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Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis
Carnivorous plants represent a so far underexploited reservoir of novel proteases with potentially useful activities. Here we investigate 44 cysteine proteases from the Cape sundew, Drosera capensis, predicted from genomic DNA sequences. D. capensis has a large number of cysteine protease genes; ana...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949590/ https://www.ncbi.nlm.nih.gov/pubmed/27471585 http://dx.doi.org/10.1016/j.csbj.2016.05.003 |
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author | Butts, Carter T. Zhang, Xuhong Kelly, John E. Roskamp, Kyle W. Unhelkar, Megha H. Freites, J. Alfredo Tahir, Seemal Martin, Rachel W. |
author_facet | Butts, Carter T. Zhang, Xuhong Kelly, John E. Roskamp, Kyle W. Unhelkar, Megha H. Freites, J. Alfredo Tahir, Seemal Martin, Rachel W. |
author_sort | Butts, Carter T. |
collection | PubMed |
description | Carnivorous plants represent a so far underexploited reservoir of novel proteases with potentially useful activities. Here we investigate 44 cysteine proteases from the Cape sundew, Drosera capensis, predicted from genomic DNA sequences. D. capensis has a large number of cysteine protease genes; analysis of their sequences reveals homologs of known plant proteases, some of which are predicted to have novel properties. Many functionally significant sequence and structural features are observed, including targeting signals and occluding loops. Several of the proteases contain a new type of granulin domain. Although active site residues are conserved, the sequence identity of these proteases to known proteins is moderate to low; therefore, comparative modeling with all-atom refinement and subsequent atomistic MD-simulation is used to predict their 3D structures. The structure prediction data, as well as analysis of protein structure networks, suggest multifarious variations on the papain-like cysteine protease structural theme. This in silico methodology provides a general framework for investigating a large pool of sequences that are potentially useful for biotechnology applications, enabling informed choices about which proteins to investigate in the laboratory. |
format | Online Article Text |
id | pubmed-4949590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-49495902016-07-28 Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis Butts, Carter T. Zhang, Xuhong Kelly, John E. Roskamp, Kyle W. Unhelkar, Megha H. Freites, J. Alfredo Tahir, Seemal Martin, Rachel W. Comput Struct Biotechnol J Research Article Carnivorous plants represent a so far underexploited reservoir of novel proteases with potentially useful activities. Here we investigate 44 cysteine proteases from the Cape sundew, Drosera capensis, predicted from genomic DNA sequences. D. capensis has a large number of cysteine protease genes; analysis of their sequences reveals homologs of known plant proteases, some of which are predicted to have novel properties. Many functionally significant sequence and structural features are observed, including targeting signals and occluding loops. Several of the proteases contain a new type of granulin domain. Although active site residues are conserved, the sequence identity of these proteases to known proteins is moderate to low; therefore, comparative modeling with all-atom refinement and subsequent atomistic MD-simulation is used to predict their 3D structures. The structure prediction data, as well as analysis of protein structure networks, suggest multifarious variations on the papain-like cysteine protease structural theme. This in silico methodology provides a general framework for investigating a large pool of sequences that are potentially useful for biotechnology applications, enabling informed choices about which proteins to investigate in the laboratory. Research Network of Computational and Structural Biotechnology 2016-06-14 /pmc/articles/PMC4949590/ /pubmed/27471585 http://dx.doi.org/10.1016/j.csbj.2016.05.003 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Butts, Carter T. Zhang, Xuhong Kelly, John E. Roskamp, Kyle W. Unhelkar, Megha H. Freites, J. Alfredo Tahir, Seemal Martin, Rachel W. Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis |
title | Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis |
title_full | Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis |
title_fullStr | Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis |
title_full_unstemmed | Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis |
title_short | Sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the Cape sundew, Drosera capensis |
title_sort | sequence comparison, molecular modeling, and network analysis predict structural diversity in cysteine proteases from the cape sundew, drosera capensis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949590/ https://www.ncbi.nlm.nih.gov/pubmed/27471585 http://dx.doi.org/10.1016/j.csbj.2016.05.003 |
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