Relevant bibliographies by topics / Protein structure analysis

Academic literature on the topic 'Protein structure analysis'

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Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Protein structure analysis"

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Schulze-Kremer, Steffen, and Ross D. King. "IPSA—Inductive Protein Structure Analysis." "Protein Engineering, Design and Selection" 5, no. 5 (1992): 377–90. http://dx.doi.org/10.1093/protein/5.5.377.

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Baek, Mihwa, Masakatsu Kamiya, Taichi Nakazumi, Satoshi Tomisawa, Yasuhiro Kumaki, Takashi Kikukawa, Makoto Demura, Keiichi Kawano, and Tomoyasu Aizawa. "3P011 Structural analysis of antimicrobial peptide CP1 with LPS by NMR(01A. Protein: Structure,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S213. http://dx.doi.org/10.2142/biophys.53.s213_5.

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Wang, Zhuo, Yasuo Okuma, Daiske Kasuya, Kaoru Mitsuoka, Yasushi Saeki, and Takuo Yasunaga. "2P010 Structural analysis of the 26S proteasome by cryo-electron microscopy and Single-Particle Analysis(01A. Protein: Structure,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S160. http://dx.doi.org/10.2142/biophys.53.s160_4.

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Presta, Leonard. "Protein structure analysis and development of databases." "Protein Engineering, Design and Selection" 2, no. 6 (1989): 395–97. http://dx.doi.org/10.1093/protein/2.6.395.

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Gray, Peter M. D., Norman W. Paton, Graham J. L. Kemp, and John E. Fothergill. "An object-oriented database for protein structure analysis." "Protein Engineering, Design and Selection" 3, no. 4 (1990): 235–43. http://dx.doi.org/10.1093/protein/3.4.235.

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Nanni, L., S. Mazzara, L. Pattini, and A. Lumini. "Protein classification combining surface analysis and primary structure." Protein Engineering Design and Selection 22, no. 4 (January 10, 2009): 267–72. http://dx.doi.org/10.1093/protein/gzn084.

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Taylor, William R., Jaap Heringa, Franck Baud, and Tomas P. Flores. "A Fourier analysis of symmetry in protein structure." Protein Engineering, Design and Selection 15, no. 2 (February 2002): 79–89. http://dx.doi.org/10.1093/protein/15.2.79.

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Ohta, Emi, Takuya Muto, Yusuke Kishi, Mariko Yamaguchi, takayoshi Watanabe, Yoichi Yamazaki, Hironari Kamikubo, Takahiro Hohsaka, and mikio Kataoka. "3P029 Analysis of unfolded structure of Staphylococcal nuclease mutants by using FRET(01A. Protein: Structure,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S216. http://dx.doi.org/10.2142/biophys.53.s216_5.

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Noble, M. E. M., A. Cleasby, L. N. Johnson, M. R. Egmond, and L. G. J. Frenken. "Analysis of the structure of Pseudomonas glumae lipase." "Protein Engineering, Design and Selection" 7, no. 4 (1994): 559–62. http://dx.doi.org/10.1093/protein/7.4.559.

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Balamurugan, B., M. N. A. Md Roshan, B. Shaahul Hameed, K. Sumathi, R. Senthilkumar, A. Udayakumar, K. H. Venkatesh Babu, et al. "PSAP: protein structure analysis package." Journal of Applied Crystallography 40, no. 4 (July 13, 2007): 773–77. http://dx.doi.org/10.1107/s0021889807021875.

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A computing engine, theProtein Structure Analysis Package(PSAP), has been developed to calculate and display various hidden structural and functional features of three-dimensional protein structures. The proposed computing engine has several utilities to enable structural biologists to analyze three-dimensional protein molecules and provides an easy-to-use Web interface to compute and visualize the necessary features dynamically on the client machine. Users need to provide the Protein Data Bank (PDB) identification code or upload three-dimensional atomic coordinates from the client machine. For visualization, the free molecular graphics programsRasMolandJmolare deployed in the computing engine. Furthermore, the computing engine is interfaced with an up-to-date local copy of the PDB. The atomic coordinates are updated every week and hence users can access all the structures available in the PDB. The computing engine is free and is accessible online at http://iris.physics.iisc.ernet.in/psap/.
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Dissertations / Theses on the topic "Protein structure analysis"

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Pritchard, Leighton. "Evolutionary and structural analysis of protein structure-function relationships." Thesis, University of Strathclyde, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248316.

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Jonsson, Andreas. "Mass spectrometry in protein structure analysis /." Stockholm, 2001. http://diss.kib.ki.se/2001/91-628-4716-3/.

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Copley, Richard Robertson. "Analysis and prediction of protein structure." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361954.

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Boscott, Paul Edmond. "Sequence analysis in protein structure prediction." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386870.

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Hommola, Susan Kerstin. "Categorical data analysis of protein structure." Thesis, University of Leeds, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.578618.

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It has long been known that the amino-acid sequence of a protein determines its 3- dimensional structure, but accurate ab initio prediction of structure from sequence remains elusive. In this thesis, we aim to gain insight into generic principles of protein folding through statistical modelling of protein structure. The first part is concerned with local protein structure. We study the relationship of dihedral angles in short protein segments up to a length of three residues. We adopt a contingency table approach, exploring a targeted set of hypotheses through log-linear modelling to detect patterns of association between the dihedral angles in the segments considered. For segments of length two (dipeptides), our models indicate a substantial association of the side-chain conformation of the first residue with the backbone conformation of the second residue (side-to-back interaction) as well as a weaker, but still significant, associa- tion of the backbone conformation of the first residue with the side-chain conformation of the second residue (back-to-side interaction). Comparison of these interactions across dif- ferent dipeptides through cluster analysis reveals a striking pattern. For the side-to-back term, all dipeptides having the same first residue cluster together, whereas for the back- to-side term we observe a much weaker pattern. This suggests that the conformation of the first residue dictates the conformation of the second. Our categorical approach proves difficult for the analysis of longer segments due to the discrepancy between the increased complexity and the shrinking amount of data available. In the second part, we study non-local interactions represented by contact maps. Our approach focuses entirely on the positions of contacting residues and is completely inde- pendent of protein amino-acid sequence. We investigate and quantify patterns in three specific regions of aggregated contact maps of single-domain proteins belonging to the four major SCOP classes (all-α, all-β, α/β, α+β) using logistic regression models. The first two regions represent contacts of residues aligned to the N-terminus with subsequent residues, and contacts of residues aligned to the C-terminus with previous residues, in a symmetric fashion with respect to the chain termini. The third region contains contacts between terminal residues. The models for each region contain factors for the positions of contacting residues as well as factors describing parallel and anti-parallel β-strand contact patterns. There is an interesting asymmetry between N-aligned and C-aligned contacts for the α/β SCOP class. The region around the -terminus shows a strong propensity towards parallel contacts between the first few residues and residues further along the sequence, whereas the last few residues do not show any strong patterns. This N-terminal dominance could indicate cotranslational folding. The other classes do not exhibit this asymmetry, but reveal predominantly anti-parallel β-strand patterns (all-β class), mixed patterns (α+β class) or no distinct patterns (all-a class). Contact patterns in the terminal regions are generally weak showing no strong preferences towards parallel or anti-parallel f3-strand contacts.
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Michie, Alexander David. "Analysis and classification of protein structure." Thesis, University College London (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267834.

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Elliott, Craig Julian. "Analysis and prediction of protein structure." Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284165.

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Gkolias, Theodoros. "Shape analysis in protein structure alignment." Thesis, University of Kent, 2018. https://kar.kent.ac.uk/66682/.

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In this Thesis we explore the problem of structural alignment of protein molecules using statistical shape analysis techniques. The structural alignment problem can be divided into three smaller ones: the representation of protein structures, the sampling of possible alignments between the molecules and the evaluation of a given alignment. Previous work done in this field, can be divided in two approaches: an adhoc algorithmic approach from the Bioinformatics literature and an approach using statistical methods either in a likelihood or Bayesian framework. Both approaches address the problem from a different scope. For example, the algorithmic approach is easy to implement but lacks an overall modelling framework, and the Bayesian address this issue but sometimes the implementation is not straightforward. We develop a method which is easy to implement and is based on statistical assumptions. In order to asses the quality of a given alignment we use a size and shape likelihood density which is based in the structure information of the molecules. This likelihood density is also extended to include sequence infor- mation and gap penalty parameters so that biologically meaningful solution can be produced. Furthermore, we develop a search algorithm to explore possible alignments from a given starting point. The results suggest that our approach produces better or equal alignments when it is compared to the most recent struc- tural alignment methods. In most of the cases we managed to achieve a higher number of matched atoms combined with a high TMscore. Moreover, we extended our method using Bayesian techniques to perform alignments based on posterior modes. In our approach, we estimate directly the mode of the posterior distribution which provides the final alignment between two molecules. We also, choose a different approach for treating the mean parameter. In previous methods the mean was either integrated out of the likelihood density or considered as fixed. We choose to assign a prior over it and obtain its posterior mode. Finally, we consider an extension of the likelihood model assuming a Normal density for both the matched and unmatched parts of a molecule and diagonal covariance structure. We explore two different variants. In the first we consider a fixed zero mean for the unmatched parts of the molecules and in the second we consider a common mean for both the matched and unmatched parts. Based on simulated and real results, both models seems to perform well in obtaining high number of matched atoms and high TMscore.
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Chivian, Dylan Casey. "Application of information from homologous proteins for the prediction of protein structure /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/9264.

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Betts, Matthew James. "Analysis and prediction of protein-protein recognition." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313795.

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Books on the topic "Protein structure analysis"

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Kamp, Roza Maria, Theodora Choli-Papadopoulou, and Brigitte Wittmann-Liebold, eds. Protein Structure Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5.

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1927-, Jollès Pierre, and Jörnvall Hans, eds. Proteomics in functional genomics: Protein structure analysis. Basel: Birkhäuser Verlag, 2000.

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Structure in protein chemistry. 2nd ed. New York: Garland Science, 2007.

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Kyte, Jack. Structure in protein chemistry. New York: Garland Pub., 1995.

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Kyte, Jack. Structure in protein chemistry. New York: Garland Pub., 2006.

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Atassi, M. Zouhair, and Ettore Appella, eds. Methods in Protein Structure Analysis. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1031-8.

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Henrik, Bohr, and Brunak S[0]ren, eds. Protein structure by distance analysis. Amsterdam: IOS Press, 1994.

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Z, Atassi M., and Appella Ettore, eds. Methods in protein structure analysis. New York: Plenum Press, 1995.

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1940-, Creighton Thomas E., ed. Protein structure: A practical approach. Washington, DC: IRL Press, 1997.

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Y, Yada R., Jackman R. L, Smith J. L, and World Congress of Food Science and Technology (8th : 1991 : Toronto, Ont.), eds. Protein structure-function relationships in foods. London: Blackie Academic & Professional, 1994.

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Book chapters on the topic "Protein structure analysis"

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Rosenberg, Ian M. "Protein Structure." In Protein Analysis and Purification, 8–23. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-2056-5_2.

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Rosenberg, Ian M. "Protein Structure." In Protein Analysis and Purification, 5–18. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4757-1108-0_2.

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Kyriakidis, D. A. "Purification of Proteins for Sequencing." In Protein Structure Analysis, 3–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_1.

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Choli-Papadopoulou, T., Y. Skendros, and K. Katsani. "A Manual Method for Protein Sequence Analysis Using the DABITC/PITC Method." In Protein Structure Analysis, 137–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_10.

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Salnikow, J. "Solid-Phase Sequencing of Peptides and Proteins." In Protein Structure Analysis, 153–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_11.

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Hirano, H. "Sequence Analysis of the NH2-Terminally Blocked Proteins Immobilized on PVDF Membranes from Polyacrylamide Gels." In Protein Structure Analysis, 167–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_12.

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Jungblut, P. "Two-Dimensional Electrophoresis." In Protein Structure Analysis, 183–214. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_13.

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Jungblut, P. "Semi-Dry Blotting onto Hydrophobic Membranes." In Protein Structure Analysis, 215–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_14.

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Kamp, R. M. "Highly Sensitive Amino Acid Analysis." In Protein Structure Analysis, 231–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_15.

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Vollenbroich, D., and K. Krause. "Quantitative Analysis of D- and L-Amino Acids by HPLC." In Protein Structure Analysis, 249–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59219-5_16.

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Conference papers on the topic "Protein structure analysis"

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Ferretti, Marco, and Luigi Santangelo. "Protein Secondary Structure Analysis in the Cloud." In the 6th International Workshop. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3235830.3235837.

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Liu, Wei, Anuj Srivastava, and Jinfeng Zhang. "Protein structure alignment using elastic shape analysis." In the First ACM International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854790.

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Iryanto, Syam B., Taufik Djatna, and Toto Haryanto. "Ensemble learning for protein secondary structure analysis." In 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS). IEEE, 2017. http://dx.doi.org/10.1109/icacsis.2017.8355066.

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Hao Tian, R. Sunderraman, I. Weber, Haibin Wang, and Hong Yang. "A Protein Structure Data and Analysis System." In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1617067.

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"SEGMENTATION OF SES FOR PROTEIN STRUCTURE ANALYSIS." In International Conference on Bioinformatics. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002590900830089.

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Yang, Lina, Pu Wei, Xichun Li, and Yuan Yan Tang. "Application Of LSTM In Protein Structure Prediction LINA." In 2019 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2019. http://dx.doi.org/10.1109/icwapr48189.2019.8946472.

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Hua, Hongxuan. "IPSNN: Identification of Protein Structure based Neural Network." In 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2018. http://dx.doi.org/10.1109/spac46244.2018.8965498.

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Hua, Hongxuan. "CPSNF: Classification of Protein Structure with Novel Features." In 2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2018. http://dx.doi.org/10.1109/spac46244.2018.8965568.

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Leon, Florin, Bogdan Ioan Aignatoaiei, and Mihai Horia Zaharia. "Performance Analysis of Algorithms for Protein Structure Classification." In 2009 20th International Workshop on Database and Expert Systems Application. IEEE, 2009. http://dx.doi.org/10.1109/dexa.2009.17.

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Hamel, L., Gongqin Sun, and Jing Zhang. "Toward Protein Structure Analysis with Self-Organizing Maps." In 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology. IEEE, 2005. http://dx.doi.org/10.1109/cibcb.2005.1594961.

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Reports on the topic "Protein structure analysis"

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Cao, Haibo. Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method. Office of Scientific and Technical Information (OSTI), January 2003. http://dx.doi.org/10.2172/822060.

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Zemla, A. Protein Classification Based on Analysis of Local Sequence-Structure Correspondence. Office of Scientific and Technical Information (OSTI), February 2006. http://dx.doi.org/10.2172/893991.

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Zemla, A. Protein Classification Based on Analysis of Local Sequence-Structure Correspondence. Office of Scientific and Technical Information (OSTI), February 2006. http://dx.doi.org/10.2172/928169.

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Miller, Susan M. Structure/Function Analysis of Protein-Protein Interactions and Role of Dynamic Motions in Mercuric Ion Reductase. Office of Scientific and Technical Information (OSTI), May 2005. http://dx.doi.org/10.2172/840156.

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Honig, Barry. Protein structure and function prediction from physical chemical principles and database analysis. Office of Scientific and Technical Information (OSTI), September 2002. http://dx.doi.org/10.2172/804719.

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Liao, Jianhua, Jingting Liu, Baoqing Liu, Chunyan Meng, and Peiwen Yuan. Effect of OIP5-AS1 on clinicopathological characteristics and prognosis of cancer patients: a meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2022. http://dx.doi.org/10.37766/inplasy2022.10.0118.

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Review question / Objective: According to recent studies, long non-coding RNA (lncRNAs) i.e., OPA-interacting protein 5 antisense RNA 1 (OIP5-AS1) has an important role in various carcinomas. However, its role in the cancer is contradictory. Therefore, we aimed to evaluate the link between OIP5-AS1 and cancer patients' clinicopathological characteristics and prognosis to better understand OIP5-AS1's role in cancer. Condition being studied: Reported studies have revealed that long non-coding RNA (lncRNAs) are considerably involved in crucial physiological events in several carcinomas, it can inhibit or promote the occurrence and development of tumors by changing the sequence and spatial structure, modulating epigenetic, regulating the expression level and interacting with binding proteins. However, the mechanism of cancer regulation via lncRNAs was incompletely understood. Hence, clarifying the application value of lncRNAs in preclinical and clinical disease diagnosis and treatment was therefore the prime objective in the field of cancer research at the time.
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Christopher, David A., and Avihai Danon. Plant Adaptation to Light Stress: Genetic Regulatory Mechanisms. United States Department of Agriculture, May 2004. http://dx.doi.org/10.32747/2004.7586534.bard.

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Original Objectives: 1. Purify and biochemically characterize RB60 orthologs in higher plant chloroplasts; 2. Clone the gene(s) encoding plant RB60 orthologs and determine their structure and expression; 3. Manipulate the expression of RB60; 4. Assay the effects of altered RB60 expression on thylakoid biogenesis and photosynthetic function in plants exposed to different light conditions. In addition, we also examined the gene structure and expression of RB60 orthologs in the non-vascular plant, Physcomitrella patens and cloned the poly(A)-binding protein orthologue (43 kDa RB47-like protein). This protein is believed to a partner that interacts with RB60 to bind to the psbA5' UTR. Thus, to obtain a comprehensive view of RB60 function requires analysis of its biochemical partners such as RB43. Background & Achievements: High levels of sunlight reduce photosynthesis in plants by damaging the photo system II reaction center (PSII) subunits, such as D1 (encoded by the chloroplast tpsbAgene). When the rate of D1 synthesis is less than the rate of photo damage, photo inhibition occurs and plant growth is decreased. Plants use light-activated translation and enhanced psbAmRNA stability to maintain D1 synthesis and replace the photo damaged 01. Despite the importance to photosynthetic capacity, these mechanisms are poorly understood in plants. One intriguing model derived from the algal chloroplast system, Chlamydomonas, implicates the role of three proteins (RB60, RB47, RB38) that bind to the psbAmRNA 5' untranslated leader (5' UTR) in the light to activate translation or enhance mRNA stability. RB60 is the key enzyme, protein D1sulfide isomerase (Pill), that regulates the psbA-RN :Binding proteins (RB's) by way of light-mediated redox potentials generated by the photosystems. However, proteins with these functions have not been described from higher plants. We provided compelling evidence for the existence of RB60, RB47 and RB38 orthologs in the vascular plant, Arabidopsis. Using gel mobility shift, Rnase protection and UV-crosslinking assays, we have shown that a dithiol redox mechanism which resembles a Pill (RB60) activity regulates the interaction of 43- and 30-kDa proteins with a thermolabile stem-loop in the 5' UTR of the psbAmRNA from Arabidopsis. We discovered, in Arabidopsis, the PD1 gene family consists of II members that differ in polypeptide length from 361 to 566 amino acids, presence of signal peptides, KDEL motifs, and the number and positions of thioredoxin domains. PD1's catalyze the reversible formation an disomerization of disulfide bonds necessary for the proper folding, assembly, activity, and secretion of numerous enzymes and structural proteins. PD1's have also evolved novel cellular redox functions, as single enzymes and as subunits of protein complexes in organelles. We provide evidence that at least one Pill is localized to the chloroplast. We have used PDI-specific polyclonal and monoclonal antisera to characterize the PD1 (55 kDa) in the chloroplast that is unevenly distributed between the stroma and pellet (containing membranes, DNA, polysomes, starch), being three-fold more abundant in the pellet phase. PD1-55 levels increase with light intensity and it assembles into a high molecular weight complex of ~230 kDa as determined on native blue gels. In vitro translation of all 11 different Pill's followed by microsomal membrane processing reactions were used to differentiate among PD1's localized in the endoplasmic reticulum or other organelles. These results will provide.1e insights into redox regulatory mechanisms involved in adaptation of the photosynthetic apparatus to light stress. Elucidating the genetic mechanisms and factors regulating chloroplast photosynthetic genes is important for developing strategies to improve photosynthetic efficiency, crop productivity and adaptation to high light environments.
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Morrison, Mark, Joshuah Miron, Edward A. Bayer, and Raphael Lamed. Molecular Analysis of Cellulosome Organization in Ruminococcus Albus and Fibrobacter Intestinalis for Optimization of Fiber Digestibility in Ruminants. United States Department of Agriculture, March 2004. http://dx.doi.org/10.32747/2004.7586475.bard.

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Improving plant cell wall (fiber) degradation remains one of the highest priority research goals for all ruminant enterprises dependent on forages, hay, silage, or other fibrous byproducts as energy sources, because it governs the provision of energy-yielding nutrients to the host animal. Although the predominant species of microbes responsible for ruminal fiber degradation are culturable, the enzymology and genetics underpinning the process are poorly defined. In that context, there were two broad objectives for this proposal. The first objective was to identify the key cellulosomal components in Ruminococcus albus and to characterize their structural features as well as regulation of their expression, in response to polysaccharides and (or) P AA/PPA. The second objective was to evaluate the similarities in the structure and architecture of cellulosomal components between R. albus and other ruminal and non-ruminal cellulolytic bacteria. The cooperation among the investigators resulted in the identification of two glycoside hydrolases rate-limiting to cellulose degradation by Ruminococcus albus (Cel48A and CeI9B) and our demonstration that these enzymes possess a novel modular architecture specific to this bacterium (Devillard et al. 2004). We have now shown that the novel X-domains in Cel48A and Cel9B represent a new type of carbohydrate binding module, and the enzymes are not part of a ceiluiosome-like complex (CBM37, Xu et al. 2004). Both Cel48A and Cel9B are conditionally expressed in response to P AA/PPA, explaining why cellulose degradation in this bacterium is affected by the availability of these compounds, but additional studies have shown for the first time that neither PAA nor PPA influence xylan degradation by R. albus (Reveneau et al. 2003). Additionally, the R. albus genome sequencing project, led by the PI. Morrison, has supported our identification of many dockerin containing proteins. However, the identification of gene(s) encoding a scaffoldin has been more elusive, and recombinant proteins encoding candidate cohesin modules are now being used in Israel to verify the existence of dockerin-cohesin interactions and cellulosome production by R. albus. The Israeli partners have also conducted virtually all of the studies specific to the second Objective of the proposal. Comparative blotting studies have been conducted using specific antibodies prepare against purified recombinant cohesins and X-domains, derived from cellulosomal scaffoldins of R. flavefaciens 17, a Clostridium thermocellum mutant-preabsorbed antibody preparation, or against CbpC (fimbrial protein) of R. albus 8. The data also suggest that additional cellulolytic bacteria including Fibrobacter succinogenes S85, F. intestinalis DR7 and Butyrivibrio fibrisolvens Dl may also employ cellulosomal modules similar to those of R. flavefaciens 17. Collectively, our work during the grant period has shown that R. albus and other ruminal bacteria employ several novel mechanisms for their adhesion to plant surfaces, and produce both cellulosomal and non-cellulosomal forms of glycoside hydrolases underpinning plant fiber degradation. These improvements in our mechanistic understanding of bacterial adhesion and enzyme regulation now offers the potential to: i) optimize ruminal and hindgut conditions by dietary additives to maximize fiber degradation (e.g. by the addition of select enzymes or PAA/PPA); ii) identify plant-borne influences on adhesion and fiber-degradation, which might be overcome (or improved) by conventional breeding or transgenic plant technologies and; iii) engineer or select microbes with improved adhesion capabilities, cellulosome assembly and fiber degradation. The potential benefits associated with this research proposal are likely to be realized in the medium term (5-10 years).
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9

Sela, Shlomo, and Michael McClelland. Investigation of a new mechanism of desiccation-stress tolerance in Salmonella. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598155.bard.

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Low-moisture foods (LMF) are increasingly involved in foodborne illness. While bacteria cannot grow in LMF due to the low water content, pathogens such as Salmonella can still survive in dry foods and pose health risks to consumer. We recently found that Salmonella secretes a proteinaceous compound during desiccation, which we identified as OsmY, an osmotic stress response protein of 177 amino acids. To elucidate the role of OsmY in conferring tolerance against desiccation and other stresses in Salmonella entericaserovarTyphimurium (STm), our specific objectives were: (1) Characterize the involvement of OsmY in desiccation tolerance; (2) Perform structure-function analysis of OsmY; (3) Study OsmY expression under various growth- and environmental conditions of relevance to agriculture; (4) Examine the involvement of OsmY in response to other stresses of relevance to agriculture; and (5) Elucidate regulatory pathways involved in controlling osmY expression. We demonstrated that an osmY-mutant strain is impaired in both desiccation tolerance (DT) and in long-term persistence during cold storage (LTP). Genetic complementation and addition of a recombinantOsmY (rOsmY) restored the mutant survival back to that of the wild type (wt). To analyze the function of specific domains we have generated a recombinantOsmY (rOsmY) protein. A dose-response DT study showed that rOsmY has the highest protection at a concentration of 0.5 nM. This effect was protein- specific as a comparable amount of bovine serum albumin, an unrelated protein, had a three-time lower protection level. Further characterization of OsmY revealed that the protein has a surfactant activity and is involved in swarming motility. OsmY was shown to facilitate biofilm formation during dehydration but not during bacterial growth under optimal growth conditions. This finding suggests that expression and secretion of OsmY under stress conditions was potentially associated with facilitating biofilm production. OsmY contains two conserved BON domains. To better understand the role of the BON sites in OsmY-mediated dehydration tolerance, we have generated two additional rOsmY constructs, lacking either BON1 or BON2 sites. BON1-minus (but not BON2) protein has decreased dehydration tolerance compared to intact rOsmY, suggesting that BON1 is required for maximal OsmY-mediated activity. Addition of BON1-peptide at concentration below 0.4 µM did not affect STm survival. Interestingly, a toxic effect of BON1 peptide was observed in concentration as low as 0.4 µM. Higher concentrations resulted in complete abrogation of the rOsmY effect, supporting the notion that BON-mediated interaction is essential for rOsmY activity. We performed extensive analysis of RNA expression of STm undergoing desiccation after exponential and stationary growth, identifying all categories of genes that are differentially expressed during this process. We also performed massively in-parallel screening of all genes in which mutation caused changes in fitness during drying, identifying over 400 such genes, which are now undergoing confirmation. As expected OsmY is one of these genes. In conclusion, this is the first study to identify that OsmY protein secreted during dehydration contributes to desiccation tolerance in Salmonella by facilitating dehydration- mediated biofilm formation. Expression of OsmY also enhances swarming motility, apparently through its surfactant activity. The BON1 domain is required for full OsmY activity, demonstrating a potential intervention to reduce pathogen survival in food processing. Expression and fitness screens have begun to elucidate the processes of desiccation, with the potential to uncover additional specific targets for efforts to mitigate pathogen survival in desiccation.
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10

Zhao, Zepeng, Fengyuan Zhang, and Yijin Li. The Relationship Between Il-1 RN intron 2 (VNTR) rs2234663 Gene Polymorphism and The Progression of Periodontitis: A systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2023. http://dx.doi.org/10.37766/inplasy2023.3.0100.

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Review question / Objective: The aim of this systematic review and meta-analysis of case-control studies is to find out the association of IL-1 RN intron 2 (VNTR) rs2234663 Gene Polymorphism and the occurrence and progression of periodontitis(including chronic periodontitis, aggressive periodontitis and early-onset periodontitis). Condition being studied: Periodontitis is one of the most common ailments affecting the teeth, leading to the destruction of the supporting and surrounding tooth structure. Periodontitis is originally a disease originating from the gingival tissue which if left untreated results in penetration of inflammation to the deeper tissues, altering the bone homeostasis causing tooth loss. Periodontal disease has a multifactorial origin. The main culprit identified in periodontitis is the bacterial biofilm growing on the tooth surfaces. The deleterious effects of periodontopathogens are not limited to the periodontium, but they also exude their ill effects on the systemic health of the patients. While the host response determines the progression of the disease, genetics, environmental factors, systemic health of the patient, lifestyle habits and various social determinants also play a role. Interleukin-1 receptor antagonist encoded by this gene IL-1RN is a member of the interleukin 1 cytokine family. This protein inhibits the activities of interleukin 1, alpha (IL1A) and interleukin 1, beta (IL1B), and modulates a variety of interleukin 1 related immune and inflammatory responses, particularly in the acute phase of infection and inflammation. We aim to study their association by conducting a meta-analysis.
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