{"doi":"10.1093/bioinformatics/btl382","title":"Identification of function-associated loop motifs and application to protein function prediction","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>Motivation: The detection of function-related local 3D-motifs in protein structures can provide insights towards protein function in absence of sequence or fold similarity. Protein loops are known to play important roles in protein function and several loop classifications have been described, but the automated identification of putative functional 3D-motifs in such classifications has not yet been addressed. This identification can be used on sequence annotations.</jats:p>\n               <jats:p>Results: We evaluated three different scoring methods for their ability to identify known motifs from the PROSITE database in ArchDB. More than 500 new putative function-related motifs not reported in PROSITE were identified. Sequence patterns derived from these motifs were especially useful at predicting precise annotations. The number of reliable sequence annotations could be increased up to 100% with respect to standard BLAST.</jats:p>\n               <jats:p>Contact:  boliva@imim.es</jats:p>\n               <jats:p>Supplementary information: Supplementary Data are available at Bioinformatics online.</jats:p>","journal":"Bioinformatics","year":2006,"id":15732,"datarank":1.9412926273268625,"base_score":3.970291913552122,"endowment":3.970291913552122,"self_citation_contribution":0.5955437870328184,"citation_network_contribution":1.345748840294044,"self_endowment_contribution":0.5955437870328184,"citer_contribution":1.345748840294044,"corpus_percentile":null,"corpus_rank":null,"citation_count":52,"citer_count":46,"citers_with_citation_signal":37,"citers_with_endowment":37,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":118904,"name":"Enrique Querol","orcid":null,"position":1,"is_corresponding":false},{"id":118905,"name":"Francesc X. Aviles","orcid":null,"position":2,"is_corresponding":false},{"id":118906,"name":"Baldo Oliva","orcid":null,"position":3,"is_corresponding":false},{"id":118903,"name":"Jordi Espadaler","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":3.970291913552122,"endowment":3.970291913552122,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"16870939","pmcid":null,"openalex_id":"https://openalex.org/W2082535576","authors":[],"funders":[],"total_grants":0,"fwci":1.2267,"citation_percentile":0.77365923,"influential_citations":1,"citation_trend":[{"year":2012,"count":1},{"year":2013,"count":2},{"year":2014,"count":2},{"year":2015,"count":2},{"year":2016,"count":4},{"year":2017,"count":1},{"year":2018,"count":1},{"year":2020,"count":1},{"year":2021,"count":6},{"year":2022,"count":3},{"year":2023,"count":5},{"year":2024,"count":2},{"year":2025,"count":5},{"year":2026,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://academic.oup.com/bioinformatics/article-pdf/22/18/2237/904161/btl382.pdf","host_type":"BRONZE"},{"url":"https://academic.oup.com/bioinformatics/article-pdf/22/18/2237/48840964/bioinformatics_22_18_2237.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1093/bioinformatics/btl382","host_type":"journal"}],"fields_of_study":["Protein Structure and Dynamics","Machine Learning in Bioinformatics","Enzyme Structure and Function","Biology","Computer Science","Medicine","Amino Acid Sequence","Computer Simulation","Models, Biological","Models, Chemical","Models, Molecular","Molecular Sequence Data","Protein Conformation","Proteins","Sequence Alignment","Sequence Analysis, Protein","Structure-Activity Relationship"],"mesh_terms":["Proteins","Sequence Alignment","Sequence Analysis, Protein","Amino Acid Sequence","Protein Conformation","Structure-Activity Relationship","Models, Biological","Models, Chemical","Models, Molecular","Computer Simulation","Molecular Sequence Data"],"keywords":["Computational biology","Protein function prediction","Function (biology)","Protein function","Identification (biology)","Sequence (biology)","Protein sequencing","Sequence motif","Sequence alignment","Computer science","Biology","Data mining","Bioinformatics","Peptide sequence","Genetics","Gene"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-01T18:48:10.980716Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}