MANIFOLD: protein fold recognition based on secondary structure, sequence similarity and enzyme classification

Human Absorbable MicroRNA Prediction based on an Ensemble Manifold Ranking Model

MicroRNAs, a class of short non-coding RNAs, are able to regulate more than half of human genes and affect many fundamental biological processes. It has been long considered synthesized endogenously until very recent discoveries showing that human can absorb exogenous microRNAs from dietary resources. This finding has raised a challenge scientific question: which exogenous microRNAs can be integrated into human circulation and possibly exert functions in human? Here we present a well-designed ensemble manifold ranking model for identifying human absorbable exogenous miRNAs from 14 common dietary species. Specifically, we have analyzed 4,910 dietary microRNAs with 1,120 features derived based on the microRNA sequence and structure. In total, 70 discriminative features were selected to characterize the circulating microRNAs in human and have been used to infer the possibility of a certain exogenous microRNA getting integrated into human circulation. Finally, 461 dietary microRNAs have been identified as transportable exogenous microRNAs. To assess the performance of our ensemble model, we have validated the top predictions through a milk-feeding study. In addition, 26 microRNAs from two virus species were predicted as transportable and have been validated in two external experiments. The results demonstrate the data-driven computational model is highly promising to study transportable microRNAs while bypassing the complex mechanistic details.

Fly cryptochrome and the visual system

Cryptochromes are flavoproteins, structurally and evolutionarily related to photolyases, that are involved in the development, magnetoreception, and temporal organization of a variety of organisms. Drosophila CRYPTOCHROME (dCRY) is involved in light synchronization of the master circadian clock, and its C terminus plays an important role in modulating light sensitivity and activity of the protein. The activation of dCRY by light requires a conformational change, but it has been suggested that activation could be mediated also by specific "regulators" that bind the C terminus of the protein. This C-terminal region harbors several protein-protein interaction motifs, likely relevant for signal transduction regulation. Here, we show that some functional linear motifs are evolutionarily conserved in the C terminus of cryptochromes and that class III PDZ-binding sites are selectively maintained in animals. A coimmunoprecipitation assay followed by mass spectrometry analysis revealed that dCRY interacts with Retinal Degeneration A (RDGA) and with Neither Inactivation Nor Afterpotential C (NINAC) proteins. Both proteins belong to a multiprotein complex (the Signalplex) that includes visual-signaling molecules. Using bioinformatic and molecular approaches, dCRY was found to interact with Neither Inactivation Nor Afterpotential C through Inactivation No Afterpotential D (INAD) in a light-dependent manner and that the CRY-Inactivation No Afterpotential D interaction is mediated by specific domains of the two proteins and involves the CRY C terminus. Moreover, an impairment of the visual behavior was observed in fly mutants for dCRY, indicative of a role, direct or indirect, for this photoreceptor in fly vision.

Quality assessment of protein model-structures based on structural and functional similarities

Background

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology.

Results

GOBA - Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests.

Conclusions

The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models.

A computational model of the LGI1 protein suggests a common binding site for ADAM proteins

Mutations of human leucine-rich glioma inactivated (LGI1) gene encoding the epitempin protein cause autosomal dominant temporal lateral epilepsy (ADTLE), a rare familial partial epileptic syndrome. The LGI1 gene seems to have a role on the transmission of neuronal messages but the exact molecular mechanism remains unclear. In contrast to other genes involved in epileptic disorders, epitempin shows no homology with known ion channel genes but contains two domains, composed of repeated structural units, known to mediate protein-protein interactions.A three dimensional in silico model of the two epitempin domains was built to predict the structure-function relationship and propose a functional model integrating previous experimental findings. Conserved and electrostatic charged regions of the model surface suggest a possible arrangement between the two domains and identifies a possible ADAM protein binding site in the β-propeller domain and another protein binding site in the leucine-rich repeat domain. The functional model indicates that epitempin could mediate the interaction between proteins localized to different synaptic sides in a static way, by forming a dimer, or in a dynamic way, by binding proteins at different times.The model was also used to predict effects of known disease-causing missense mutations. Most of the variants are predicted to alter protein folding while several other map to functional surface regions. In agreement with experimental evidence, this suggests that non-secreted LGI1 mutants could be retained within the cell by quality control mechanisms or by altering interactions required for the secretion process.

Outer membrane proteins can be simply identified using secondary structure element alignment

Background

Outer membrane proteins (OMPs) are frequently found in the outer membranes of gram-negative bacteria, mitochondria and chloroplasts and have been found to play diverse functional roles. Computational discrimination of OMPs from globular proteins and other types of membrane proteins is helpful to accelerate new genome annotation and drug discovery.

Results

Based on the observation that almost all OMPs consist of antiparallel β-strands in a barrel shape and that their secondary structure arrangements differ from those of other types of proteins, we propose a simple method called SSEA-OMP to identify OMPs using secondary structure element alignment. Through intensive benchmark experiments, the proposed SSEA-OMP method is better than some well-established OMP detection methods.

Conclusions

The major advantage of SSEA-OMP is its good prediction performance considering its simplicity. The web server implements the method is freely accessible at http://protein.cau.edu.cn/SSEA-OMP/index.html.

A study of hierarchical and flat classification of proteins

Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that expert-defined hierarchies of protein classes exist and can potentially be exploited to improve classification performance. In this article, we investigate empirically whether this is the case for two such hierarchies. We compare multiclass classification techniques that exploit the information in those class hierarchies and those that do not, using logistic regression, decision trees, bagged decision trees, and support vector machines as the underlying base learners. In particular, we compare hierarchical and flat variants of ensembles of nested dichotomies. The latter have been shown to deliver strong classification performance in multiclass settings. We present experimental results for synthetic, fold recognition, enzyme classification, and remote homology detection data. Our results show that exploiting the class hierarchy improves performance on the synthetic data but not in the case of the protein classification problems. Based on this, we recommend that strong flat multiclass methods be used as a baseline to establish the benefit of exploiting class hierarchies in this area.

Adding structural information to the von Hippel-Lindau (VHL) tumor suppressor interaction network

The von Hippel-Lindau (VHL) tumor suppressor gene is a protein interaction hub, controlling numerous genes implicated in tumor progression. Here we focus on structural aspects of protein interactions for a list of 35 experimentally verified protein VHL (pVHL) interactors. Using structural information and computational analysis we have located three distinct interaction interfaces (A, B, and C). Interface B is the most versatile, recognizing a refined linear motif present in 17 otherwise non-related proteins. It has been possible to distinguish compatible and exclusive interactions by relating pVHL function to interaction interfaces and subcellular localization. A novel hypothesis is presented regarding the possible function of the N-terminus as an inhibitor of pVHL function.

LGI1 mutations in autosomal dominant and sporadic lateral temporal epilepsy

Autosomal dominant lateral temporal epilepsy (ADLTE) or autosomal dominant partial epilepsy with auditory features (ADPEAF) is an inherited epileptic syndrome with onset in childhood/adolescence and benign evolution. The hallmark of the syndrome consists of typical auditory auras or ictal aphasia in most affected family members. ADTLE/ADPEAF is associated in about half of the families with mutations of the leucine-rich, glioma-inactivated 1 (LGI1) gene. In addition, de novo LGI1 mutations are found in about 2% of sporadic cases with idiopathic partial epilepsy with auditory features, who are clinically similar to the majority of patients with ADLTE/ADPEAF but have no family history. Twenty-five LGI1 mutations have been described in familial and sporadic lateral temporal epilepsy patients. The mutations are distributed throughout the gene and are mostly missense mutations occurring in both the N-terminal leucine rich repeat (LRR) and C-terminal EPTP (beta propeller) protein domains. We show a tridimensional model of the LRR protein region that allows missense mutations of this region to be divided into two distinct groups: structural and functional mutations. Frameshift, nonsense and splice site point mutations have also been reported that result in protein truncation or internal deletion. The various types of mutations are associated with a rather homogeneous phenotype, and no obvious genotype-phenotype correlation can be identified. Both truncating and missense mutations appear to prevent secretion of mutant proteins, suggesting a loss of function effect of mutations. The function of LGI1 is unclear. Several molecular mechanisms possibly leading to lateral temporal epilepsy are illustrated and briefly discussed.

Electric dipole reorientation in the interaction of botulinum neurotoxins with neuronal membranes

Botulinum neurotoxins are highly potent toxins capable of rapid and specific interaction with the presynaptic membrane. We have hypothesised that: (1) these neurotoxins possess an electric dipole with the positive pole on receptor binding domain Hc-C and that (2) on approaching the negatively charged presynaptic membrane, they reorient themselves and hit the membrane surface with Hc-C; this electrostatic effect would contribute efficient binding. Electrostatic calculations confirm these hypotheses and strongly indicate that electrostatics effects can play an important role in the unique presynaptic membrane binding properties of these neurotoxins and generally on the interaction of other plasma membrane protein ligands.

Gamma-glutamyl transferase in the cell wall participates in extracellular glutathione salvage from the root apoplast

The molecular properties and subcellular location of bound gamma-glutamyl transferase (GGT) were studied, and an experimental setup devised to assess its functions in barley roots. Enzyme histochemistry was used to detect GGT activity at tissue level; immunocytochemistry to localize the protein at subcellular level; and modelling studies to investigate its surface charge properties. GGT activity in vivo was measured for the first time. Functions were explored by applying chemical treatments with inhibitors and the thiol-oxidizing drug diamide, performing time-course chromatographic and spectrophotometric analyses on low-molecular-weight thiols. Gamma-glutamyl transferase activity was found to be high in the root apical region and the protein was anchored to root cell wall components, probably by basic amino acid residues. The results show that GGT is essential to the recovery of apoplastic glutathione provided exogenously or extruded by oxidative treatment. It is demonstrated that GGT activity helps to salvage extracellular glutathione and may contribute to redox control of the extracellular environment, thus providing evidence of a functional role for gamma-glutamyl cycle in roots.

Evolutionary and structural insights into the multifaceted glutathione peroxidase (Gpx) superfamily

Glutathione peroxidase (GPx) is a widespread protein superfamily found in many organisms throughout all kingdoms of life. Although it was initially thought to use only glutathione as reductant, recent evidence suggests that the majority of GPxs have specificity for thioredoxin. We present a thorough in silico analysis performed on 724 sequences and 12 structures aimed to clarify the evolutionary, structural, and sequence determinants of GPx specificity. Structural variability was found to be limited to only two regions, termed oligomerization loop and functional helix, which modulate both reduced substrate specificity and oligomerization state. We show that mammalian GPx-1, the canonic selenocysteine-based tetrameric glutathione peroxidase, is a recent "invention" during evolution. Contrary to common belief, cysteine-based thioredoxin-specific GPx, which we propose the TGPx, are both more common and more ancient. This raises interesting evolutionary considerations regarding oligomerization and the use of active-site selenocysteine residue. In addition, phylogenetic analysis has revealed the presence of a novel member belonging to the GPx superfamily in Mammalia and Amphibia, for which we propose the name GPx-8, following the present numeric order of the mammalian GPxs.

Plasmodium possesses dynein light chain classes that are unique and conserved across species

Plasmodium belongs to the phylum Apicomplexa. Within the Apicomplexa, Plasmodium, Toxoplasma and Cryptosporidium are parasites of considerable medical importance while Theileria and Eimeria are animal pathogens. P. falciparum is particularly important as it causes malaria, resulting in more than 1 million deaths each year. The malaria parasite actively invades the host cell in which it propagates and several proteins associated with the apical organelles have been implicated to be crucial in the invasion process. The biogenesis of the apical organelles is not well understood, but several studies indicate that microtubule-based vesicular transport is involved. Vesicular transport proteins are also present in Plasmodium and are presumed to be involved in transcellular transport in infected erythrocytes. Dynein is a multi-subunit motor protein involved in microtubule-based vesicular transport. In this study, we analyzed the cytoplasmic dynein light chains (Dlcs) of P. falciparum since they provide adaptor surface to the cargoes and are likely to be involved in differential transport. Dlcs consist of three different families: TcTex1/2, LC8 and LC7/roadblock. The data presented demonstrate that P. falciparum Dlcs sequences and functional domains show high sequence similarity within the species, but that only the Dlc group 1 (LC8) has a high similarity to human orthologues. TcTex1 and LC7/roadblock have low similarity to human orthologues. This sequence variation could be targeted for vaccine or drug development.

Improving the sensitivity and specificity of protein homology search by incorporating predicted secondary structures

In this paper, we improve the homology search performance by the combination of the predicted protein secondary structures and protein sequences. Previous research suggested that the straightforward combination of predicted secondary structures did not improve the homology search performance, mostly because of the errors in the structure prediction. We solved this problem by taking into account the confidence scores output by the prediction programs.

The victor/FRST function for model quality estimation

Scoring functions are widely used in the final step of model selection in protein structure prediction. This is of interest both for comparative modeling targets, where it is important to select the best model among a set of many good, "correct" ones, as well as for other (fold recognition or novel fold) targets, where the set may contain many incorrect models. A novel combination of four knowledge-based potentials recognizing different features of native protein structures is introduced and tested. The pairwise, solvation, hydrogen bond, and torsion angle potentials contain largely orthogonal information. Of these, the torsion angle potential is found to show the strongest correlation with model quality. Combining these features with a linear weighting function, it was possible to construct a robust energy function capable of discriminating native-like structures on several benchmarking sets. In a recent blind test (CAFASP-4 MQAP), the scoring function ranked consistently well and was able to reliably distinguish the correct template from an ensemble of high quality decoys in 52 of 70 cases (33 of 34 for comparative modeling). An executable version of the Victor/FRST function for Linux PCs is available for download from the URL http://protein.cribi.unipd.it/frst/.

Fold classification based on secondary structure--how much is gained by including loop topology?

Background

It has been proposed that secondary structure information can be used to classify (to some extend) protein folds. Since this method utilizes very limited information about the protein structure, it is not surprising that it has a higher error rate than the approaches that use full 3D fold description. On the other hand, the comparing of 3D protein structures is computing intensive. This raises the question to what extend the error rate can be decreased with each new source of information, especially if the new information can still be used with simple alignment algorithms.

We consider the question whether the information about closed loops can improve the accuracy of this approach. While the answer appears to be obvious, we had to overcome two challenges. First, how to code and to compare topological information in such a way that local alignment of strings will properly identify similar structures. Second, how to properly measure the effect of new information in a large data sample.

We investigate alternative ways of computing and presenting this information.

Results

We used the set of beta proteins with at most 30% pairwise identity to test the approach; local alignment scores were used to build a tree of clusters which was evaluated using a new log-odd cluster scoring function. In particular, we derive a closed formula for the probability of obtaining a given score by chance.Parameters of local alignment function were optimized using a genetic algorithm.

Of 81 folds that had more than one representative in our data set, log-odds scores registered significantly better clustering in 27 cases and significantly worse in 6 cases, and small differences in the remaining cases. Various notions of the significant change or average change were considered and tried, and the results were all pointing in the same direction.

Conclusion

We found that, on average, properly presented information about the loop topology improves noticeably the accuracy of the method but the benefits vary between fold families as measured by log-odds cluster score.

Protein secondary structure prediction with dihedral angles

We present DESTRUCT, a new method of protein secondary structure prediction, which achieves a three-state accuracy (Q3) of 79.4% in a cross-validated trial on a nonredundant set of 513 proteins. An iterative set of cascade-correlation neural networks is used to predict both secondary structure and psi dihedral angles, with predicted values enhancing the subsequent iteration. Predictive accuracies of 80.7% and 81.7% are achieved on the CASP4 and CASP5 targets, respectively. Our approach is significantly more accurate than other contemporary methods, due to feedback and a novel combination of structural representations.

Functional insights from the structural modelling of a small Fe-hydrogenase

Recently, a novel Fe-hydrogenase from a high rate of hydrogen producing Enterobacter cloacae strain IIT-BT08 was identified and partially characterized. This 147 residue protein was found to be much smaller than previously known Fe-hydrogenases, yet retaining a high catalytic activity. We predicted the structure of this protein and found it to be structurally similar to one of the two sub-domains containing the catalytic H-cluster so far jointly present in all other Fe-hydrogenases. This novel architecture allows a tentative explanation of protein function with the high rate of catalytic activity being due to a missing regulatory sub-domain, presumably allowing higher enzymatic activity at the cost of greater exposure to oxygen inactivation. This new insight may improve our understanding of the molecular and functional organization of other, more complex Fe-hydrogenases.

SSEP-Domain: protein domain prediction by alignment of secondary structure elements and profiles

MOTIVATION

The prediction of protein domains is a crucial task for functional classification, homology-based structure prediction and structural genomics. In this paper, we present the SSEP-Domain protein domain prediction approach, which is based on the application of secondary structure element alignment (SSEA) and profile-profile alignment (PPA) in combination with InterPro pattern searches. SSEA allows rapid screening for potential domain regions while PPA provides us with the necessary specificity for selecting significant hits. The combination with InterPro patterns allows finding domain regions without solved structural templates if sequence family definitions exist.

RESULTS

A preliminary version of SSEP-Domain was ranked among the top-performing domain prediction servers in the CASP 6 and CAFASP 4 experiments. Evaluation of the final version shows further improvement over these results together with a significant speed-up.

AVAILABILITY

The server is available at http://www.bio.ifi.lmu.de/SSEP/

Structural insights into the function of human caveolin 1

Caveolin-1 (Cav-1) is emerging as the central protein controlling caveolae formation, caveolae trafficking, and cellular signalling. In particular, it is known that Cav-1 interacts and modulates the activity of several signalling proteins through the so-called caveolin scaffolding domain. In this paper, we used a bioinformatics approach to assess the validity of some long-standing structural features of Cav-1. We could confirm the existence of a membrane spanning region of Cav-1 and highlight an interesting pattern of palmitoylated cysteine residues explaining the structural features of the Cav-1 C-terminal region. Moreover, the scaffolding domain is predicted to have a different structure than previously reported.

The SSEA server for protein secondary structure alignment

SUMMARY

We present a web server that computes alignments of protein secondary structures. The server supports both performing pairwise alignments and searching a secondary structure against a library of domain folds. It can calculate global and local secondary structure element alignments. A combination of local and global alignment steps can be used to search for domains inside the query sequence or help in the discrimination of novel folds. Both the SCOP and PDB fold libraries, clustered at 95 and 40% sequence identity, are available for alignment.

AVAILABILITY

The web server interface is freely accessible to academic users at http://protein.cribi.unipd.it/ssea/. The executable version and benchmarking data are available from the same web page.