John Moult

Critical assessment of methods of protein structure prediction (CASP)—Round 6

This article is an introduction to the special issue of the journal PROTEINS, dedicated to the ninth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article 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. CASP 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. Proteins 2011;

CAPRI: A Critical Assessment of PRedicted Interactions

CAPRI is a communitywide experiment to assess the capacity of protein‐docking methods to predict protein–protein interactions. Nineteen groups participated in rounds 1 and 2 of CAPRI and submitted blind structure predictions for seven protein–protein complexes based on the known structure of the component proteins. The predictions were compared to the unpublished X‐ray structures of the complexes. We describe here the motivations for launching CAPRI, the rules that we applied to select targets and run the experiment, and some conclusions that can already be drawn. The results stress the need for new scoring functions and for methods handling the conformation changes that were observed in some of the target systems. CAPRI has already been a powerful drive for the community of computational biologists who development docking algorithms. We hope that this issue of Proteins will also be of interest to the community of structural biologists, which we call upon to provide new targets for future rounds of CAPRI, and to all molecular biologists who view protein–protein recognition as an essential process. Proteins 2003;52:2–9.

SNPs3D: Candidate gene and SNP selection for association studies

BackgroundThe relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level.DescriptionThe resource http://www.SNPs3D.org has three primary modules. One module identifies which genes are candidates for involvement in a specified disease. A second module provides information about the relationships between sets of candidate genes. The third module analyzes the likely impact of non-synonymous SNPs on protein function. Disease/candidate gene relationships and gene-gene relationships are derived from the literature using simple but effective text profiling. SNP/protein function relationships are derived by two methods, one using principles of protein structure and stability, the other based on sequence conservation. Entries for each gene include a number of links to other data, such as expression profiles, pathway context, mouse knockout information and papers. Gene-gene interactions are presented in an interactive graphical interface, providing rapid access to the underlying information, as well as convenient navigation through the network. Use of the resource is illustrated with aspects of the inflammatory response and hypertension.ConclusionThe combination of SNP impact analysis, a knowledge based network of gene relationships and candidate genes, and access to a wide range of data and literature allow a user to quickly assimilate available information, and so develop models of gene-pathway-disease interaction.

Completeness in structural genomics

Structural genomics has the goal of obtaining useful, three-dimensional models of all proteins by a combination of experimental structure determination and comparative model building. We evaluate different strategies for optimizing information return on effort. The strategy that maximizes structural coverage requires about seven times fewer structure determinations compared with the strategy in which targets are selected at random. With a choice of reasonable model quality and the goal of 90% coverage, we extrapolate the estimate of the total effort of structural genomics. It would take ∼16,000 carefully selected structure determinations to construct useful atomic models for the vast majority of all proteins. In practice, unless there is global coordination of target selection, the total effort will likely increase by a factor of three. The task can be accomplished within a decade provided that selection of targets is highly coordinated and significant funding is available.

Critical assessment of methods of protein structure prediction—Round VII

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. Proteins 2007.

Processing and Analysis of CASP3 Protein Structure Predictions

Livermore Prediction Center provides basic infrastructure for the CASP (Critical Assessment of Structure Prediction) experiments, including prediction processing and verification servers, a system of prediction evaluation tools, and interactive numerical and graphical displays. Here we outline the essentials of our approach, with discussion of the superposition procedures, definitions of basic measures, and descriptions of new methods developed to analyze predictions. Our primary focus is on the evaluation of threedimensional models and secondary structure predictions. To put the results of the three prediction experiments held to date on the same footing, the latest CASP3 evaluation criteria were retrospectively applied to both CASP1 and CASP2 predictions. Finally, we give an overview of our website (http://PredictionCenter.llnl.gov), which makes the target structures, predictions, and the evaluation system accessible to the community. Proteins Suppl 1999;3:22–29. Published 1999 Wiley‐Liss, Inc.

Critical assessment of methods of protein structure prediction (CASP) - round x: Critical Assessment of Structure Prediction

This article is an introduction to the special issue of the journal PROTEINS, dedicated to the tenth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. The 10 CASP experiments span almost 20 years of progress in the field of protein structure modeling, and there have been enormous advances in methods and model accuracy in that period. Notable in this round is the first sustained improvement of models with refinement methods, using molecular dynamics. For the first time, we tested the ability of modeling methods to make use of sparse experimental three‐dimensional contact information, such as may be obtained from new experimental techniques, with encouraging results. On the other hand, new contact prediction methods, though holding considerable promise, have yet to make an impact in CASP testing. The nature of CASP targets has been changing in recent CASPs, reflecting shifts in experimental structural biology, with more irregular structures, more multi‐domain and multi‐subunit structures, and less standard versions of known folds. When allowance is made for these factors, we continue to see steady progress in the overall accuracy of models, particularly resulting from improvement of non‐template regions. Proteins 2014; 82(Suppl 2):1–6.

Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment — GPCR Dock 2008 — was conducted in coordination with the publication of the crystal structure of the human adenosine A2A receptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops.

Progress over the first decade of CASP experiments.

CASP has now completed a decade of monitoring the state of the art in protein structure prediction. The quality of structure models produced in the latest experiment, CASP6, has been compared with that in earlier CASPs. Significant although modest progress has again been made in the fold recognition regime, and cumulatively, progress in this area is impressive. Models of previously unknown folds again appear to have modestly improved, and several mixed α/β structures have been modeled in a topologically correct manner. Progress remains hard to detect in high sequence identity comparative modeling, but server performance in this area has moved forward. Proteins 2005;61:225–236.

Evaluation of disorder predictions in CASP9

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 receiver 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. Proteins 2011;.