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Relevant bibliographies by topics / Protein-protein interactions

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Academic literature on the topic 'Protein-protein interactions'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 July 2024

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Journal articles on the topic "Protein-protein interactions"

1

Acuner Ozbabacan, S. E., H. B. Engin, A. Gursoy, and O. Keskin. "Transient protein-protein interactions." Protein Engineering Design and Selection 24, no. 9 (June 15, 2011): 635–48. http://dx.doi.org/10.1093/protein/gzr025.

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Legrain, Pierre. "Protein–Protein Interactions: Protein interactions contribute to protein function." Trends in Genetics 18, no. 8 (August 2002): 432. http://dx.doi.org/10.1016/s0168-9525(02)02710-5.

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Lederman, Lynne. "Protein-Protein Interactions." BioTechniques 40, no. 5 (May 2006): 567–69. http://dx.doi.org/10.2144/06405tn01.

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Hirata, Rosário D. C. "Protein-Protein Interactions." Revista Brasileira de Ciências Farmacêuticas 40, no. 1 (March 2004): 111–12. http://dx.doi.org/10.1590/s1516-93322004000100017.

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Williamson, Mike P., and Michael J. Sutcliffe. "Protein–protein interactions." Biochemical Society Transactions 38, no. 4 (July 26, 2010): 875–78. http://dx.doi.org/10.1042/bst0380875.

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In the present article, we describe the two standard high-throughput methods for identification of protein complexes: two-hybrid screens and TAP (tandem affinity purification) tagging. These methods have been used to characterize the interactome of Saccharomyces cerevisiae, showing that the majority of proteins are part of complexes, and that complexes typically consist of a core to which are bound ‘party’ and ‘dater’ proteins. Complexes typically are merely the sum of their parts. A particularly interesting type of complex is the metabolon, containing enzymes within the same metabolic pathway. There is reasonably good evidence that metabolons exist, but they have not been detected using high-thoughput assays, possibly because of their fragility.

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Halperin, Inbal, Haim Wolfson, and Ruth Nussinov. "Protein-Protein Interactions." Structure 12, no. 6 (June 2004): 1027–38. http://dx.doi.org/10.1016/j.str.2004.04.009.

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Janin, Joël, and Alexandre MJJ Bonvin. "Protein–protein interactions." Current Opinion in Structural Biology 23, no. 6 (December 2013): 859–61. http://dx.doi.org/10.1016/j.sbi.2013.10.003.

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Ottmann, Christian. "Protein–Protein Interactions." Drug Discovery Today: Technologies 24 (June 2017): 1–2. http://dx.doi.org/10.1016/j.ddtec.2017.11.008.

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NG, SEE-KIONG, and SOON-HENG TAN. "DISCOVERING PROTEIN–PROTEIN INTERACTIONS." Journal of Bioinformatics and Computational Biology 01, no. 04 (January 2004): 711–41. http://dx.doi.org/10.1142/s0219720004000600.

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The ongoing genomics and proteomics efforts have helped identify many new genes and proteins in living organisms. However, simply knowing the existence of genes and proteins does not tell us much about the biological processes in which they participate. Many major biological processes are controlled by protein interaction networks. A comprehensive description of protein–protein interactions is therefore necessary to understand the genetic program of life. In this tutorial, we provide an overview of the various current high-throughput methods for discovering protein–protein interactions, covering both the conventional experimental methods and new computational approaches.

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CHUA, HON NIAN, KANG NING, WING-KIN SUNG, HON WAI LEONG, and LIMSOON WONG. "USING INDIRECT PROTEIN–PROTEIN INTERACTIONS FOR PROTEIN COMPLEX PREDICTION." Journal of Bioinformatics and Computational Biology 06, no. 03 (June 2008): 435–66. http://dx.doi.org/10.1142/s0219720008003497.

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Protein complexes are fundamental for understanding principles of cellular organizations. As the sizes of protein–protein interaction (PPI) networks are increasing, accurate and fast protein complex prediction from these PPI networks can serve as a guide for biological experiments to discover novel protein complexes. However, it is not easy to predict protein complexes from PPI networks, especially in situations where the PPI network is noisy and still incomplete. Here, we study the use of indirect interactions between level-2 neighbors (level-2 interactions) for protein complex prediction. We know from previous work that proteins which do not interact but share interaction partners (level-2 neighbors) often share biological functions. We have proposed a method in which all direct and indirect interactions are first weighted using topological weight (FS-Weight), which estimates the strength of functional association. Interactions with low weight are removed from the network, while level-2 interactions with high weight are introduced into the interaction network. Existing clustering algorithms can then be applied to this modified network. We have also proposed a novel algorithm that searches for cliques in the modified network, and merge cliques to form clusters using a "partial clique merging" method. Experiments show that (1) the use of indirect interactions and topological weight to augment protein–protein interactions can be used to improve the precision of clusters predicted by various existing clustering algorithms; and (2) our complex-finding algorithm performs very well on interaction networks modified in this way. Since no other information except the original PPI network is used, our approach would be very useful for protein complex prediction, especially for prediction of novel protein complexes.

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Dissertations / Theses on the topic "Protein-protein interactions"

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Jones, Susan. "Protein-protein interactions." Thesis, University College London (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338952.

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Cooper, Simon T. "PAX6 protein-protein interactions." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/29070.

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The gene PAX6 is located on chromosome 11 (11p13) and encodes a transcription factor (PAX6) that is expressed early in development. The PAX6 protein is expressed in the developing eye, regions of the brain, central nervous system (CNS), nasal epithelium and pancreas. PAX6 is best known for its role eye development with heterozygous mutations causing congenital ocular malformations. However, it must be remembered that PAX6 has multiple functions in the brain including specification of neuronal subtypes and axon guidance. There is growing understanding of the role of PAX6 as a transcription factor during development, and many of its DNA targets have recently been defined. However, almost nothing is known about the proteins with which PAX6 interacts. In the initial stage of my research I identified a conserved region consisting of the final 32 amino acids of the PST (proline, serine and threonine rich) domain of PAX6. Based on sequence homology and secondary structure predictions I classed this region as a novel domain, the ‘C terminal domain’. Next I used the yeast 2-hybrid system to investigate possible PAX6 protein interactions. By screening a mouse brain cDNA library with the C terminal domain and whole PST domain, I identified three novel and interesting interactors, HOMER3, DNCL1 and TRIM11. I re-confirmed these interactions in a pairwise manner using the yeast 2-hybrid system, and I showed that the C terminal domain was vital for the interactions between PAX6 and HOMER3 or DNCL1. Furthermore, certain C terminal mutations that are known to cause ocular malformations in patients are also sufficient to reduce or abolish these interactions. I attempted to further characterise the interactions by co-immunoprecipitation. However, this was not possible due to technical difficulties.

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Xia, Zebin. "Peptidomimetics to mimic protein-protein interactions." Diss., Texas A&M University, 2003. http://hdl.handle.net/1969.1/2239.

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Quenched Molecular Dynamics (QMD) used to explore molecular conformations was developed to operate in Insight II platform for two simulation engines: CHARMm and Discover. Two scripts and procedures were written for molecular minimization, dynamics, minimization of each of several hundred conformers, and cut off. Experience with Insight II/Discover versus Quanta/CHARMm, and between Insight II/CHARMm versus Quanta/CHARMm has taught that the forcefield is the key factor in QMD studies. Protein A has been used for the purification of commercial antibodies, but it is expensive. Seven peptidomimetics of protein A were designed based on the hot-spots located at the helix-loop-helix region of protein A, and synthesized via solid phase using the Fmoc approach. These peptidomimetics were characterized by MS and NMR. The conformations of four peptidomimetics were studied by NMR and CD in water/hexafluoroisopropanol (pH 4). The CD and NMR data show that addition of hexafluoroisopropanol stabilizes their a-helical conformations. The structures of these peptidomimetics in solution were generated with Quanta/CHARMm using NMR data as limits for the QMD technique. Protein G has also been used to purify antibodies, but it is expensive too. A number of protein G mimics were designed as trivalent molecules. An efficient preparation of trivalent molecules having a useful primary amine arm has been developed through solid phase synthesis. The cheap, commercially available poly(propylene imine) dendrimers were used as scaffolds which allow multimerization of functionalized compounds. A small library of trivalent compounds were synthesized using this approach. A portion of compounds in this library were tested by Amersham Biosciences. The seven amino acid modified DAB-Am-4 exhibits strong binding to the IgG/Fab, and is a potential ligand for IgG purification. The interactions between neurotrophins (ie NGF and NT-3) and their receptors are typical drug targets. Fourteen second-generation peptidomimetics showing NGF-like or NT3-like activities in a preliminary bioassay, were resynthesized and tested again. Preliminary and retested data were compared. To access a direct binding assay, five fluorescently labeled peptidomimetics 41a-e were synthesized for a fluorescence activated cell sorting (FACScan) assay. Six monomeric precursors 42 and 43 were prepared on large scales for the library of bivalent turn analogs

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Bateman, Katherine Sophie. "Structural studies of protein, protein interactions." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0020/NQ46804.pdf.

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Laidlaw, Stephen Mark. "Protein-protein interactions of fowlpox virus." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424671.

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Bougouffa, Salim. "Empirical modelling of protein-protein interactions." Thesis, University of Manchester, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529241.

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Robinson, Ross Alexander. "Structural biology of protein - protein interactions." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504517.

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Gill, Katrina Louise. "Protein-protein interactions in membrane proteins." Thesis, University of Newcastle Upon Tyne, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400016.

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Richter, Carsten Detlev. "Protein-protein interactions in modular megasynthases." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612738.

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Sammond, Deanne Wallander Kuhlman Brian A. "Computational redesign of protein-protein interactions." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1822.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.
Title from electronic title page (viewed Dec. 11, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biochemistry and Biophysics Program in Molecular and Cellular Biophysics." Discipline: Biochemistry and Biophysics; Department/School: Medicine.

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Books on the topic "Protein-protein interactions"

1

Fu, Haian. Protein-Protein Interactions. New Jersey: Humana Press, 2004. http://dx.doi.org/10.1385/1592597629.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. Protein-Protein Interactions. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8.

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Meyerkord, Cheryl L., and Haian Fu, eds. Protein-Protein Interactions. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2425-7.

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Wendt, Michael D., ed. Protein-Protein Interactions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28965-1.

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Poluri, Krishna Mohan, Khushboo Gulati, Deepak Kumar Tripathi, and Nupur Nagar. Protein-Protein Interactions. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2423-3.

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Mukhtar, Shahid, ed. Protein-Protein Interactions. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-3327-4.

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service), SpringerLink (Online, ed. Protein-Protein Interactions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Ruth, Nussinov, and Schreiber Gideon, eds. Computational protein-protein interactions. Boca Raton: CRC Press/Taylor & Francis, 2009.

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Schuck, Peter, ed. Protein Interactions. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/978-0-387-35966-3.

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Cai, Jianfeng, and Rongsheng E. Wang. Protein interactions. Rijeka: InTech, 2012.

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Book chapters on the topic "Protein-protein interactions"

1

Poluri, Krishna Mohan, Khushboo Gulati, Deepak Kumar Tripathi, and Nupur Nagar. "Protein-Protein Interactions in Host–Pathogen Interactions." In Protein-Protein Interactions, 207–64. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2423-3_5.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. "Experimental Methods for Determination of Protein–Protein Interactions." In Protein-Protein Interactions, 197–264. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8_5.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. "Structural and Functional Properties of Proteins." In Protein-Protein Interactions, 1–60. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8_1.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. "Prediction, Analysis, Visualization, and Storage of Protein–Protein Interactions Using Computational Approaches." In Protein-Protein Interactions, 265–346. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8_6.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. "Evolution-Structure Paradigm of Protein Complexes." In Protein-Protein Interactions, 153–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8_4.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. "Energetic Aspects of Protein–Protein Interactions (PPIs)." In Protein-Protein Interactions, 113–51. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8_3.

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Poluri, Krishna Mohan, Khushboo Gulati, and Sharanya Sarkar. "Structural Aspects of Protein–Protein Interactions." In Protein-Protein Interactions, 61–112. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1594-8_2.

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Poluri, Krishna Mohan, Khushboo Gulati, Deepak Kumar Tripathi, and Nupur Nagar. "Drug Design Methods to Regulate Protein–Protein Interactions." In Protein-Protein Interactions, 265–341. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2423-3_6.

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Poluri, Krishna Mohan, Khushboo Gulati, Deepak Kumar Tripathi, and Nupur Nagar. "Protein–Protein Interactions in Neurodegenerative Diseases." In Protein-Protein Interactions, 101–69. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2423-3_3.

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Poluri, Krishna Mohan, Khushboo Gulati, Deepak Kumar Tripathi, and Nupur Nagar. "Protein Networks in Human Disease." In Protein-Protein Interactions, 1–41. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2423-3_1.

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Conference papers on the topic "Protein-protein interactions"

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HSU, WEI-LUN, CHRISTOPHER OLDFIELD, JINGWEI MENG, FEI HUANG, BIN XUE, VLADIMIR N. UVERSKY, PEDRO ROMERO, and A. KEITH DUNKER. "INTRINSIC PROTEIN DISORDER AND PROTEIN-PROTEIN INTERACTIONS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814366496_0012.

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Deng, Minghua, Shipra Mehta, Fengzhu Sun, and Ting Chen. "Inferring domain-domain interactions from protein-protein interactions." In the sixth annual international conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/565196.565211.

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Katebi, Ataur R., Andrzej Kloczkowski, and Robert L. Jeringan. "Computational testing of protein-protein interactions." In 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop, BIBMW. IEEE, 2009. http://dx.doi.org/10.1109/bibmw.2009.5332118.

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Chua, Hon Nian, Kang Ning, Wing-Kin Sung, Hon Wai Leong, and Limsoon Wong. "USING INDIRECT PROTEIN-PROTEIN INTERACTIONS FOR PROTEIN COMPLEX PREDICTION." In Proceedings of the CSB 2007 Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2007. http://dx.doi.org/10.1142/9781860948732_0014.

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Liao, Wei-Chen, and Nai-Kuei Huang. "Profiling the Nanoparticles Associated Protein-protein Interactions." In 2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering (BIBE). IEEE, 2009. http://dx.doi.org/10.1109/bibe.2009.54.

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Ameer-Beg, S. M., N. Edme, M. Peter, P. R. Barber, T. Ng, and B. Vojnovic. "Imaging Protein-Protein Interactions By Multiphoton FLIM." In European Conference on Biomedical Optics. Washington, D.C.: OSA, 2003. http://dx.doi.org/10.1364/ecbo.2003.5139_180.

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"Deep learning for Protein-Protein Interactions Predication." In 2020 the 10th International Workshop on Computer Science and Engineering. WCSE, 2020. http://dx.doi.org/10.18178/wcse.2020.06.003.

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Ameer-Beg, Simon M., Natasha Edme, Marion Peter, Paul R. Barber, Tony Ng, and Borivoj Vojnovic. "Imaging protein-protein interactions by multiphoton FLIM." In European Conference on Biomedical Optics 2003, edited by Tony Wilson. SPIE, 2003. http://dx.doi.org/10.1117/12.500544.

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Sanchez-Graillet, Olivia, and Massimo Poesio. "Discovering contradicting protein-protein interactions in text." In the Workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2007. http://dx.doi.org/10.3115/1572392.1572428.

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Nafar, Zahra, and Ashkan Golshani. "Data Mining Methods for Protein-Protein Interactions." In 2006 Canadian Conference on Electrical and Computer Engineering. IEEE, 2006. http://dx.doi.org/10.1109/ccece.2006.277746.

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Reports on the topic "Protein-protein interactions"

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Noy, A., T. Sulchek, and R. Friddle. Direct Probing of Protein-Protein Interactions. Office of Scientific and Technical Information (OSTI), March 2005. http://dx.doi.org/10.2172/15015174.

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Blackwell, T. K. C-Myc Protein-Protein and Protein-DNA Interactions: Targets for Therapeutic Intervention. Fort Belvoir, VA: Defense Technical Information Center, September 1998. http://dx.doi.org/10.21236/ada371161.

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Blackwell, T. K. C-Myc Protein-Protein and Protein-DNA Interactions: Targets for Therapeutic Intervention. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada344737.

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Blackwell, T. K. C-MYC Protein-Protein and Protein-DNA Interactions: Targets for Therapeutic Intervention. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada381686.

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Umland, Timothy C. Cross-Species Virus-Host Protein-Protein Interactions Inhibiting Innate Immunity. Fort Belvoir, VA: Defense Technical Information Center, July 2016. http://dx.doi.org/10.21236/ad1012633.

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Martin, Shawn Bryan, Kenneth L. Sale, Jean-Loup Michel Faulon, and Diana C. Roe. Developing algorithms for predicting protein-protein interactions of homology modeled proteins. Office of Scientific and Technical Information (OSTI), January 2006. http://dx.doi.org/10.2172/883467.

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Wang, Lianyong, Jianping Hu, and Martin Jonikas. Transforming our understanding of chloroplast-associated genes through comprehensive characterization of protein localizations and protein-protein interactions. Office of Scientific and Technical Information (OSTI), November 2023. http://dx.doi.org/10.2172/2205224.

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Sarkisian, Christopher J., and Lewis A. Chodosh. Impact of Disrupted BRCA2 Protein-Protein Interactions on DNA Repair and Tumorigenesis. Fort Belvoir, VA: Defense Technical Information Center, July 2001. http://dx.doi.org/10.21236/ada400189.

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Jeremiah Pate, Jeremiah Pate. Amelioration of Alpha-Synuclein in Parkinson's Disease through potentiated protein-protein interactions. Experiment, October 2016. http://dx.doi.org/10.18258/8102.

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Sarkisian, Christopher J., and Lewis A. Chodosh. Impact of Disrupted Brca2 Protein-Protein Interactions on DNA Repair and Tumorigenesis. Fort Belvoir, VA: Defense Technical Information Center, July 2002. http://dx.doi.org/10.21236/ada413006.

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