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1.  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
2.  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
3.  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
4.  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
5.  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
6.  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
7.  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
8.  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
9.  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
10.  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
11.  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
12.  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
13.  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
14.  Functional characterization of Ape1 variants identified in the human population 
Nucleic Acids Research  2000;28(20):3871-3879.
Apurinic/apyrimidinic (AP) sites are common mutagenic and cytotoxic DNA lesions. Ape1 is the major human repair enzyme for abasic sites and incises the phosphodiester backbone 5′ to the lesion to initiate a cascade of events aimed at removing the AP moiety and maintaining genetic integrity. Through resequencing of genomic DNA from 128 unrelated individuals, and searching published reports and sequence databases, seven amino acid substitution variants were identified in the repair domain of human Ape1. Functional characterization revealed that three of the variants, L104R, E126D and R237A, exhibited ∼40–60% reductions in specific incision activity. A fourth variant, D283G, is similar to the previously characterized mutant D283A found to exhibit ∼10% repair capacity. The most common substitution (D148E; observed at an allele frequency of 0.38) had no impact on endonuclease and DNA binding activities, nor did a G306A substitution. A G241R variant showed slightly enhanced endonuclease activity relative to wild-type. In total, four of seven substitutions in the repair domain of Ape1 imparted reduced function. These reduced function variants may represent low penetrance human polymorphisms that associate with increased disease susceptibility.
PMCID: PMC110798  PMID: 11024165

Results 1-14 (14)