CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

<p>Abstract</p> <p>Background</p> <p>The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB), thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm), has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods.</p> <p>Results</p> <p>The evaluation of CMASA shows that the CMASA is highly accurate (0.96), sensitive (0.86), and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function) and SPASM (a local structure alignment method); and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods). The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA).</p> <p>Conclusions</p> <p>The CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the mail-based server (<url>http://159.226.149.45/other1/CMASA/CMASA.htm</url>).</p

Comparison of the marginal adaptation of direct and indirect composite inlay restorations with optical coherence tomography

OBJECTIVE: The purpose of the study was to use the photonic imaging modality of optical coherence tomography (OCT) to compare the marginal adaptation of composite inlays fabricated by direct and indirect techniques. MATERIAL AND METHODS: Class II cavities were prepared on 34 extracted human molar teeth. The cavities were randomly divided into two groups according to the inlay fabrication technique. The first group was directly restored on cavities with a composite (Esthet X HD, Dentsply, Germany) after isolating. The second group was indirectly restored with the same composite material. Marginal adaptations were scanned before cementation with an invisible infrared light beam of OCT (Thorlabs), allowing measurement in 200 µm intervals. Restorations were cemented with a self-adhesive cement resin (SmartCem2, Dentsply), and then marginal adaptations were again measured with OCT. Mean values were statistically compared by using independent-samples t-test and paired samples t-test (p<0.05), before and after cementation. RESULTS: Direct inlays presented statistically smaller marginal discrepancy values than indirect inlays, before (p=0.00001442) and after (p=0.00001466) cementation. Marginal discrepancy values were increased for all restorations after cementation (p=0.00008839, p=0.000000952 for direct and indirect inlays, respectively). The mean marginal discrepancy value of the direct group increased from 56.88±20.04 µm to 91.88±31.7 µm, whereas the indirect group increased from 107.54±35.63 µm to 170.29±54.83 µm. Different techniques are available to detect marginal adaptation of restorations, but the OCT system can give quantitative information about resin cement thickness and its interaction between tooth and restoration in a nondestructive manner. CONCLUSIONS: Direct inlays presented smaller marginal discrepancy than indirect inlays. The marginal discrepancy values were increased for all restorations that refer to cement thickness after cementation

PhosTryp: a phosphorylation site predictor specific for parasitic protozoa of the family trypanosomatidae

<p>Abstract</p> <p>Background</p> <p>Protein phosphorylation modulates protein function in organisms at all levels of complexity. Parasites of the <it>Leishmania </it>genus undergo various developmental transitions in their life cycle triggered by changes in the environment. The molecular mechanisms that these organisms use to process and integrate these external cues are largely unknown. However <it>Leishmania </it>lacks transcription factors, therefore most regulatory processes may occur at a post-translational level and phosphorylation has recently been demonstrated to be an important player in this process. Experimental identification of phosphorylation sites is a time-consuming task. Moreover some sites could be missed due to the highly dynamic nature of this process or to difficulties in phospho-peptide enrichment.</p> <p>Results</p> <p>Here we present PhosTryp, a phosphorylation site predictor specific for trypansomatids. This method uses an SVM-based approach and has been trained with recent <it>Leishmania </it>phosphosproteomics data. PhosTryp achieved a 17% improvement in prediction performance compared with Netphos, a non organism-specific predictor. The analysis of the peptides correctly predicted by our method but missed by Netphos demonstrates that PhosTryp captures <it>Leishmania</it>-specific phosphorylation features. More specifically our results show that <it>Leishmania </it>kinases have sequence specificities which are different from their counterparts in higher eukaryotes. Consequently we were able to propose two possible <it>Leishmania</it>-specific phosphorylation motifs.</p> <p>We further demonstrate that this improvement in performance extends to the related trypanosomatids <it>Trypanosoma brucei </it>and <it>Trypanosoma cruzi</it>. Finally, in order to maximize the usefulness of PhosTryp, we trained a predictor combining all the peptides from <it>L. infantum, T. brucei and T. cruzi</it>.</p> <p>Conclusions</p> <p>Our work demonstrates that training on organism-specific data results in an improvement that extends to related species. PhosTryp is freely available at <url>http://phostryp.bio.uniroma2.it</url></p

The LabelHash algorithm for substructure matching

Background: There is an increasing number of proteins with known structure but unknown function. Determining their function would have a significant impact on understanding diseases and designing new therapeutics. However, experimental protein function determination is expensive and very time-consuming. Computational methods can facilitate function determination by identifying proteins that have high structural and chemical similarity. Results: We present LabelHash, a novel algorithm for matching substructural motifs to large collections of protein structures. The algorithm consists of two phases. In the first phase the proteins are preprocessed in a fashion that allows for instant lookup of partial matches to any motif. In the second phase, partial matches for a given motif are expanded to complete matches. The general applicability of the algorithm is demonstrated with three different case studies. First, we show that we can accurately identify members of the enolase superfamily with a single motif. Next, we demonstrate how LabelHash can complement SOIPPA, an algorithm for motif identification and pairwise substructure alignment. Finally, a large collection of Catalytic Site Atlas motifs is used to benchmark the performance of the algorithm. LabelHash runs very efficiently in parallel; matching a motif against all proteins in the 95 % sequence identity filtered non-redundant Protein Data Bank typically takes no more than a few minutes. The LabelHash algorithm is available through a web server and as a suite of standalone programs a

A Role for TLR4 in Clostridium difficile Infection and the Recognition of Surface Layer Proteins

Clostridium difficile is the etiological agent of antibiotic-associated diarrhoea (AAD) and pseudomembranous colitis in humans. The role of the surface layer proteins (SLPs) in this disease has not yet been fully explored. The aim of this study was to investigate a role for SLPs in the recognition of C. difficile and the subsequent activation of the immune system. Bone marrow derived dendritic cells (DCs) exposed to SLPs were assessed for production of inflammatory cytokines, expression of cell surface markers and their ability to generate T helper (Th) cell responses. DCs isolated from C3H/HeN and C3H/HeJ mice were used in order to examine whether SLPs are recognised by TLR4. The role of TLR4 in infection was examined in TLR4-deficient mice. SLPs induced maturation of DCs characterised by production of IL-12, TNFα and IL-10 and expression of MHC class II, CD40, CD80 and CD86. Furthermore, SLP-activated DCs generated Th cells producing IFNγ and IL-17. SLPs were unable to activate DCs isolated from TLR4-mutant C3H/HeJ mice and failed to induce a subsequent Th cell response. TLR4−/− and Myd88−/−, but not TRIF−/− mice were more susceptible than wild-type mice to C. difficile infection. Furthermore, SLPs activated NFκB, but not IRF3, downstream of TLR4. Our results indicate that SLPs isolated from C. difficile can activate innate and adaptive immunity and that these effects are mediated by TLR4, with TLR4 having a functional role in experimental C. difficile infection. This suggests an important role for SLPs in the recognition of C. difficile by the immune system

Quantitative comparison of catalytic mechanisms and overall reactions in convergently evolved enzymes : implications for classification of enzyme function

The authors thank the National Institutes of Health (NIH R01 GM60595 to PCB) and the Scottish Universities Life Sciences Alliance (SULSA to JBOM) for funding.Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.Publisher PDFPeer reviewe