Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB)
Loops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformat...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2007-01-01
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| Series: | Bioinformatics and Biology Insights |
| Subjects: | |
| Online Access: | http://la-press.com/article.php?article_id=503 |
| _version_ | 1811280001526398976 |
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| author | Antoni Hermoso Jordi Espadaler Enrique Querol, E Francesc X. Aviles Michael J.E. Sternberg Baldomero Oliva Narcis Fernandez-Fuentes |
| author_facet | Antoni Hermoso Jordi Espadaler Enrique Querol, E Francesc X. Aviles Michael J.E. Sternberg Baldomero Oliva Narcis Fernandez-Fuentes |
| author_sort | Antoni Hermoso |
| collection | DOAJ |
| description | Loops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformation of loops remains problematic. Here, we present a structural classification of loops, ArchDB, a mine of information with application in both mentioned fields: loop structure prediction and function prediction. ArchDB (http://sbi.imim.es/archdb) is a database of classified protein loop motifs. The current database provides four different classification sets tailored for different purposes. ArchDB-40, a loop classification derived from SCOP40, well suited for modeling common loop motifs. Since features relevant to loop structure or function can be more easily determined on well-populated clusters, we have developed ArchDB-95, a loop classification derived from SCOP95. This new classification set shows a ∼40% increase in the number of subclasses, and a large 7-fold increase in the number of putative structure/function-related subclasses. We also present ArchDB-EC, a classification of loop motifs from enzymes, and ArchDB-KI, a manually annotated classification of loop motifs from kinases. Information about ligand contacts and PDB sites has been included in all classification sets. Improvements in our classification scheme are described, as well as several new database features, such as the ability to query by conserved annotations, sequence similarity, or uploading 3D coordinates of a protein. The lengths of classified loops range between 0 and 36 residues long. ArchDB offers an exhaustive sampling of loop structures. Functional information about loops and links with related biological databases are also provided. All this information and the possibility to browse/query the database through a web-server outline an useful tool with application in the comparative study of loops, the analysis of loops involved in protein function and to obtain templates for loop modeling. |
| first_indexed | 2024-04-13T01:07:01Z |
| format | Article |
| id | doaj.art-b766df59cae04a38b1e5410dcd2c1399 |
| institution | Directory Open Access Journal |
| issn | 1177-9322 |
| language | English |
| last_indexed | 2024-04-13T01:07:01Z |
| publishDate | 2007-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Bioinformatics and Biology Insights |
| spelling | doaj.art-b766df59cae04a38b1e5410dcd2c13992022-12-22T03:09:20ZengSAGE PublishingBioinformatics and Biology Insights1177-93222007-01-0117790Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB)Antoni HermosoJordi EspadalerEnrique Querol, EFrancesc X. AvilesMichael J.E. SternbergBaldomero OlivaNarcis Fernandez-FuentesLoops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformation of loops remains problematic. Here, we present a structural classification of loops, ArchDB, a mine of information with application in both mentioned fields: loop structure prediction and function prediction. ArchDB (http://sbi.imim.es/archdb) is a database of classified protein loop motifs. The current database provides four different classification sets tailored for different purposes. ArchDB-40, a loop classification derived from SCOP40, well suited for modeling common loop motifs. Since features relevant to loop structure or function can be more easily determined on well-populated clusters, we have developed ArchDB-95, a loop classification derived from SCOP95. This new classification set shows a ∼40% increase in the number of subclasses, and a large 7-fold increase in the number of putative structure/function-related subclasses. We also present ArchDB-EC, a classification of loop motifs from enzymes, and ArchDB-KI, a manually annotated classification of loop motifs from kinases. Information about ligand contacts and PDB sites has been included in all classification sets. Improvements in our classification scheme are described, as well as several new database features, such as the ability to query by conserved annotations, sequence similarity, or uploading 3D coordinates of a protein. The lengths of classified loops range between 0 and 36 residues long. ArchDB offers an exhaustive sampling of loop structures. Functional information about loops and links with related biological databases are also provided. All this information and the possibility to browse/query the database through a web-server outline an useful tool with application in the comparative study of loops, the analysis of loops involved in protein function and to obtain templates for loop modeling.http://la-press.com/article.php?article_id=503function annotationloop structure classificationloop modeling |
| spellingShingle | Antoni Hermoso Jordi Espadaler Enrique Querol, E Francesc X. Aviles Michael J.E. Sternberg Baldomero Oliva Narcis Fernandez-Fuentes Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) Bioinformatics and Biology Insights function annotation loop structure classification loop modeling |
| title | Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) |
| title_full | Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) |
| title_fullStr | Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) |
| title_full_unstemmed | Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) |
| title_short | Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB) |
| title_sort | including functional annotations and extending the collection of structural classifications of protein loops archdb |
| topic | function annotation loop structure classification loop modeling |
| url | http://la-press.com/article.php?article_id=503 |
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