{"id":"https://openalex.org/W7224221680","doi":"https://doi.org/10.64898/2026.10.23.761317","title":"NK-RCPP: a receptor-conditioned computational workflow for prioritizing neurokinin-receptor peptide candidates","display_name":"NK-RCPP: a receptor-conditioned computational workflow for prioritizing neurokinin-receptor peptide candidates","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224221680","doi":"https://doi.org/10.64898/2026.10.23.761317"},"language":"en","primary_location":{"id":"doi:10.64898/2026.10.23.761317","doi":"https://doi.org/10.64898/2026.10.23.761317","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.10.23.761317","pdf_url":"https://www.biorxiv.org/content/biorxiv/early/2026/10/28/2026.10.23.761317.full.pdf","source":{"id":"https://openalex.org/S4306402567","display_name":"bioRxiv (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"bioRxiv","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.biorxiv.org/content/biorxiv/early/2026/10/28/2026.10.23.761317.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160144792","display_name":"Xiaosong Zhou","orcid":"https://orcid.org/0009-0008-8629-3786","observed_orcids":["https://orcid.org/0009-0008-8629-3786"]},"institutions":[{"id":"https://openalex.org/I130343225","display_name":"Universiti Putra Malaysia","ror":"https://ror.org/02e91jd64","country_code":"MY","type":"education","lineage":["https://openalex.org/I130343225"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Xiaosong Zhou","raw_affiliation_strings":["Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia"],"raw_orcid":"https://orcid.org/0009-0008-8629-3786","affiliations":[{"raw_affiliation_string":"Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia","institution_ids":["https://openalex.org/I130343225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101851959","display_name":"Yuli Zhang","orcid":"https://orcid.org/0000-0001-6267-4244","observed_orcids":["https://orcid.org/0000-0001-6267-4244","https://orcid.org/0009-0009-3685-8360"]},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haohong Zhang","raw_affiliation_strings":["Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0001-6267-4244","affiliations":[{"raw_affiliation_string":"Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076346443","display_name":"Kang Ning","orcid":"https://orcid.org/0000-0003-3325-5387","observed_orcids":["https://orcid.org/0000-0003-3325-5387","https://orcid.org/0000-0002-5628-8555"]},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kang Ning","raw_affiliation_strings":["Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0003-3325-5387","affiliations":[{"raw_affiliation_string":"Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076346443"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.6859999895095825,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.6859999895095825,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10911","display_name":"Chemical Synthesis and Analysis","score":0.17870000004768372,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11178","display_name":"Receptor Mechanisms and Signaling","score":0.04659999907016754,"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/neurokinin-receptors","display_name":"neurokinin receptors","score":0.9020000100135803},{"id":"https://openalex.org/keywords/neurokinin-1-receptor","display_name":"neurokinin-1 receptor","score":0.7609999775886536},{"id":"https://openalex.org/keywords/nk2-receptor","display_name":"NK2 receptor","score":1.0},{"id":"https://openalex.org/keywords/nk3-receptor","display_name":"NK3 receptor","score":1.0},{"id":"https://openalex.org/keywords/g-protein-coupled-receptors","display_name":"G protein-coupled receptors","score":0.8840000033378601}],"concepts":[{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.7856000065803528},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.5878000259399414},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5241000056266785},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46709999442100525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45649999380111694},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.43160000443458557},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3625999987125397},{"id":"https://openalex.org/C3018260909","wikidata":"https://www.wikidata.org/wiki/Q1322871","display_name":"Exploratory analysis","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30799999833106995},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27950000762939453},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2793000042438507},{"id":"https://openalex.org/C2779281246","wikidata":"https://www.wikidata.org/wiki/Q172847","display_name":"Peptide","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.64898/2026.10.23.761317","doi":"https://doi.org/10.64898/2026.10.23.761317","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.10.23.761317","pdf_url":"https://www.biorxiv.org/content/biorxiv/early/2026/10/28/2026.10.23.761317.full.pdf","source":{"id":"https://openalex.org/S4306402567","display_name":"bioRxiv (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"bioRxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.64898/2026.10.23.761317","doi":"https://doi.org/10.64898/2026.10.23.761317","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.10.23.761317","pdf_url":"https://www.biorxiv.org/content/biorxiv/early/2026/10/28/2026.10.23.761317.full.pdf","source":{"id":"https://openalex.org/S4306402567","display_name":"bioRxiv (Cold Spring Harbor Laboratory)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2750212522","host_organization_name":"Cold Spring Harbor Laboratory","host_organization_lineage":["https://openalex.org/I2750212522"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"bioRxiv","raw_type":"posted-content"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5683000087738037}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224221680.pdf","grobid_xml":"https://content.openalex.org/works/W7224221680.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2898463143","https://openalex.org/W2020625703","https://openalex.org/W2120834564","https://openalex.org/W2055877275","https://openalex.org/W2526194133","https://openalex.org/W2042697351","https://openalex.org/W4388451717","https://openalex.org/W2079255795","https://openalex.org/W2279098020","https://openalex.org/W4382777259"],"abstract_inverted_index":{"Abstract":[0],"Prioritizing":[1],"peptides":[2,199],"for":[3,32,64,178,184,213],"closely":[4],"related":[5],"G":[6],"protein-coupled":[7],"receptors":[8,34],"requires":[9],"comparing":[10],"target-directed":[11],"scores":[12,46,57,149,192,206],"with":[13,47,150],"evidence":[14],"from":[15,101],"other":[16],"structural":[17],"contexts.":[18],"We":[19],"applied":[20],"the":[21,59,74,80,97,110,132,210,233,245],"Neurokinin":[22],"Receptor-Conditioned":[23],"Peptide":[24],"Prioritization":[25],"workflow":[26],"(NK-RCPP)":[27],"to":[28,197],"96":[29],"generated":[30],"candidates":[31,118,133,228,254],"neurokinin":[33,202],"NK1R,":[35,66,215],"NK2R":[36,68,117,143,217,253],"and":[37,69,105,128,139,161,193,218,229,240],"NK3R.":[38],"The":[39,171],"retrospective":[40],"analysis":[41],"combined":[42],"receptor-matched":[43,191],"on-target":[44,56],"REF15":[45,205],"4,518":[48],"paired":[49,158,194],"structural-neighbour":[50,159,195],"comparisons":[51,196],"covering":[52],"82":[53],"candidates.":[54,72,221],"Lower":[55],"than":[58,209],"matched":[60,91,211,236],"controls":[61,212],"were":[62,207],"observed":[63],"14/32":[65,214],"23/32":[67,216],"6/32":[70,219],"NK3R":[71,220],"Adding":[73],"neighbour-score":[75],"criterion":[76],"retained":[77,224],"16":[78],"of":[79,96,114,232],"33":[81],"evaluable":[82,226],"on-target-favoured":[83,227],"candidates,":[84],"reducing":[85],"that":[86],"pool":[87],"by":[88],"51.5%.":[89],"At":[90],"receptor-specific":[92],"shortlist":[93,173,237],"sizes,":[94],"half":[95,231],"candidate":[98,165],"identities":[99],"differed":[100],"on-target-only":[102],"selection.":[103],"NK2R-04":[104,239],"NK2R-19":[106,241],"remained":[107,242],"selected":[108,243],"at":[109,235,244],"higher":[111,246],"neighbour-fraction":[112,247],"threshold":[113,162],"0.75.":[115],"Fourteen":[116],"lacked":[119],"neighbour":[120],"summaries,":[121],"leaving":[122],"their":[123],"joint-rule":[124],"status":[125],"unresolved.":[126],"Sequence-frequency":[127],"embedding":[129],"analyses":[130],"described":[131],"within":[134,167],"a":[135,168,175],"1,048-peptide":[136],"comparison":[137,144],"space,":[138],"an":[140],"exploratory":[141],"10-peptide":[142],"showed":[145],"differences":[146],"in":[147],"standardized":[148],"uncertain":[151],"score-potency":[152],"agreement.":[153],"These":[154],"findings":[155],"show":[156],"how":[157],"scoring":[160],"choice":[163],"shape":[164],"selection":[166],"receptor":[169],"family.":[170],"resulting":[172],"provides":[174],"defined":[176],"set":[177],"testing":[179],"whether":[180],"joint":[181],"prioritization":[182,223],"enriches":[183],"active,":[185],"receptor-preferred":[186],"peptides.":[187],"Highlights":[188],"NK-RCPP":[189],"combines":[190],"prioritize":[198],"across":[200],"three":[201],"receptors.":[203],"On-target":[204],"lower":[208],"Joint":[222],"16/33":[225],"changed":[230],"selections":[234],"sizes.":[238],"threshold;":[248],"missing":[249],"summaries":[250],"left":[251],"14":[252],"unclassified.":[255]},"counts_by_year":[],"updated_date":"2026-11-01T11:40:01.658920","created_date":"2026-10-30T00:00:00"}
