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Journal articles on the topic 'Homology modelling'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 September 2023

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1

Swindells, Mark B., and Janet M. Thornton. "Modelling by homology." Current Opinion in Structural Biology 1, no. 2 (April 1991): 219–23. http://dx.doi.org/10.1016/0959-440x(91)90064-z.

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2

Studer, Gabriel, Gerardo Tauriello, Stefan Bienert, Marco Biasini, Niklaus Johner, and Torsten Schwede. "ProMod3—A versatile homology modelling toolbox." PLOS Computational Biology 17, no. 1 (January 28, 2021): e1008667. http://dx.doi.org/10.1371/journal.pcbi.1008667.

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Computational methods for protein structure modelling are routinely used to complement experimental structure determination, thus they help to address a broad spectrum of scientific questions in biomedical research. The most accurate methods today are based on homology modelling, i.e. detecting a homologue to the desired target sequence that can be used as a template for modelling. Here we present a versatile open source homology modelling toolbox as foundation for flexible and computationally efficient modelling workflows. ProMod3 is a fully scriptable software platform that can perform all steps required to generate a protein model by homology. Its modular design aims at fast prototyping of novel algorithms and implementing flexible modelling pipelines. Common modelling tasks, such as loop modelling, sidechain modelling or generating a full protein model by homology, are provided as production ready pipelines, forming the starting point for own developments and enhancements. ProMod3 is the central software component of the widely used SWISS-MODEL web-server.
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3

Vincent Vidyasagar J, Tharun Kumar G, Ramesh M, and Akila C R. "Current review on homology modelling." International Journal of Pharmaceutical Research and Life Sciences 7, no. 2 (December 28, 2019): 30–33. http://dx.doi.org/10.26452/ijprls.v7i2.1338.

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The procheck synopsis of the model is considered, and the anolea chart is inspected. Presently a little arrangement of an obscure protein is taken, and its grouping arrangement is finished with the assistance of a layout. The swiss model workspace is utilized to at extended last model the structure of the obscure protein. The procheck outline and its anolea are inspected and contrasted and the structure of the known protein. The approval of the structure is assessed.
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4

Aszódi, Andrés, and William R. Taylor. "Homology modelling by distance geometry." Folding and Design 1, no. 5 (October 1996): 325–34. http://dx.doi.org/10.1016/s1359-0278(96)00048-x.

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5

BARRY, THOMAS R., and SHAWN DOONAN. "Homology modelling of yeast aspartate aminotransferase." Biochemical Society Transactions 22, no. 1 (February 1, 1994): 83S. http://dx.doi.org/10.1042/bst022083s.

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6

Domicevica, Laura, and Philip C. Biggin. "Homology modelling of human P-glycoprotein." Biochemical Society Transactions 43, no. 5 (October 1, 2015): 952–58. http://dx.doi.org/10.1042/bst20150125.

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P-glycoprotein (P-gp) is an ATP-binding cassette transporter that exports a huge range of compounds out of cells and is thus one of the key proteins in conferring multi-drug resistance in cancer. Understanding how it achieves such a broad specificity and the series of conformational changes that allow export to occur form major, on-going, research objectives around the world. Much of our knowledge to date has been derived from mutagenesis and assay data. However, in recent years, there has also been great progress in structural biology and although the structure of human P-gp has not yet been solved, there are now a handful of related structures on which homology models can be built to aid in the interpretation of the vast amount of experimental data that currently exists. Many models for P-gp have been built with this aim, but the situation is complicated by the apparent flexibility of the system and by the fact that although many potential templates exist, there is large variation in the conformational state in which they have been crystallized. In this review, we summarize how homology modelling has been used in the past, how models are typically selected and finally illustrate how MD simulations can be used as a means to give more confidence about models that have been generated via this approach.
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7

Zhekova, Hristina R., Igor Zdravkovic, Sergei Yu Noskov, Toshie Sakuma, Susanna C. Concilio, Ryan Johnson, Stephen J. Russell, and Kah-Whye Peng. "Homology Modelling of Sodium Iodide Symporter." Biophysical Journal 114, no. 3 (February 2018): 573a—574a. http://dx.doi.org/10.1016/j.bpj.2017.11.3137.

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8

Vlachakis, Dimitrios, Dimitrios Georgios Kontopoulos, and Sophia Kossida. "Space Constrained Homology Modelling: The Paradigm of the RNA-Dependent RNA Polymerase of Dengue (Type II) Virus." Computational and Mathematical Methods in Medicine 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/108910.

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Protein structure is more conserved than sequence in nature. In this direction we developed a novel methodology that significantly improves conventional homology modelling when sequence identity is low, by taking into consideration 3D structural features of the template, such as size and shape. Herein, our new homology modelling approach was applied to the homology modelling of the RNA-dependent RNA polymerase (RdRp) of dengue (type II) virus. The RdRp of dengue was chosen due to the low sequence similarity shared between the dengue virus polymerase and the available templates, while purposely avoiding to use the actual X-ray structure that is available for the dengue RdRp. The novel approach takes advantage of 3D space corresponding to protein shape and size by creating a 3D scaffold of the template structure. The dengue polymerase model built by the novel approach exhibited all features of RNA-dependent RNA polymerases and was almost identical to the X-ray structure of the dengue RdRp, as opposed to the model built by conventional homology modelling. Therefore, we propose that the space-aided homology modelling approach can be of a more general use to homology modelling of enzymes sharing low sequence similarity with the template structures.
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9

Boscott, P. E., G. J. Barton, and W. G. Richards. "Secondary structure prediction for modelling by homology." "Protein Engineering, Design and Selection" 6, no. 3 (1993): 261–66. http://dx.doi.org/10.1093/protein/6.3.261.

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10

Ghetti, Andrea, Martino Bolognesi, Fabio Cobianchi, and Carlo Morandi. "Modelling by homology of RNA binding domain." Molecular Biology Reports 14, no. 2-3 (1990): 87–88. http://dx.doi.org/10.1007/bf00360427.

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11

Summers, Neena L., and Martin Karplus. "Construction of side-chains in homology modelling." Journal of Molecular Biology 210, no. 4 (December 1989): 785–811. http://dx.doi.org/10.1016/0022-2836(89)90109-5.

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12

Vardhini, Shailima RD, and Siddeshwari Ekke. "HOMOLOGY MODELLING AND STRUCTURAL ANALYSIS OF HER 2." INTERNATIONAL RESEARCH JOURNAL OF PHARMACY 4, no. 12 (January 15, 2014): 36–40. http://dx.doi.org/10.7897/2230-8407.041208.

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13

Junk, Philipp, and Christina Kiel. "HOMELETTE: a unified interface to homology modelling software." Bioinformatics 38, no. 6 (December 25, 2021): 1749–51. http://dx.doi.org/10.1093/bioinformatics/btab866.

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Abstract Summary Homology modelling, the technique of generating models of 3D protein structures based on experimental structures from related proteins, has become increasingly popular over the years. An abundance of different tools for model generation and model evaluation is available from various research groups. We present HOMELETTE, an interface which implements a unified programmatic access to these tools. This allows for the assemble of custom pipelines from pre- or self-implemented building blocks. Availability and implementation HOMELETTE is implemented in Python, compatible with version 3.6 and newer. It is distributed under the MIT license. Documentation and tutorials are available at Read the Docs (https://homelette.readthedocs.io/). The latest version of HOMELETTE is available on PyPI (https://pypi.org/project/homelette/) and GitHub (https://github.com/PhilippJunk/homelette). A full installation of the latest version of HOMELETTE with all dependencies is also available as a Docker container (https://hub.docker.com/r/philippjunk/homelette_template). Supplementary information Supplementary data are available at Bioinformatics online.
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14

Farce, Amaury, Sebastien Dilly, Said Yous, Pascal Berthelot, and Philippe Chavatte. "Homology modelling of the serotoninergic 5-HT2c receptor." Journal of Enzyme Inhibition and Medicinal Chemistry 21, no. 3 (January 1, 2006): 285–92. http://dx.doi.org/10.1080/14756360600700608.

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15

Lesk, Arthur M., and D. Ross Boswell. "Homology modelling: inferences from tables of aligned sequences." Current Biology 2, no. 5 (May 1992): 257. http://dx.doi.org/10.1016/0960-9822(92)90371-g.

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16

Brahemi, Ghali, Angelika Burger, Andrew Westwell, and Andrea Brancale. "Homology Modelling of Human E1 Ubiquitin Activating Enzyme." Letters in Drug Design & Discovery 7, no. 1 (January 1, 2010): 57–62. http://dx.doi.org/10.2174/157018010789869316.

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17

Lesk, Arthur M., and D. Ross Boswell. "Homology modelling: inferences from tables of aligned sequences." Current Opinion in Structural Biology 2, no. 2 (April 1992): 242–47. http://dx.doi.org/10.1016/0959-440x(92)90153-x.

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18

Sen, Arnab, Saubashya Sur, Louis S. Tisa, Asim Kr Bothra, Subarna Thakur, and Uttam Kr Mondal. "Homology modelling of the Frankia nitrogenase iron protein." Symbiosis 50, no. 1-2 (December 4, 2009): 37–44. http://dx.doi.org/10.1007/s13199-009-0035-9.

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19

Oliaro-Bosso, S., T. Schulz-Gasch, S. Taramino, M. Scaldaferri, F. Viola, and G. Balliano. "Access of the substrate to the active site of squalene and oxidosqualene cyclases: comparative inhibition, site-directed mutagenesis and homology-modelling studies." Biochemical Society Transactions 33, no. 5 (October 26, 2005): 1202–5. http://dx.doi.org/10.1042/bst0331202.

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Substrate access to the active-site cavity of squalene-hopene cyclase from Alicyclobacillus acidocaldarious and lanosterol synthase [OSC (oxidosqualene cyclase)] from Saccharomyces cerevisiae was studied by an inhibition, mutagenesis and homology-modelling approach. Crystal structure and homology modelling indicate that both enzymes possess a narrow constriction that separates an entrance lipophilic channel from the active-site cavity. The role of the constriction as a mobile gate that permits substrate passage was investigated by experiments in which critically located Cys residues, either present in native protein or inserted by site-directed mutagenesis, were labelled with specifically designed thiol-reacting molecules. Some amino acid residues of the yeast enzyme, selected on the basis of sequence alignment and a homology model, were individually replaced by residues bearing side chains of different lengths, charges or hydrophobicities. In some of these mutants, substitution severely reduced enzymatic activity and thermal stability. Homology modelling revealed that in these mutants some critical stabilizing interactions could no longer occur. The possible critical role of entrance channel and constriction in specific substrate recognition by eukaryotic OSC is discussed.
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20

Wyrwicz, Lucjan S., and Leszek Rychlewski. "Fold recognition insights into function of herpes ICP4 protein." Acta Biochimica Polonica 54, no. 3 (September 17, 2007): 551–59. http://dx.doi.org/10.18388/abp.2007_3228.

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ICP4 is an important factor regulating the life cycle of HSV1. This conserved protein has several molecular functions, including activation of expression of viral late gene transcripts and inhibition of immediate early genes. Although ICP4 and its Alphaherpesvirinae homologs (eg.: IE62 of VZV) have been subjects of various molecular studies, a complete view of their molecular function is lacking. Here we present the results of fold recognition and molecular modelling of ICP4 functional domains. The performed state-of-the-art bioinformatic fold recognition analysis identified a dual helix-turn-helix motif as a binding module of repressor activities (so called region 2 domain). The mapping of distant homology identified that a segment responsible for activation of late gene promoters (region 4) exhibits folding of uracil DNA glycosylase (UDG), but seems to be a non-functional homolog of UDG. Potential implications of the results are discussed.
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21

Hannaford, G. J. H., C. R. Maple, K. S. Sarakinou, and J. G. L. Mullins. "Rapid homology modelling of membrane transport proteins and receptors." Biochemical Society Transactions 29, no. 5 (October 1, 2001): A124. http://dx.doi.org/10.1042/bst029a124a.

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22

Lemcke, Thomas, Inge T. Christensen, and Flemming S. Jergensen. "Homology modelling of dihydrofolate reductase from the malaria parasite." European Journal of Pharmaceutical Sciences 4 (September 1996): S105. http://dx.doi.org/10.1016/s0928-0987(97)86310-5.

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23

Costa, Caterina, Carmela Cavalcante, Francesca Zito, Yukio Yokota, and Valeria Matranga. "Phylogenetic analysis and homology modelling of Paracentrotus lividus nectin." Molecular Diversity 14, no. 4 (November 12, 2009): 653–65. http://dx.doi.org/10.1007/s11030-009-9203-3.

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24

Waterhouse, Andrew, Martino Bertoni, Stefan Bienert, Gabriel Studer, Gerardo Tauriello, Rafal Gumienny, Florian T. Heer, et al. "SWISS-MODEL: homology modelling of protein structures and complexes." Nucleic Acids Research 46, W1 (May 21, 2018): W296—W303. http://dx.doi.org/10.1093/nar/gky427.

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25

Ramyachitra, D., and P. Pradeep Kumar. "Frog leap algorithm for homology modelling in grid environment." International Journal of Grid and Utility Computing 7, no. 1 (2016): 29. http://dx.doi.org/10.1504/ijguc.2016.073775.

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26

Venselaar, Hanka, Robbie P. Joosten, Bas Vroling, Coos A. B. Baakman, Maarten L. Hekkelman, Elmar Krieger, and Gert Vriend. "Homology modelling and spectroscopy, a never-ending love story." European Biophysics Journal 39, no. 4 (August 29, 2009): 551–63. http://dx.doi.org/10.1007/s00249-009-0531-0.

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27

Tye, Heather, Ulrich Guertler, Marco H. Hofmann, Moriz Mayer, Sandeep Pal, Georg Rast, Michael P. Sanderson, Otmar Schaaf, Matthias Treu, and Stephan K. Zahn. "Discovery of novel amino-pyrimidine inhibitors of the insulin-like growth factor 1 (IGF1R) and insulin receptor (INSR) kinases; parallel optimization of cell potency and hERG inhibition." MedChemComm 6, no. 7 (2015): 1244–51. http://dx.doi.org/10.1039/c5md00097a.

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28

Yaakob, Nor Suhaila, Hasdianty Abdullah, Rosfarizan Mohamad, Abdul Latif Ibrahim, and Arbakariya Ariff. "3D Protein Structure Prediction of Rhodococcus UKMP-5M Phenol Hydroxylase Using Homology Modelling." Bioremediation Science and Technology Research 2, no. 1 (July 20, 2014): 1–4. http://dx.doi.org/10.54987/bstr.v2i1.58.

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The Swiss-prot data-base was used for the protein sequence of Rhodococcus UKMP-5M. BlastP was used to determine the suitable template for homology modelling. Swiss Model is the homology modelling software was used to determine the 3D structure which passed the ProQ quality test for further analysis. Validation result for the predicted structure of Rhodococcus UKMP-5M, in which the prediction structure has passed the validation test with 5.951 Lgscore. This is lies in the range of extremely good model and 0.514 MaxSub which is lies in the range of very good model.
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29

Wiltgen, Marco, and Gernot P. Tilz. "A Basic Molecular Analysis of the Diabetic Antigen GAD by Homology Modelling. Principles of the Method and Understanding of Antigenicity and Binding Sites." Pteridines 18, no. 1 (February 2007): 79–94. http://dx.doi.org/10.1515/pteridines.2007.18.1.79.

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Abstract Functional specificity of a protein is linked to its structure. A growing section of bioinformatics deals with the prediction and visualization of protein 3D structures. In homology modelling, a protein sequence with an unknown structure is aligned with sequences of known protein structures. By exploiting structural information from the known configurations, the new structure can be predicted. In this introductory paper, we will present the principles of homology modelling and demonstrate the method used, by determining the structure of the enzyme glutamic decarboxylase (GAD 65). This protein is an autoantigen involved in several human autoimmune diseases. We will illustrate the different steps in structure prediction of GAD 65 by use of two experimentally determined structures of pig kidney DOPA decarboxylase (one structure in complex with the inhibitor carbidopa) as templates. The resulting model of GAD 65 provides detailed information about the active site of the protein and selected epitopes. By analysis of the interactions between the DOPA decarboxylase with the inhibitor carbidopa, the residues of the GAD 65 active site can be identified via the sequence alignment between DOPA and GAD 65. The locations of known epitopes in the molecule are visualized in special representations giving insights into mechanisms of antigenicity. Hydrophobicity analysis gives first hints for the adherence ability of GAD 65 to the cell membrane. Homology modelling is at present one of the most efficient techniques to provide accurate structural models of proteins. It is expected that in few years, for every new determined protein sequence, at least one member with a known structure of the same protein family will be available, which will steadily increase the importance and applicability of homology modelling.
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30

Oakhill, Jonathan S., Brian J. Sutton, Andrew R. Gorringe, and Robert W. Evans. "Homology modelling of transferrin-binding protein A from Neisseria meningitidis." Protein Engineering, Design and Selection 18, no. 5 (April 8, 2005): 221–28. http://dx.doi.org/10.1093/protein/gzi024.

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31

González, Danilo, Rubén Vega, Liliana Llanos, Michel Flores, Alejandro Yévenes, and Emilio Cardemil. "ATP-DEPENDENT PHOSPHOENOLPYRUVATE CARBOXYLASES: HOMOLOGY MODELLING AND ACTIVE SITE ANALYSIS." Biochemical Society Transactions 28, no. 5 (October 1, 2000): A442. http://dx.doi.org/10.1042/bst028a442c.

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32

Venthur, Herbert, Ana Mutis, Jing-Jiang Zhou, and Andrés Quiroz. "Ligand binding and homology modelling of insect odorant-binding proteins." Physiological Entomology 39, no. 3 (August 21, 2014): 183–98. http://dx.doi.org/10.1111/phen.12066.

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33

Fazil, Mobashar Hussain Urf Turabe, Sunil Kumar, Naidu Subbarao, Haushila Prasad Pandey, and Durg Vijai Singh. "Homology modelling of a sensor histidine kinase from Aeromonas hydrophila." Journal of Molecular Modeling 16, no. 5 (October 29, 2009): 1003–9. http://dx.doi.org/10.1007/s00894-009-0602-2.

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34

Schweikardt, Thorsten, Elmar Jaenicke, and Heinz Decker. "Homology modelling of hemocyanins and tyrosinases: pitfalls in automated approaches." Micron 35, no. 1-2 (January 2004): 97–98. http://dx.doi.org/10.1016/j.micron.2003.10.030.

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35

FALLER, M. "Protein homology modelling of the B fraction of factor B." Molecular Immunology 30 (September 1993): 9. http://dx.doi.org/10.1016/0161-5890(93)90197-j.

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36

Abbondandolo, Alberto, Alessandro Portaluri, and Matthias Schwarz. "The homology of path spaces and Floer homology with conormal boundary conditions." Journal of Fixed Point Theory and Applications 4, no. 2 (December 2008): 263–93. http://dx.doi.org/10.1007/s11784-008-0097-y.

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37

Abdullah, Hasdianty, Nor Suhaila Yaacob, Mohd Fadzli Ahmad, Farah Aula Mohd Fauzi, and Abdul Latif Ibrahim. "Preliminary prediction of lipase 3D protein structure and function in <i>Rhodococcus</i> sp. NAM81 using bioinformatics approach." Bioremediation Science and Technology Research 3, no. 1 (November 2, 2015): 11–15. http://dx.doi.org/10.54987/bstr.v3i1.246.

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Protein function depends greatly on its structure. Based on this principle, it is vital to study the protein structure in order to understand its function. This study attempts to build the predicted model of lipase gene in Rhodococcus sp. NAM81 using homology modelling method. The predicted structure was then used to investigate the function of protein through several bioinformatic tools. The DNA sequence of lipase gene was obtained from the Rhodococcus sp. NAM81 genome scaffold. Blastx analysis showed 100% identity to the target enzyme andthe appropriate template for homology modelling was determined using Blastp analysis. The 3D protein structure was built using two homology modelling software, EsyPred3D and Swiss Model Server. Both structures built obtained LGScore of greater than 4, which means they are extremely good models according to ProQ validation criteria. Both structures also satisfied the Ramachandran plot structure validation analysis. The predicted structures were 100% matched with each other when superimposed with DaliLite pairwise. This shows that both structure validation servers agreed on the same model. Structure analysis using ProFunc had found seven motifs and active sites that indicate similar function of this protein with other known proteins. Thus, this study has successfully produced a good 3D protein structure for the target enzyme.
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38

Ghosh, Sayantan, and J. Febin Prabhu Dass. "Non-canonical pathway network modelling and ubiquitination site prediction through homology modelling of NF-κB." Gene 581, no. 1 (April 2016): 48–56. http://dx.doi.org/10.1016/j.gene.2016.01.025.

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39

Edelsbrunner, Herbert. "The shape of things to come in computational geometry." EU Research Spring 2023, no. 34 (April 2023): 53–55. http://dx.doi.org/10.56181/iyjl3478.

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Herbert Edelsbrunner, a pioneer of alpha shapes and persistent homology, is using these ground-breaking computational geometry ideas to empower new applications such as cancer detection and modelling.
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40

Arias-Valero, Juan Sebastián, and Emilio Lluis-Puebla. "Some remarks on hypergestural homology of spaces and its relation to classical homology." Journal of Mathematics and Music 14, no. 3 (February 27, 2020): 245–65. http://dx.doi.org/10.1080/17459737.2020.1722269.

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41

Li, Xingchun, Zhenhua Chu, Xianyuan Du, Youli Qiu, and Yu Li. "Combined molecular docking, homology modelling and density functional theory studies to modify dioxygenase to efficiently degrade aromatic hydrocarbons." RSC Advances 9, no. 20 (2019): 11465–75. http://dx.doi.org/10.1039/c8ra10663k.

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To promote the biodegradation of aromatic hydrocarbons in petroleum-contaminated soils, naphthalene dioxygenase (NDO), which is the key metabolic enzyme that degrades aromatic hydrocarbons, was modified using molecular docking and homology modelling.
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42

Bhatt, Tarun K. "Structural Characterization of Histone Deacetylase from Plasmodium Falciparum." Asian Journal of Science and Applied Technology 1, no. 2 (November 5, 2012): 28–30. http://dx.doi.org/10.51983/ajsat-2012.1.2.733.

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Histone deacetylase (HDAC) is the key enzyme responsible for epigenetic regulation of an organism. This protein has been involved in transcriptional regulation of many proteins associated with chromatin remodelling. Homologs of histone deacetylase are also found in malaria parasite Plasmodium falciparum where it plays major role in regulation of key pathways of parasite. In this study, we determined the three-dimensional structure of histone deacetylase from Plasmodium falciparum (PfHDAC) by using homology modelling tools available at Swiss Modeller server and Modweb. Modelled structure was alidated using Ramachandran plot and active site determination was performed using CASTp. We believe that structural analysis of PfHDAC could be pivotal in discovering new drug like molecules against malaria parasite.
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43

Prajapat, R., R. K. Gaur, R. Raizada, and V. K. Gupta. "In silico Analysis of Genetic Diversity of Begomovirus using Homology Modelling." Journal of Biological Sciences 10, no. 3 (March 15, 2010): 217–23. http://dx.doi.org/10.3923/jbs.2010.217.223.

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44

NAWAZ, Muhammad, Naeem IQBAL, Sobia IDREES, and Ihsan ULLAH. "DREB1A from Oryza sativa var. IR6: homology modelling and molecular docking." TURKISH JOURNAL OF BOTANY 38 (2014): 1095–102. http://dx.doi.org/10.3906/bot-1403-45.

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45

Folkers, G., J. Brünjes, M. Michael, and J. Schill. "Modelling by Homology of the HSV1-TK Sequence Embedded Structural Alignment." Journal of Receptor Research 13, no. 1-4 (January 1993): 147–62. http://dx.doi.org/10.3109/10799899309073652.

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46

Vardhini, Shailima RD. "HOMOLOGY MODELLING, VALIDATION AND DOCKING OF DFHR WITH BREAST CANCER INHIBITORS." Journal of Pharmaceutical & Scientific Innovation 3, no. 2 (April 25, 2014): 158–63. http://dx.doi.org/10.7897/2277-4572.032129.

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47

WRIGGLESWORTH, JOHN M. "The active site structure of cytochrome oxidase: Modelling by “catalytic homology”." Biochemical Society Transactions 19, no. 3 (August 1, 1991): 258S. http://dx.doi.org/10.1042/bst019258s.

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48

Claude, J. B., K. Suhre, C. Notredame, J. M. Claverie, and C. Abergel. "CaspR: a web server for automated molecular replacement using homology modelling." Nucleic Acids Research 32, Web Server (July 1, 2004): W606—W609. http://dx.doi.org/10.1093/nar/gkh400.

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49

Sahay, Archna, and Madhvi Shakya. "In silico Analysis and Homology Modelling of Antioxidant Proteins of Spinach." Journal of Proteomics & Bioinformatics 03, no. 05 (2010): 148–54. http://dx.doi.org/10.4172/jpb.1000134.

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Michalsky, E., A. Goede, and R. Preissner. "Loops In Proteins (LIP)--a comprehensive loop database for homology modelling." Protein Engineering Design and Selection 16, no. 12 (December 1, 2003): 979–85. http://dx.doi.org/10.1093/protein/gzg119.

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