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      In silico functional elucidation of uncharacterized proteins of Chlamydia abortus strain LLG

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          Abstract

          Aim:

          This study reports structural modeling, molecular dynamics profiling of hypothetical proteins in Chlamydia abortus genome database.

          Methodology:

          The hypothetical protein sequences were extracted from C. abortus LLG Genome Database for functional elucidation using in silico methods.

          Results:

          Fifty-one proteins with their roles in defense, binding and transporting other biomolecules were unraveled. Forty-five proteins were found to be nonhomologous to proteins present in hosts infected by C. abortus. Of these, 31 proteins were related to virulence. The structural modeling of two proteins, first, WP_006344020.1 (phosphorylase) and second, WP_006344325.1 (chlamydial protease/proteasome-like activity factor) were accomplished. The conserved active sites necessary for the catalytic function were analyzed.

          Conclusion:

          The finally concluded proteins are envisioned as possible targets for developing drugs to curtail chlamydial infections, however, and should be validated by molecular biological methods.

          Lay abstract

          Sequencing technologies have generated abundant data on genome and proteins of an organism. The hypothetical proteins are those whose existence is predicted by computational analysis of genes or protein sequences, but practical evidence to prove them are lacking. This study predicts functions of hypothetical proteins in Chlamydia abortus by computational and bioinformatics methods, determining their 3D structures by structural genomics, homology modeling with known proteins and annotating possible catalytic sites. These findings may be helpful for evolving strategies to curtail Chlamydia abortus infection.

          Most cited references41

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          Protein Identification and Analysis Tools on the ExPASy Server

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            Prediction of protein subcellular localization.

            Because the protein's function is usually related to its subcellular localization, the ability to predict subcellular localization directly from protein sequences will be useful for inferring protein functions. Recent years have seen a surging interest in the development of novel computational tools to predict subcellular localization. At present, these approaches, based on a wide range of algorithms, have achieved varying degrees of success for specific organisms and for certain localization categories. A number of authors have noticed that sequence similarity is useful in predicting subcellular localization. For example, Nair and Rost (Protein Sci 2002;11:2836-2847) have carried out extensive analysis of the relation between sequence similarity and identity in subcellular localization, and have found a close relationship between them above a certain similarity threshold. However, many existing benchmark data sets used for the prediction accuracy assessment contain highly homologous sequences-some data sets comprising sequences up to 80-90% sequence identity. Using these benchmark test data will surely lead to overestimation of the performance of the methods considered. Here, we develop an approach based on a two-level support vector machine (SVM) system: the first level comprises a number of SVM classifiers, each based on a specific type of feature vectors derived from sequences; the second level SVM classifier functions as the jury machine to generate the probability distribution of decisions for possible localizations. We compare our approach with a global sequence alignment approach and other existing approaches for two benchmark data sets-one comprising prokaryotic sequences and the other eukaryotic sequences. Furthermore, we carried out all-against-all sequence alignment for several data sets to investigate the relationship between sequence homology and subcellular localization. Our results, which are consistent with previous studies, indicate that the homology search approach performs well down to 30% sequence identity, although its performance deteriorates considerably for sequences sharing lower sequence identity. A data set of high homology levels will undoubtedly lead to biased assessment of the performances of the predictive approaches-especially those relying on homology search or sequence annotations. Our two-level classification system based on SVM does not rely on homology search; therefore, its performance remains relatively unaffected by sequence homology. When compared with other approaches, our approach performed significantly better. Furthermore, we also develop a practical hybrid method, which combines the two-level SVM classifier and the homology search method, as a general tool for the sequence annotation of subcellular localization.
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              Type III protein secretion systems in bacterial pathogens of animals and plants.

              C Hueck (1998)
              Various gram-negative animal and plant pathogens use a novel, sec-independent protein secretion system as a basic virulence mechanism. It is becoming increasingly clear that these so-called type III secretion systems inject (translocate) proteins into the cytosol of eukaryotic cells, where the translocated proteins facilitate bacterial pathogenesis by specifically interfering with host cell signal transduction and other cellular processes. Accordingly, some type III secretion systems are activated by bacterial contact with host cell surfaces. Individual type III secretion systems direct the secretion and translocation of a variety of unrelated proteins, which account for species-specific pathogenesis phenotypes. In contrast to the secreted virulence factors, most of the 15 to 20 membrane-associated proteins which constitute the type III secretion apparatus are conserved among different pathogens. Most of the inner membrane components of the type III secretion apparatus show additional homologies to flagellar biosynthetic proteins, while a conserved outer membrane factor is similar to secretins from type II and other secretion pathways. Structurally conserved chaperones which specifically bind to individual secreted proteins play an important role in type III protein secretion, apparently by preventing premature interactions of the secreted factors with other proteins. The genes encoding type III secretion systems are clustered, and various pieces of evidence suggest that these systems have been acquired by horizontal genetic transfer during evolution. Expression of type III secretion systems is coordinately regulated in response to host environmental stimuli by networks of transcription factors. This review comprises a comparison of the structure, function, regulation, and impact on host cells of the type III secretion systems in the animal pathogens Yersinia spp., Pseudomonas aeruginosa, Shigella flexneri, Salmonella typhimurium, enteropathogenic Escherichia coli, and Chlamydia spp. and the plant pathogens Pseudomonas syringae, Erwinia spp., Ralstonia solanacearum, Xanthomonas campestris, and Rhizobium spp.
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                Author and article information

                Journal
                Future Sci OA
                Future Sci OA
                FSO
                Future Science OA
                Future Science Ltd (London, UK )
                2056-5623
                March 2017
                24 January 2017
                : 3
                : 1
                : FSO169
                Affiliations
                [1 ]Centre for Computational Biology & Bioinformatics, Central University of Himachal Pradesh, Shahpur 176206, India
                [2 ]Department of Botany, Punjabi University, Patiala 147002, India
                [3 ]ReGenera Research Group of Aging-Intervention & Montenapoleone Medical Centre, Milano, Italy
                [4 ]Department of Microbiology & Immunology, National Institute of Nutrition, Hyderabad 500007, India
                [5 ]ICAR-Indian Veterinary Research Institute, Regional Station, Palampur 176061, India
                Author notes
                *Author for correspondence: bsbpalampur@ 123456yahoo.co.in

                Authors contributed equally

                Article
                10.4155/fsoa-2016-0066
                5351547
                7812ddc1-0225-41a8-b2e0-730f4ac5802d
                © Birbal Singh

                This work is licensed under a Creative Commons Attribution 4.0 License

                History
                : 15 September 2016
                : 05 December 2016
                Categories
                Research Article

                chlamydia abortus,functional annotation,hypothetical proteins

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