{"id":"https://openalex.org/W4387451333","doi":"https://doi.org/10.1038/s42256-023-00721-6","title":"A method for multiple-sequence-alignment-free protein structure prediction using a protein language model","display_name":"A method for multiple-sequence-alignment-free protein structure prediction using a protein language model","publication_year":2023,"publication_date":"2023-10-09","ids":{"openalex":"https://openalex.org/W4387451333","doi":"https://doi.org/10.1038/s42256-023-00721-6"},"language":"en","primary_location":{"id":"doi:10.1038/s42256-023-00721-6","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-023-00721-6","pdf_url":"https://www.nature.com/articles/s42256-023-00721-6.pdf","source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.nature.com/articles/s42256-023-00721-6.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072385246","display_name":"Xiaomin Fang","orcid":"https://orcid.org/0000-0002-7563-5268"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaomin Fang","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380524","display_name":"Fan Wang","orcid":"https://orcid.org/0000-0002-5373-4302"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Wang","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-5373-4302","affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086931226","display_name":"Lihang Liu","orcid":"https://orcid.org/0009-0003-5815-1047"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihang Liu","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-5815-1047","affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109583536","display_name":"Jingzhou He","orcid":null},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingzhou He","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108737864","display_name":"Dayong Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dayong Lin","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044309879","display_name":"Yingfei Xiang","orcid":"https://orcid.org/0000-0002-4505-7735"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfei Xiang","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4505-7735","affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074137196","display_name":"Kunrui Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunrui Zhu","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441245","display_name":"Xiaonan Zhang","orcid":"https://orcid.org/0000-0003-4359-9079"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaonan Zhang","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015314503","display_name":"Hua Wu","orcid":"https://orcid.org/0000-0002-2805-4612"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Wu","raw_affiliation_strings":["Baidu Inc., NLP, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc., NLP, Shenzhen, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423946","display_name":"Hui Li","orcid":"https://orcid.org/0000-0003-0580-7033"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hui Li","raw_affiliation_strings":["BioMap, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BioMap, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030589527","display_name":"Le Song","orcid":"https://orcid.org/0000-0002-9655-2787"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Le Song","raw_affiliation_strings":["BioMap, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9655-2787","affiliations":[{"raw_affiliation_string":"BioMap, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5072385246"],"corresponding_institution_ids":["https://openalex.org/I98301712"],"apc_list":{"value":9750,"currency":"EUR","value_usd":11690},"apc_paid":{"value":9750,"currency":"EUR","value_usd":11690},"fwci":13.3226,"has_fulltext":true,"cited_by_count":90,"citation_normalized_percentile":{"value":0.99243194,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"5","issue":"10","first_page":"1087","last_page":"1096"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7482700347900391},{"id":"https://openalex.org/keywords/protein-structure-prediction","display_name":"Protein structure prediction","score":0.6198037266731262},{"id":"https://openalex.org/keywords/casp","display_name":"CASP","score":0.6176571846008301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5255352854728699},{"id":"https://openalex.org/keywords/protein-structure","display_name":"Protein structure","score":0.46168985962867737},{"id":"https://openalex.org/keywords/protein-superfamily","display_name":"Protein superfamily","score":0.4613701105117798},{"id":"https://openalex.org/keywords/threading","display_name":"Threading (protein sequence)","score":0.454702228307724},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4442219138145447},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43187665939331055},{"id":"https://openalex.org/keywords/protein-sequencing","display_name":"Protein sequencing","score":0.41778427362442017},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3470965623855591},{"id":"https://openalex.org/keywords/peptide-sequence","display_name":"Peptide sequence","score":0.1760844588279724}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7482700347900391},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.6198037266731262},{"id":"https://openalex.org/C66153294","wikidata":"https://www.wikidata.org/wiki/Q899291","display_name":"CASP","level":4,"score":0.6176571846008301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5255352854728699},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.46168985962867737},{"id":"https://openalex.org/C178180057","wikidata":"https://www.wikidata.org/wiki/Q7251477","display_name":"Protein superfamily","level":3,"score":0.4613701105117798},{"id":"https://openalex.org/C200307862","wikidata":"https://www.wikidata.org/wiki/Q7797175","display_name":"Threading (protein sequence)","level":3,"score":0.454702228307724},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4442219138145447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43187665939331055},{"id":"https://openalex.org/C10010492","wikidata":"https://www.wikidata.org/wiki/Q3142557","display_name":"Protein sequencing","level":4,"score":0.41778427362442017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3470965623855591},{"id":"https://openalex.org/C167625842","wikidata":"https://www.wikidata.org/wiki/Q899763","display_name":"Peptide sequence","level":3,"score":0.1760844588279724},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s42256-023-00721-6","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-023-00721-6","pdf_url":"https://www.nature.com/articles/s42256-023-00721-6.pdf","source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s42256-023-00721-6","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s42256-023-00721-6","pdf_url":"https://www.nature.com/articles/s42256-023-00721-6.pdf","source":{"id":"https://openalex.org/S2912241403","display_name":"Nature Machine Intelligence","issn_l":"2522-5839","issn":["2522-5839"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nature Machine Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387451333.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1987134040","https://openalex.org/W2073758233","https://openalex.org/W2102461176","https://openalex.org/W2130479394","https://openalex.org/W2152811165","https://openalex.org/W2161151688","https://openalex.org/W2557595285","https://openalex.org/W2747329762","https://openalex.org/W2970476646","https://openalex.org/W2997234557","https://openalex.org/W3104537585","https://openalex.org/W3111174583","https://openalex.org/W3133458480","https://openalex.org/W3146944767","https://openalex.org/W3171848268","https://openalex.org/W3177828909","https://openalex.org/W3186179742","https://openalex.org/W3191761521","https://openalex.org/W3193271391","https://openalex.org/W3193589100","https://openalex.org/W3198923619","https://openalex.org/W3211795435","https://openalex.org/W3212854871","https://openalex.org/W4281291878","https://openalex.org/W4287724045","https://openalex.org/W4313430582","https://openalex.org/W6739901393","https://openalex.org/W6763868836","https://openalex.org/W6778883912","https://openalex.org/W6894159261"],"related_works":["https://openalex.org/W2411998238","https://openalex.org/W2462594639","https://openalex.org/W2136856901","https://openalex.org/W1888349473","https://openalex.org/W2117340986","https://openalex.org/W2335447195","https://openalex.org/W2159298533","https://openalex.org/W2920908742","https://openalex.org/W3000866803","https://openalex.org/W2005312858"],"abstract_inverted_index":{"Abstract":[0],"Protein":[1],"structure":[2,61,187],"prediction":[3,62],"pipelines":[4,18,184],"based":[5],"on":[6,21,157,169],"artificial":[7],"intelligence,":[8],"such":[9],"as":[10,26,112],"AlphaFold2,":[11,135],"have":[12],"achieved":[13],"near-experimental":[14],"accuracy.":[15],"These":[16],"advanced":[17],"mainly":[19],"rely":[20],"multiple":[22],"sequence":[23],"alignments":[24],"(MSAs)":[25],"inputs":[27],"to":[28,54,115,142],"learn":[29],"the":[30,34,56,81,104,119,125,131,144,151,166,182],"co-evolution":[31,120],"information":[32],"from":[33,40,149],"homologous":[35,173],"sequences.":[36],"Nonetheless,":[37],"searching":[38],"MSAs":[39,116],"protein":[41,60,77,93,127,186],"databases":[42],"is":[43,155],"time":[44,180],"consuming,":[45],"usually":[46],"taking":[47],"tens":[48],"of":[49,58,68,86,98,100,134,147],"minutes.":[50],"Consequently,":[51],"we":[52,136],"attempt":[53],"explore":[55],"limits":[57],"fast":[59],"by":[63,123],"using":[64],"only":[65,150],"primary":[66,101,152],"structures":[67,102],"proteins.":[69],"Our":[70],"proposed":[71],"method,":[72],"HelixFold-Single,":[73],"combines":[74],"a":[75,91],"large-scale":[76,92],"language":[78,94,128],"model":[79,95,129,141],"with":[80,96,165,171],"superior":[82],"geometric":[83],"learning":[84,106,118],"capability":[85],"AlphaFold2.":[87],"HelixFold-Single":[88,154,176],"first":[89],"pre-trains":[90],"thousands":[97],"millions":[99],"utilizing":[103],"self-supervised":[105],"paradigm,":[107],"which":[108],"will":[109],"be":[110],"used":[111],"an":[113,138],"alternative":[114],"for":[117,185],"information.":[121],"Then,":[122],"combining":[124],"pre-trained":[126],"and":[130,160],"essential":[132],"components":[133],"obtain":[137],"end-to-end":[139],"differentiable":[140],"predict":[143],"three-dimensional":[145],"coordinates":[146],"atoms":[148],"structure.":[153],"validated":[156],"datasets":[158],"CASP14":[159],"CAMEO,":[161],"achieving":[162],"competitive":[163],"accuracy":[164],"MSA-based":[167],"methods":[168],"targets":[170],"large":[172],"families.":[174],"Furthermore,":[175],"consumes":[177],"much":[178],"less":[179],"than":[181],"mainstream":[183],"prediction,":[188],"demonstrating":[189],"its":[190],"potential":[191],"in":[192],"tasks":[193],"requiring":[194],"many":[195],"predictions.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":14},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":43},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2023-10-10T00:00:00"}
