Classifier ensembles for protein structural class prediction with varying homology

Structural class characterizes the overall folding type of a protein or its domain. A number of computational methods have been proposed to predict structural class based on primary sequences; however, the accuracy of these methods is strongly affected by sequence homology. This paper proposes, an ensemble classification method and a compact feature-based sequence representation. This method improves prediction accuracy for the four main structural classes compared to competing methods, and provides highly accurate predictions for sequences of widely varying homologies. The experimental evaluation of the proposed method shows superior results across sequences that are characterized by entire homology spectrum, ranging from 25% to 90% homology. The error rates were reduced by over 20% when compared with using individual prediction methods and most commonly used composition vector representation of protein sequences. Comparisons with competing methods on three large benchmark datasets consistently show the superiority of the proposed method.     

Copper(II) complexes of Neobelliera Bullata Trypsin Modulating Oostatic Factor and its analogues

The stoichiometry, stability constants and solution structure of the complexes formed in the reaction of copper(II) with hexapeptide NPTNLH, i.e. the Neobelliera Bullata Trypsin Modulating Oostatic Factor (Neb-TMOF), and its analogues DPTNLH, Ac-NPTNLH and Ac-DPTNLH have been determined by potentiometric, UV-visible, CD and EPR spectroscopic methods. Upon raising pH for Ac-NPTNLH and Ac-DPTNLH peptides, copper(II) coordination starts from the imidazole nitrogen of the His⁶; afterwards three deprotonated amide nitrogens are progressively involved in metal ions coordination. In a wide pH range of 4.5-8.5 for the NPTNLH and DPTNLH ligands the CuL complex dominates with the imidazole nitrogen of His⁶ coordinated to form a macrochelate. The N-terminal amino group of the NPTNLH and DPTNLH peptides takes part in the coordination of the metal ion in the CuL, CuH₋₁L and CuH₋₂L complexes. However, at pH above 9 the CuH₋₃L complex with the {N_Im, 3N⁻} coordination mode is formed. For the CuH₋₂L complex the spectroscopic data clearly indicate the 4N {NH₂, CO or COO⁻, 2N⁻, N_Im} bonding mode with the axial coordination of the N-terminal amine group to the metal ion.     

Suppressor of Cytokine Signaling (SOCS) 5 Utilises Distinct Domains for Regulation of JAK1 and Interaction with the Adaptor Protein Shc-1

Suppressor of Cytokine Signaling (SOCS)5 is thought to act as a tumour suppressor through negative regulation of JAK/STAT and epidermal growth factor (EGF) signaling. However, the mechanism/s by which SOCS5 acts on these two distinct pathways is unclear. We show for the first time that SOCS5 can interact directly with JAK via a unique, conserved region in its N-terminus, which we have termed the JAK interaction region (JIR). Co-expression of SOCS5 was able to specifically reduce JAK1 and JAK2 (but not JAK3 or TYK2) autophosphorylation and this function required both the conserved JIR and additional sequences within the long SOCS5 N-terminal region. We further demonstrate that SOCS5 can directly inhibit JAK1 kinase activity, although its mechanism of action appears distinct from that of SOCS1 and SOCS3. In addition, we identify phosphoTyr317 in Shc-1 as a high-affinity substrate for the SOCS5-SH2 domain and suggest that SOCS5 may negatively regulate EGF and growth factor-driven Shc-1 signaling by binding to this site. These findings suggest that different domains in SOCS5 contribute to two distinct mechanisms for regulation of cytokine and growth factor signaling.     

Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models

Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.     

Biophotonic markers of malignancy: Discriminating cancers using wavelength-specific biophotons

Early detection is a critically important factor when successfully diagnosing and treating cancer. Whereas contemporary molecular techniques are capable of identifying biomarkers associated with cancer, surgical interventions are required to biopsy tissue. The common imaging alternative, positron-emission tomography (PET), involves the use of nuclear material which poses some risks. Novel, non-invasive techniques to assess the degree to which tissues express malignant properties are now needed. Recent developments in biophoton research have made it possible to discriminate cancerous cells from normal cells both in vitro and in vivo. The current study expands upon a growing body of literature where we classified and characterized malignant and non-malignant cell types according to their biophotonic activity. Using wavelength-exclusion filters, we demonstrate that ratios between infrared and ultraviolet photon emissions differentiate cancer and non-cancer cell types. Further, we identified photon sources associated with three filters (420-nm, 620-nm., and 950-nm) which classified cancer and non-cancer cell types. The temporal increases in biophoton emission within these wavelength bandwidths is shown to be coupled with intrisitic biomolecular events using Cosic's resonant recognition model. Together, the findings suggest that the use of wavelength-exclusion filters in biophotonic measurement can be employed to detect cancer in vitro.     

The MiSink Plugin: Cytoscape as a graphical interface to the Database of Interacting Proteins

The MiSink Plugin converts Cytoscape, an open-source bioinformatics platform for network visualization, to a graphical interface for the database of interacting proteins (DIP: http://dip.doe-mbi.ucla.edu). Seamless integration is possible by providing bi-directional communication between Cytoscape and any Web site supplying data in XML or tab-delimited format. Availability: MiSink is freely available for download at http://dip.doe-mbi.ucla.edu/Software.cgi.     

Suppurative thyroiditis caused by Salmonella enteritidis

Bacterial thyroiditis is a rare disease, and one of which the clinical symptoms and signs are frequently misleading. On the other hand, prompt diagnosis is crucial for successful treatment. We report the case of an 82 year-old man with diabetes mellitus type 2 and a history of steroid treatment who presented with severe odynophagia and dysphagia associated with fever, chills, sore throat and right ear pain. Based on the clinical picture, radiological studies, thyroid cytology, blood and thyroid aspirate culture, suppurative thyroiditis caused by Salmonella enteritidis was diagnosed. The patient was successfully treated with antibiotics and surgical drainage.