IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/

Retention time prediction and protein identification

Proteins are commonly identified through enzymatic digestion and generation of short sequence tags or fingerprints of peptide masses by mass spectrometry. Separation methods, such as liquid chromatography and electrophoresis, are often used to fractionate complex protein or peptide mixtures and these separations also provide information on the different species, such as molecular weight and isoelectric point from electrophoresis and hydrophobicity in reversed-phase chromatography. These are also properties that can be predicted from amino acid sequences derived from genomic sequences and used in protein identification. This chapter reviews recently introduced methods based on retention time prediction to extract information from chromatographic separations and the applications to protein identification in organisms with small and large genomes. Novel data on retention time prediction of posttranslationally modified peptides is also presented.

The timing of eukaryotic evolution: Does a relaxed molecular clock reconcile proteins and fossils?

The use of nucleotide and amino acid sequences allows improved understanding of the timing of evolutionary events of life on earth. Molecular estimates of divergence times are, however, controversial and are generally much more ancient than suggested by the fossil record. The limited number of genes and species explored and pervasive variations in evolutionary rates are the most likely sources of such discrepancies. Here we compared concatenated amino acid sequences of 129 proteins from 36 eukaryotes to determine the divergence times of several major clades, including animals, fungi, plants, and various protists. Due to significant variations in their evolutionary rates, and to handle the uncertainty of the fossil record, we used a Bayesian relaxed molecular clock simultaneously calibrated by six paleontological constraints. We show that, according to 95% credibility intervals, the eukaryotic kingdoms diversified 950-1,259 million years ago (Mya), animals diverged from choanoflagellates 761-957 Mya, and the debated age of the split between protostomes and deuterostomes occurred 642-761 Mya. The divergence times appeared to be robust with respect to prior assumptions and paleontological calibrations. Interestingly, these relaxed clock time estimates are much more recent than those obtained under the assumption of a global molecular clock, yet bilaterian diversification appears to be approximate to100 million years more ancient than the Cambrian boundary.

Antimicrobial peptide-lipid binding interactions and binding selectivity

Surface pressure measurements, external reflection- Fourier transform infrared spectroscopy, and neutron re. flectivity have been used to investigate the lipid-binding behavior of three antimicrobial peptides: melittin, magainin II, and cecropin P1. As expected, all three cationic peptides were shown to interact more strongly with the anionic lipid, 1,2 dihexadecanoyl-sn-glycerol3-( phosphor-rac-( 1- glycerol)) ( DPPG), compared to the zwitterionic lipid, 1,2 dihexadecanoyl-sn-glycerol-3-phosphocholine ( DPPC). All three peptides have been shown to penetrate DPPC lipid layers by surface pressure, and this was confirmed for the melittin-DPPC interaction by neutron reflectivity measurements. Adsorption of peptide was, however, minimal, with a maximum of 0.4 mg m(-2) seen for melittin adsorption compared to 2.1 mg m(-2) for adsorption to DPPG ( from 0.7 mu M solution). The mode of binding to DPPG was shown to depend on the distribution of basic residues within the peptide alpha-helix, although in all cases adsorption below the lipid layer was shown to dominate over insertion within the layer. Melittin adsorption to DPPG altered the lipid layer structure observed through changes in the external reflection-Fourier transform infrared lipid spectra and neutron reflectivity. This lipid disruption was not observed for magainin or cecropin. In addition, melittin binding to both lipids was shown to be 50% greater than for either magainin or cecropin. Adsorption to the bare air-water interface was also investigated and surface activity followed the trend melittin. magainin. cecropin. External re. ection- Fourier transform infrared amide spectra revealed that melittin adopted a helical structure only in the presence of lipid, whereas magainin and cecropin adopted helical structure also at an airwater interface. This behavior has been related to the different charge distributions on the peptide amino acid sequences.

Predicting protein structures and structural annotation of proteomes

Protein structure prediction methods aim to predict the structures of proteins from their amino acid sequences, utilizing various computational algorithms. Structural genome annotation is the process of attaching biological information to every protein encoded within a genome via the production of three-dimensional protein models.

Use of synthetic CaV2.2 Ca2+ channel peptides to study presynaptic function

Small, synthetic peptides based on specific regions of voltage-gated Ca2+ channels (VGCCs) have been widely used to study Ca2+ channel function and have been instrumental in confirming the contribution of specific amino acid sequences to interactions with putative binding partners. In particular, peptides based on the Ca2+ channel Alpha Interaction Domain (AID) on the intracellular region connecting domains I and II (the I-II loop) and the SYNaptic PRotein INTerction (synprint) site on the II-III loop have been widely used. Emerging evidence suggests that such peptides may themselves possess inherent functionality, a property that may be exploitable for future drug design. Here, we review our recent work using synthetic Ca2+ channel peptides based on sequences within the CaV2.2 amino terminal and I-II loop, originally identified as molecular determinates for G protein modulation, and their effects on VGCC function. These CaV2.2 peptides act as inhibitory modules to decrease Ca2+ influx with direct effects on VGCC gating, ultimately leading to a reduction of synaptic transmission. CaV2.2 peptides also attenuate G protein modulation of VGCCs. Amino acid substitutions generate CaV2.2 peptides with increased or decreased inhibitory effects suggesting that synthetic peptides can be used to further probe VGCC function and, potentially, form the basis for novel therapeutic development.

Secondary structure analysis of the dissimilatory sulphite reductase in Desulfovibrio desulfuricans

The complete sequences of the dsrA and dsrB genes coding for the α− and β−subunits, respectively, of the sulphite reductase enzyme in Desulfovibrio desulfuricans were determined. Analyses of the amino acid sequences indicated a number of serohaem/Fe4S4 binding consensus sequences whilst predictive secondary structure analysis revealed a similar pattern of α−helix and β−strand structures between the two subunits which was indicative of gene duplication.

Lipopeptides: from self-assembly to bioactivity

This Feature Article discusses several classes of lipopeptide with important biomedical applications as antimicrobial and antifungal agents, in immune therapies and in personal care applications among others. Two main classes of lipopeptide are considered: (i) bacterially-expressed lipopeptides with a cyclic peptide headgroup and (ii) linear lipopeptides (with one or more lipid chains) based on bio-derived and bio-inspired amino acid sequences with current clinical applications. The applications are briefly summarized, and the biophysical characterization of the molecules is reviewed, with a particular focus on self-assembly. For several of these types of biomolecule, the formation of micelles above a critical micelle concentration has been observed while others form bilayer structures, depending on conditions of pH and temperature. As yet, there are few studies on the possible relationship between self-assembly into structures such as micelles and bioactivity of this class of molecule although this is likely to attract further attention.

alpha-Aminoisobutyric acid modified protected analogues of beta-amyloid residue 17-20: a change from sheet to helix

The strong intermolecular interactions mediated by short hydrophobic sequences (e.g., 17-20, -L-Leu-L-Val-L-Phe-L-Phe-) in the middle of A beta are known to play a crucial role in the neuropathology of Alzheimer's disease. FTIR, TEM and Congo red binding studies indicated that a series of L-Ala substituted terminally protected peptides related to the sequence 17-20 of the beta-amyloid peptide, adopted D-sheet conformations. However, the Aib-modified analogues disrupt the D-sheet structure and switch over to a 310 helix with increasing number of Aib residues. X-ray crystallography shed some light on the change from sheet to helix at atomic resolution. (c) 2006 Elsevier Ltd. All rights reserved.

Complex history of a chromosomal paralogy region: insights from amphioxus aromatic amino acid hydroxylase genes and insulin-related genes

Aromatic amino acid hydroxylase (AAAH) genes and insulin-like genes form part of an extensive paralogy region shared by human chromosomes 11 and 12, thought to have arisen by tetraploidy in early vertebrate evolution. Cloning of a complementary DNA (cDNA) for an amphioxus (Branchiostoma floridae) hydroxylase gene (AmphiPAH) allowed us to investigate the ancestry of the human chromosome 11/12 paralogy region. Molecular phylogenetic evidence reveals that AmphiPAH is orthologous to vertebrate phenylalanine (PAH) genes; the implication is that all three vertebrate AAAH genes arose early in metazoan evolution, predating vertebrates. In contrast, our phylogenetic analysis of amphioxus and vertebrate insulin-related gene sequences is consistent with duplication of these genes during early chordate ancestry. The conclusion is that two tightly linked gene families on human chromosomes 11 and 12 were not duplicated coincidentally. We rationalize this paradox by invoking gene loss in the AAAH gene family and conclude that paralogous genes shared by paralogous chromosomes need not have identical evolutionary histories.

Rapid protein domain assignment from amino acid sequence using predicted secondary structure

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed