing protein structures. We then model the relationship between these local shapes and Gene Ontology using rule-based learning. Our IF-THEN rule model offers legible, high resolution descriptions that combine local substructures and is able to discriminate functions even for functionally versatile folds such as the frequently occurring TIM barrel and Rossmann fold. By evaluating the predictive performance of the model, we provide a comprehensive quantification of the structure-function relationship based only on local structure similarity. Our findings are, among others, that conserved structure is a stronger prerequisite for enzymatic activity than for binding specificity, and that structure-based predictions complement sequence-based predictions. The model is capable of generating correct hypotheses, as confirmed by a literature study, even when no significant sequence similarity to characterized proteins exists.
Conclusions/Significance
Our approach offers a new and complete description and quantification of the structure-function relationship in proteins. By demonstrating how our predictions offer higher sensitivity than using global structure, and complement the use of sequence, we show that the presented ideas could advance the development of meta-servers in function prediction.
doi:10.1371/journal.pone.0006266
PMCID: PMC2705683  PMID: 19603073
14.  NEW TOOLS AND EXPANDED DATA ANALYSIS CAPABILITIES AT THE PROTEIN STRUCTURE PREDICTION CENTER 
Proteins  2007;69(Suppl 8):19-26.
We outline the main tasks performed by the Protein Structure Prediction Center in support of the CASP7 experiment and provide a brief review of the major measures used in the automatic evaluation of predictions. We describe in more detail the software developed to facilitate analysis of modeling success over and beyond the available templates and the adopted Java-based tool enabling visualization of multiple structural superpositions between target and several models/templates. We also give an overview of the CASP infrastructure provided by the Center and discuss the organization of the results web pages available through http://predictioncenter.org.
doi:10.1002/prot.21653
PMCID: PMC2656758  PMID: 17705273
CASP infrastructure; protein structure prediction; evaluation methods; SPICE
15.  New tools and expanded data analysis capabilities at the protein structure prediction center 
Proteins  2007;69(S8):19-26.
We outline the main tasks performed by the Protein Structure Prediction Center in support of the CASP7 experiment and provide a brief review of the major measures used in the automatic evaluation of predictions. We describe in more detail the software developed to facilitate analysis of modeling success over and beyond the available templates and the adopted Java-based tool enabling visualization of multiple structural superpositions between target and several models/templates. We also give an overview of the CASP infrastructure provided by the Center and discuss the organization of the results web pages available through http://predictioncenter.org
doi:10.1002/prot.21653
PMCID: PMC2656758  PMID: 17705273
CASP infrastructure; protein structure prediction; evaluation methods; SPICE
16.  Critical assessment of methods of protein structure prediction—Round VII 
Proteins  2007;69(Suppl 8):3-9.
This paper is an introduction to the supplemental issue of the journal PROTEINS, dedicated to the seventh CASP experiment to assess the state of the art in protein structure prediction. The paper describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Highlights are improvements in model accuracy relative to that obtainable from knowledge of a single best template structure; convergence of the accuracy of models produced by automatic servers toward that produced by human modeling teams; the emergence of methods for predicting the quality of models; and rapidly increasing practical applications of the methods.
doi:10.1002/prot.21767
PMCID: PMC2653632  PMID: 17918729
protein structure prediction; community wide experiment; CASP
17.  Critical assessment of methods of protein structure prediction—Round VII 
Proteins  2007;69(S8):3-9.
This paper is an introduction to the supplemental issue of the journal PROTEINS, dedicated to the seventh CASP experiment to assess the state of the art in protein structure prediction. The paper describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Highlights are improvements in model accuracy relative to that obtainable from knowledge of a single best template structure; convergence of the accuracy of models produced by automatic servers toward that produced by human modeling teams; the emergence of methods for predicting the quality of models; and rapidly increasing practical applications of the methods.
doi:10.1002/prot.21767
PMCID: PMC2653632  PMID: 17918729
protein structure prediction; community wide experiment; CASP
18.  Using local gene expression similarities to discover regulatory binding site modules 
BMC Bioinformatics  2006;7:505.
Background
We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to relate the combinations of transcription factor binding sites (also referred to as binding site modules) identified in gene promoters to the expression of these genes. The novel aspects include local expression similarity clustering and an exact IF-THEN rule inference algorithm. We also provide a method of rule generalization to include genes with unknown expression profiles.
Results
We have implemented the proposed framework and tested it on publicly available datasets from yeast S. cerevisae. The testing procedure consists of thorough statistical analyses of the groups of genes matching the rules we infer from expression data against known sets of co-regulated genes. For this purpose we have used published ChIP-Chip data and Gene Ontology annotations. In order to make these tests more objective we compare our results with recently published similar studies.
Conclusion
Results we obtain show that local expression similarity clustering greatly enhances overall quality of the derived rules, both in terms of enrichment of Gene Ontology functional annotation and coherence with ChIP-Chip binding data. Our approach thus provides reliable hypotheses on co-regulation that can be experimentally verified. An important feature of the method is its reliance only on widely accessible sequence and expression data. The same procedure can be easily applied to other microbial organisms.
doi:10.1186/1471-2105-7-505
PMCID: PMC2001304  PMID: 17109764

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