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Structural Annotation of Mycobacterium tuberculosis Proteome

Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a s...

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Autores principales: Anand, Praveen, Sankaran, Sandhya, Mukherjee, Sumanta, Yeturu, Kalidas, Laskowski, Roman, Bhardwaj, Anshu, Bhagavat, Raghu, Brahmachari, Samir K., Chandra, Nagasuma
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205055/
https://www.ncbi.nlm.nih.gov/pubmed/22073123
http://dx.doi.org/10.1371/journal.pone.0027044
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author Anand, Praveen
Sankaran, Sandhya
Mukherjee, Sumanta
Yeturu, Kalidas
Laskowski, Roman
Bhardwaj, Anshu
Bhagavat, Raghu
Brahmachari, Samir K.
Chandra, Nagasuma
author_facet Anand, Praveen
Sankaran, Sandhya
Mukherjee, Sumanta
Yeturu, Kalidas
Laskowski, Roman
Bhardwaj, Anshu
Bhagavat, Raghu
Brahmachari, Samir K.
Chandra, Nagasuma
author_sort Anand, Praveen
collection PubMed
description Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well.
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spelling pubmed-32050552011-11-09 Structural Annotation of Mycobacterium tuberculosis Proteome Anand, Praveen Sankaran, Sandhya Mukherjee, Sumanta Yeturu, Kalidas Laskowski, Roman Bhardwaj, Anshu Bhagavat, Raghu Brahmachari, Samir K. Chandra, Nagasuma PLoS One Research Article Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB) H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation), being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well. Public Library of Science 2011-10-31 /pmc/articles/PMC3205055/ /pubmed/22073123 http://dx.doi.org/10.1371/journal.pone.0027044 Text en Anand et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Anand, Praveen
Sankaran, Sandhya
Mukherjee, Sumanta
Yeturu, Kalidas
Laskowski, Roman
Bhardwaj, Anshu
Bhagavat, Raghu
Brahmachari, Samir K.
Chandra, Nagasuma
Structural Annotation of Mycobacterium tuberculosis Proteome
title Structural Annotation of Mycobacterium tuberculosis Proteome
title_full Structural Annotation of Mycobacterium tuberculosis Proteome
title_fullStr Structural Annotation of Mycobacterium tuberculosis Proteome
title_full_unstemmed Structural Annotation of Mycobacterium tuberculosis Proteome
title_short Structural Annotation of Mycobacterium tuberculosis Proteome
title_sort structural annotation of mycobacterium tuberculosis proteome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3205055/
https://www.ncbi.nlm.nih.gov/pubmed/22073123
http://dx.doi.org/10.1371/journal.pone.0027044
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