MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.

Motivation: Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage.

Zinc-induced self-association of complement C3b and Factor H: implications for inflammation and age-related macular degeneration.

The sub-retinal pigment epithelial deposits that are a hallmark of age-related macular degeneration contain both C3b and millimolar levels of zinc. C3 is the central protein of complement, whereas C3u is formed by the spontaneous hydrolysis of the thioester bridge in C3. During activation, C3 is cleaved to form active C3b, then C3b is inactivated by Factor I and Factor H to form the C3c and C3d fragments.

FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins.

Background: The accurate prediction of ligand binding residues from amino acid sequences is important for the automated functional annotation of novel proteins. In the previous two CASP experiments, the most successful methods in the function prediction category were those which used structural superpositions of 3D models and related templates with bound ligands in order to identify putative contacting residues. However, whilst most of this prediction process can be automated, visual inspection and manual adjustments of parameters, such as the distance thresholds used for each target, have often been required to prevent over prediction.

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models.

The binding site distance test score: a robust method for the assessment of predicted protein binding sites.

Motivation: We propose a novel method for scoring the accuracy of protein binding site predictions-the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community-wide prediction experiment-CASP8. While being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site.