Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease
The Protein Data Bank (PDB) contains over 71,000 structures. Extensively studied proteins have hundreds of submissions available, including mutations, different complexes, and space groups, allowing for application of data-mining algorithms to analyze an array of static structures and gain insight a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2012-03-01
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| Series: | Viruses |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1999-4915/4/3/348/ |
| _version_ | 1811201906675023872 |
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| author | Robert McKenna Mavis Agbandje-McKenna Miorel-Lucian Palii Balasubramanian Venkatakrishnan |
| author_facet | Robert McKenna Mavis Agbandje-McKenna Miorel-Lucian Palii Balasubramanian Venkatakrishnan |
| author_sort | Robert McKenna |
| collection | DOAJ |
| description | The Protein Data Bank (PDB) contains over 71,000 structures. Extensively studied proteins have hundreds of submissions available, including mutations, different complexes, and space groups, allowing for application of data-mining algorithms to analyze an array of static structures and gain insight about a protein’s structural variation and possibly its dynamics. This investigation is a case study of HIV protease (PR) using in-house algorithms for data mining and structure superposition through generalized formulæ that account for multiple conformations and fractional occupancies. Temperature factors (B-factors) are compared with spatial displacement from the mean structure over the entire study set and separately over bound and ligand-free structures, to assess the significance of structural deviation in a statistical context. Space group differences are also examined. |
| first_indexed | 2024-04-12T02:29:48Z |
| format | Article |
| id | doaj.art-4863db47620246a9acda1cf45aa4fbba |
| institution | Directory Open Access Journal |
| issn | 1999-4915 |
| language | English |
| last_indexed | 2024-04-12T02:29:48Z |
| publishDate | 2012-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Viruses |
| spelling | doaj.art-4863db47620246a9acda1cf45aa4fbba2022-12-22T03:51:50ZengMDPI AGViruses1999-49152012-03-014334836210.3390/v4030348Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV ProteaseRobert McKennaMavis Agbandje-McKennaMiorel-Lucian PaliiBalasubramanian VenkatakrishnanThe Protein Data Bank (PDB) contains over 71,000 structures. Extensively studied proteins have hundreds of submissions available, including mutations, different complexes, and space groups, allowing for application of data-mining algorithms to analyze an array of static structures and gain insight about a protein’s structural variation and possibly its dynamics. This investigation is a case study of HIV protease (PR) using in-house algorithms for data mining and structure superposition through generalized formulæ that account for multiple conformations and fractional occupancies. Temperature factors (B-factors) are compared with spatial displacement from the mean structure over the entire study set and separately over bound and ligand-free structures, to assess the significance of structural deviation in a statistical context. Space group differences are also examined.http://www.mdpi.com/1999-4915/4/3/348/B-factor and spatial variationdata miningHIV proteasestructure superposition |
| spellingShingle | Robert McKenna Mavis Agbandje-McKenna Miorel-Lucian Palii Balasubramanian Venkatakrishnan Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease Viruses B-factor and spatial variation data mining HIV protease structure superposition |
| title | Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease |
| title_full | Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease |
| title_fullStr | Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease |
| title_full_unstemmed | Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease |
| title_short | Mining the Protein Data Bank to Differentiate Error from Structural Variation in Clustered Static Structures: An Examination of HIV Protease |
| title_sort | mining the protein data bank to differentiate error from structural variation in clustered static structures an examination of hiv protease |
| topic | B-factor and spatial variation data mining HIV protease structure superposition |
| url | http://www.mdpi.com/1999-4915/4/3/348/ |
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