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Article: NdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities

TitleNdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities
Authors
Issue Date2005
Citation
Proteins: Structure, Function And Genetics, 2005, v. 58 n. 3, p. 628-637 How to Cite?
AbstractSequence 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 Identifierhttp://hdl.handle.net/10722/147500
ISSN
2015 Impact Factor: 2.499
2015 SCImago Journal Rankings: 1.383
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Jen_US
dc.contributor.authorFeng, JAen_US
dc.date.accessioned2012-05-29T06:04:09Z-
dc.date.available2012-05-29T06:04:09Z-
dc.date.issued2005en_US
dc.identifier.citationProteins: Structure, Function And Genetics, 2005, v. 58 n. 3, p. 628-637en_US
dc.identifier.issn0887-3585en_US
dc.identifier.urihttp://hdl.handle.net/10722/147500-
dc.description.abstractSequence 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.languageengen_US
dc.relation.ispartofProteins: Structure, Function and Geneticsen_US
dc.subject.meshAlgorithmsen_US
dc.subject.meshAmino Acid Sequenceen_US
dc.subject.meshAmino Acidsen_US
dc.subject.meshBase Sequenceen_US
dc.subject.meshComputational Biology - Methodsen_US
dc.subject.meshDatabases, Factualen_US
dc.subject.meshDatabases, Proteinen_US
dc.subject.meshInterneten_US
dc.subject.meshModels, Molecularen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshMolecular Sequence Dataen_US
dc.subject.meshProtein Conformationen_US
dc.subject.meshProtein Structure, Secondaryen_US
dc.subject.meshProteins - Chemistryen_US
dc.subject.meshProteomics - Methodsen_US
dc.subject.meshRhodopseudomonas - Metabolismen_US
dc.subject.meshSequence Alignmenten_US
dc.subject.meshSequence Analysis, Proteinen_US
dc.subject.meshSequence Homology, Amino Aciden_US
dc.titleNdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensitiesen_US
dc.typeArticleen_US
dc.identifier.emailWang, J:junwen@hkucc.hku.hken_US
dc.identifier.authorityWang, J=rp00280en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1002/prot.20359en_US
dc.identifier.pmid15616964-
dc.identifier.scopuseid_2-s2.0-12944288129en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-12944288129&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume58en_US
dc.identifier.issue3en_US
dc.identifier.spage628en_US
dc.identifier.epage637en_US
dc.identifier.isiWOS:000226695900012-
dc.identifier.scopusauthoridWang, J=8950599500en_US
dc.identifier.scopusauthoridFeng, JA=7403884662en_US

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