Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo]
The protein sequence space is vast and diverse, spanning across different families. Biologically meaningful relationships exist between proteins at superfamily level. However, it is highly challenging to establish convincing relationships at the superfamily level by means of simple sequence searches...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
F1000 Research Ltd
2014-07-01
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| Series: | F1000Research |
| Subjects: | |
| Online Access: | http://f1000research.com/articles/2-93/v2 |
| _version_ | 1811336969516482560 |
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| author | Adwait Govind Joshi Upadhyayula Surya Raghavender Ramanathan Sowdhamini |
| author_facet | Adwait Govind Joshi Upadhyayula Surya Raghavender Ramanathan Sowdhamini |
| author_sort | Adwait Govind Joshi |
| collection | DOAJ |
| description | The protein sequence space is vast and diverse, spanning across different families. Biologically meaningful relationships exist between proteins at superfamily level. However, it is highly challenging to establish convincing relationships at the superfamily level by means of simple sequence searches. It is necessary to design a rigorous sequence search strategy to establish remote homology relationships and achieve high coverage. We have used iterative profile-based methods, along with constraints of sequence motifs, to specify search directions. We address the importance of multiple start points (queries) to achieve high coverage at protein superfamily level. We have devised strategies to employ a structural regime to search sequence space with good specificity and sensitivity. We employ two well-known sequence search methods, PSI-BLAST and PHI-BLAST, with multiple queries and multiple patterns to enhance homologue identification at the structural superfamily level. The study suggests that multiple queries improve sensitivity, while a pattern-constrained iterative sequence search becomes stringent at the initial stages, thereby driving the search in a specific direction and also achieves high coverage. This data mining approach has been applied to the entire structural superfamily database. |
| first_indexed | 2024-04-13T17:47:17Z |
| format | Article |
| id | doaj.art-bd36fe6561e9499db9a8452386a62996 |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-04-13T17:47:17Z |
| publishDate | 2014-07-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-bd36fe6561e9499db9a8452386a629962022-12-22T02:36:53ZengF1000 Research LtdF1000Research2046-14022014-07-01210.12688/f1000research.2-93.v24848Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo]Adwait Govind Joshi0Upadhyayula Surya Raghavender1Ramanathan Sowdhamini2Manipal University, Manipal, Karnataka, 576104, IndiaNational Centre for Biological Sciences (Tata Institute of Fundamental Research), Gandhi Krishi Vignyan Kendra Campus, Bangalore, 560065, IndiaNational Centre for Biological Sciences (Tata Institute of Fundamental Research), Gandhi Krishi Vignyan Kendra Campus, Bangalore, 560065, IndiaThe protein sequence space is vast and diverse, spanning across different families. Biologically meaningful relationships exist between proteins at superfamily level. However, it is highly challenging to establish convincing relationships at the superfamily level by means of simple sequence searches. It is necessary to design a rigorous sequence search strategy to establish remote homology relationships and achieve high coverage. We have used iterative profile-based methods, along with constraints of sequence motifs, to specify search directions. We address the importance of multiple start points (queries) to achieve high coverage at protein superfamily level. We have devised strategies to employ a structural regime to search sequence space with good specificity and sensitivity. We employ two well-known sequence search methods, PSI-BLAST and PHI-BLAST, with multiple queries and multiple patterns to enhance homologue identification at the structural superfamily level. The study suggests that multiple queries improve sensitivity, while a pattern-constrained iterative sequence search becomes stringent at the initial stages, thereby driving the search in a specific direction and also achieves high coverage. This data mining approach has been applied to the entire structural superfamily database.http://f1000research.com/articles/2-93/v2Bioinformatics |
| spellingShingle | Adwait Govind Joshi Upadhyayula Surya Raghavender Ramanathan Sowdhamini Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo] F1000Research Bioinformatics |
| title | Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo] |
| title_full | Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo] |
| title_fullStr | Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo] |
| title_full_unstemmed | Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo] |
| title_short | Improved performance of sequence search approaches in remote homology detection [v2; ref status: indexed, http://f1000r.es/3qo] |
| title_sort | improved performance of sequence search approaches in remote homology detection v2 ref status indexed http f1000r es 3qo |
| topic | Bioinformatics |
| url | http://f1000research.com/articles/2-93/v2 |
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