A web server to locate periodicities in a sequence

Summary : FT is a tool written in C++, which implements the Fourier analysis method to locate periodicities in aminoacid or DNA sequences. It is provided for free public use on a WWW server with a Java interface. Availability : The server address is http://o2.db. uoa.gr/FT Contact : shamodr@atlas.uoa.gr      

iLIR: A web resource for prediction of Atg8-family interacting proteins

Macroautophagy was initially considered to be a nonselective process for bulk breakdown of cytosolic material. However, recent evidence points toward a selective mode of autophagy mediated by the so-called selective autophagy receptors (SARs). SARs act by recognizing and sorting diverse cargo substrates (e.g., proteins, organelles, pathogens) to the autophagic machinery. Known SARs are characterized by a short linear sequence motif (LIR-, LRS-, or AIM-motif) responsible for the interaction between SARs and proteins of the Atg8 family. Interestingly, many LIR-containing proteins (LIRCPs) are also involved in autophagosome formation and maturation and a few of them in regulating signaling pathways. Despite recent research efforts to experimentally identify LIRCPs, only a few dozen of this class of—often unrelated—proteins have been characterized so far using tedious cell biological, biochemical, and crystallographic approaches. The availability of an ever-increasing number of complete eukaryotic genomes provides a grand challenge for characterizing novel LIRCPs throughout the eukaryotes. Along these lines, we developed iLIR, a freely available web resource, which provides in silico tools for assisting the identification of novel LIRCPs. Given an amino acid sequence as input, iLIR searches for instances of short sequences compliant with a refined sensitive regular expression pattern of the extended LIR motif (xLIR-motif) and retrieves characterized protein domains from the SMART database for the query. Additionally, iLIR scores xLIRs against a custom position-specific scoring matrix (PSSM) and identifies potentially disordered subsequences with protein interaction potential overlapping with detected xLIR-motifs. Here we demonstrate that proteins satisfying these criteria make good LIRCP candidates for further experimental verification. Domain architecture is displayed in an informative graphic, and detailed results are also available in tabular form. We anticipate that iLIR will assist with elucidating the full complement of LIRCPs in eukaryotes.     

CoPreTHi: a Web tool which combines transmembrane protein segment prediction methods

CoPreTHi is a Java based web application, which combines the results of methods that predict the location of transmembrane segments in protein sequences into a joint prediction histogram. Clearly, the joint prediction algorithm, produces superior quality results than individual prediction schemes. The program is available at http://o2.db.uoa.gr/CoPreTHi.     

A comparative study on filtering protein secondary structure prediction

Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement.     

LaTcOm: a web server for visualizing rare codon clusters in coding sequences

We present LaTcOm, a new web tool, which offers several alternative methods for 'rare codon cluster' (RCC) identification from a single and simple graphical user interface. In the current version, three RCC detection schemes are implemented: the recently described %MinMax algorithm and a simplified sliding window approach, along with a novel modification of a linear-time algorithm for the detection of maximally scoring subsequences tailored to the RCC detection problem. Among a number of user tunable parameters, several codon-based scales relevant for RCC detection are available, including tRNA abundance values from Escherichia coli and several codon usage tables from a selection of genomes. Furthermore, useful scale transformations may be performed upon user request (e.g. linear, sigmoid). Users may choose to visualize RCC positions within the submitted sequences either with graphical representations or in textual form for further processing. AVAILABILITY: LaTcOm is freely available online at the URL http://troodos.biol.ucy.ac.cy/latcom.html.     

Homology modeling, simulation and molecular docking studies of catechol-2, 3-Dioxygenase from Burkholderia cepacia: Involved in degradation of Petroleum hydrocarbons

Catechol 2, 3-dioxygenase is present in several types of bacteria and undergoes degradation of environmental pollutants through an important key biochemical pathways. Specifically, this enzyme cleaves aromatic rings of several environmental pollutants such as toluene, xylene, naphthalene and biphenyl derivatives. Hence, the importance of Catechol 2, 3-dioxygenase and its role in the degradation of environmental pollutants made us to predict the three-dimensional structure of Catechol 2, 3-dioxygenase from Burkholderia cepacia. The 10ns molecular dynamics simulation was carried out to check the stability of the modeled Catechol 2, 3- dioxygenase. The results show that the model was energetically stable, and it attains their equilibrium within 2000 ps of production MD run. The docking of various petroleum hydrocarbons into the Catechol 2,3-dioxygenase reveals that the benzene, O-xylene, Toluene, Fluorene, Naphthalene, Carbazol, Pyrene, Dibenzothiophene, Anthracene, Phenanthrene, Biphenyl makes strong hydrogen bond and Van der waals interaction with the active site residues of H150, L152, W198, H206, H220, H252, I254, T255, Y261, E271, L276 and F309. Free energy of binding and estimated inhibition constant of these compounds demonstrates that they are energetically stable in their binding cavity. Chrysene shows positive energy of binding in the active site atom of Fe. Except Pyrene all the substrates made close contact with Fe atom by the distance ranges from 1.67 to 2.43 Å. In addition to that, the above mentioned substrate except pyrene all other made π-π stacking interaction with H252 by the distance ranges from 3.40 to 3.90 Å. All these docking results reveal that, except Chrysene all other substrate has good free energy of binding to hold enough in the active site and makes strong VdW interaction with Catechol-2,3-dioxygenase. These results suggest that, the enzyme is capable of catalyzing the above-mentioned substrate.     

PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications.

A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the avoidance of data overfitting. Capturing information from as few as 50 protein sequences spread among the four target classes (6 transmembrane, 10 fibrous, 13 globular, and 17 mixed), PRED-CLASS was able to obtain 371 correct predictions out of a set of 387 proteins (success rate approximately 96%) unambiguously assigned into one of the target classes. The application of PRED-CLASS to several test sets and complete proteomes of several organisms demonstrates that such a method could serve as a valuable tool in the annotation of genomic open reading frames with no functional assignment or as a preliminary step in fold recognition and ab initio structure prediction methods. Detailed results obtained for various data sets and completed genomes, along with a web sever running the PRED-CLASS algorithm, can be accessed over the World Wide Web at http://o2.biol.uoa.gr/PRED-CLASS.