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- Publisher Website: 10.1002/prot.20359
- Scopus: eid_2-s2.0-12944288129
- PMID: 15616964
- WOS: WOS:000226695900012
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Article: NdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities
Title | NdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities |
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Authors | |
Keywords | Propensity Protein structures Secondary structure Sequence alignment Sequence pattern |
Issue Date | 2005 |
Citation | Proteins: Structure, Function And Genetics, 2005, v. 58 n. 3, p. 628-637 How to Cite? |
Abstract | Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. © 2004 Wiley-Liss, Inc. |
Persistent Identifier | http://hdl.handle.net/10722/147500 |
ISSN | 2023 Impact Factor: 3.2 2023 SCImago Journal Rankings: 1.086 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, J | en_US |
dc.contributor.author | Feng, JA | en_US |
dc.date.accessioned | 2012-05-29T06:04:09Z | - |
dc.date.available | 2012-05-29T06:04:09Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.citation | Proteins: Structure, Function And Genetics, 2005, v. 58 n. 3, p. 628-637 | en_US |
dc.identifier.issn | 0887-3585 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/147500 | - |
dc.description.abstract | Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. © 2004 Wiley-Liss, Inc. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Proteins: Structure, Function and Genetics | en_US |
dc.subject | Propensity | - |
dc.subject | Protein structures | - |
dc.subject | Secondary structure | - |
dc.subject | Sequence alignment | - |
dc.subject | Sequence pattern | - |
dc.subject.mesh | Algorithms | en_US |
dc.subject.mesh | Amino Acid Sequence | en_US |
dc.subject.mesh | Amino Acids | en_US |
dc.subject.mesh | Base Sequence | en_US |
dc.subject.mesh | Computational Biology - Methods | en_US |
dc.subject.mesh | Databases, Factual | en_US |
dc.subject.mesh | Databases, Protein | en_US |
dc.subject.mesh | Internet | en_US |
dc.subject.mesh | Models, Molecular | en_US |
dc.subject.mesh | Models, Statistical | en_US |
dc.subject.mesh | Molecular Sequence Data | en_US |
dc.subject.mesh | Protein Conformation | en_US |
dc.subject.mesh | Protein Structure, Secondary | en_US |
dc.subject.mesh | Proteins - Chemistry | en_US |
dc.subject.mesh | Proteomics - Methods | en_US |
dc.subject.mesh | Rhodopseudomonas - Metabolism | en_US |
dc.subject.mesh | Sequence Alignment | en_US |
dc.subject.mesh | Sequence Analysis, Protein | en_US |
dc.subject.mesh | Sequence Homology, Amino Acid | en_US |
dc.title | NdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities | en_US |
dc.type | Article | en_US |
dc.identifier.email | Wang, J:junwen@hkucc.hku.hk | en_US |
dc.identifier.authority | Wang, J=rp00280 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1002/prot.20359 | en_US |
dc.identifier.pmid | 15616964 | - |
dc.identifier.scopus | eid_2-s2.0-12944288129 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-12944288129&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 58 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.spage | 628 | en_US |
dc.identifier.epage | 637 | en_US |
dc.identifier.isi | WOS:000226695900012 | - |
dc.identifier.scopusauthorid | Wang, J=8950599500 | en_US |
dc.identifier.scopusauthorid | Feng, JA=7403884662 | en_US |
dc.identifier.issnl | 0887-3585 | - |