{"id":"https://openalex.org/W4411464989","doi":"https://doi.org/10.1145/3703412.3703426","title":"KG-DTA: A knowledge graph-based meta-path learning framework to predict drug-target binding affinity","display_name":"KG-DTA: A knowledge graph-based meta-path learning framework to predict drug-target binding affinity","publication_year":2024,"publication_date":"2024-10-08","ids":{"openalex":"https://openalex.org/W4411464989","doi":"https://doi.org/10.1145/3703412.3703426"},"language":"en","primary_location":{"id":"doi:10.1145/3703412.3703426","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703412.3703426","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on AI-ML Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3703412.3703426","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075138847","display_name":"Amit Ranjan","orcid":"https://orcid.org/0000-0002-7940-5865"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amit Ranjan","raw_affiliation_strings":["Louisiana State University, Baton Rouge, United States of America"],"affiliations":[{"raw_affiliation_string":"Louisiana State University, Baton Rouge, United States of America","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031411717","display_name":"Adam Bess","orcid":"https://orcid.org/0000-0003-1156-076X"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Bess","raw_affiliation_strings":["Louisiana State University, Baton Rouge, United States of America"],"affiliations":[{"raw_affiliation_string":"Louisiana State University, Baton Rouge, United States of America","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036882311","display_name":"Md Saiful Islam Sajol","orcid":null},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Md Saiful Islam Sajol","raw_affiliation_strings":["Louisiana State University, Baton Rouge, United States of America"],"affiliations":[{"raw_affiliation_string":"Louisiana State University, Baton Rouge, United States of America","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101334955","display_name":"Magesh Rajasekaran","orcid":"https://orcid.org/0000-0001-9022-2157"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Magesh Rajasekaran","raw_affiliation_strings":["Louisiana State University, Baton Rouge, United States of America"],"affiliations":[{"raw_affiliation_string":"Louisiana State University, Baton Rouge, United States of America","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032800073","display_name":"Chris Alvin","orcid":"https://orcid.org/0000-0001-6044-2159"},"institutions":[{"id":"https://openalex.org/I86115722","display_name":"Furman University","ror":"https://ror.org/04ytb9n23","country_code":"US","type":"education","lineage":["https://openalex.org/I86115722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris Alvin","raw_affiliation_strings":["Furman University, Greenville, United States of America"],"affiliations":[{"raw_affiliation_string":"Furman University, Greenville, United States of America","institution_ids":["https://openalex.org/I86115722"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101963514","display_name":"Supratik Mukhopadhyay","orcid":"https://orcid.org/0000-0003-0839-1133"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Supratik Mukhopadhyay","raw_affiliation_strings":["Louisiana State University, Baton Rouge, United States of America"],"affiliations":[{"raw_affiliation_string":"Louisiana State University, Baton Rouge, United States of America","institution_ids":["https://openalex.org/I121820613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5075138847"],"corresponding_institution_ids":["https://openalex.org/I121820613"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32680309,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9825999736785889,"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/T11440","display_name":"Click Chemistry and Applications","score":0.9818000197410583,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6868205070495605},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5475786328315735},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5293688774108887},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4818221628665924},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.4636927843093872},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4410005211830139},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.417780339717865},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3678531050682068},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2816125750541687},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.1773783564567566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17711219191551208},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13381770253181458},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1027170717716217},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1017446219921112}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6868205070495605},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5475786328315735},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5293688774108887},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4818221628665924},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.4636927843093872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4410005211830139},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.417780339717865},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3678531050682068},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2816125750541687},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.1773783564567566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17711219191551208},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13381770253181458},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1027170717716217},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1017446219921112}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3703412.3703426","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703412.3703426","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on AI-ML Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.lsu.edu:enviro_sciences_pubs-1371","is_oa":true,"landing_page_url":"https://repository.lsu.edu/enviro_sciences_pubs/372","pdf_url":null,"source":{"id":"https://openalex.org/S4210169993","display_name":"Civil War Book Review","issn_l":"1528-6592","issn":["1528-6592"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310315936","host_organization_name":"Louisiana State University","host_organization_lineage":["https://openalex.org/P4310315936"],"host_organization_lineage_names":["Louisiana State University"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Publications","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3703412.3703426","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3703412.3703426","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Conference on AI-ML Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1979537657","https://openalex.org/W2015604457","https://openalex.org/W2035585923","https://openalex.org/W2038702914","https://openalex.org/W2086286404","https://openalex.org/W2094722405","https://openalex.org/W2109991441","https://openalex.org/W2110118677","https://openalex.org/W2139736926","https://openalex.org/W2151697120","https://openalex.org/W2153838454","https://openalex.org/W2172154910","https://openalex.org/W2177411254","https://openalex.org/W2213443318","https://openalex.org/W2256553158","https://openalex.org/W2295598076","https://openalex.org/W2297106365","https://openalex.org/W2318276819","https://openalex.org/W2336207313","https://openalex.org/W2602318385","https://openalex.org/W2605952223","https://openalex.org/W2785947426","https://openalex.org/W2918544128","https://openalex.org/W2920069053","https://openalex.org/W2947497907","https://openalex.org/W2997680655","https://openalex.org/W3000043291","https://openalex.org/W3014881833","https://openalex.org/W3039465695","https://openalex.org/W3092712933","https://openalex.org/W3096561213","https://openalex.org/W3100541926","https://openalex.org/W3133246485","https://openalex.org/W3184618566","https://openalex.org/W3198168376","https://openalex.org/W3201055938","https://openalex.org/W3207365242","https://openalex.org/W3213361969","https://openalex.org/W3213542976","https://openalex.org/W4200534198","https://openalex.org/W4200547951","https://openalex.org/W4220872781","https://openalex.org/W4224981527","https://openalex.org/W4313595375","https://openalex.org/W4327550249","https://openalex.org/W4390111372","https://openalex.org/W4390460610","https://openalex.org/W4399780209"],"related_works":["https://openalex.org/W4206379684","https://openalex.org/W2366105490","https://openalex.org/W2580680567","https://openalex.org/W2606076248","https://openalex.org/W4285170202","https://openalex.org/W114270996","https://openalex.org/W4249200654","https://openalex.org/W2396656278","https://openalex.org/W3011011760","https://openalex.org/W2407625558"],"abstract_inverted_index":{"Drug":[0],"target":[1],"affinity":[2,111,185],"(DTA)":[3],"prediction":[4],"is":[5,179,251],"essential":[6],"at":[7],"different":[8],"phases":[9],"of":[10,53,95,103,115,209,216],"drug":[11,15,145,258,262],"discovery":[12],"and":[13,24,35,55,68,97,109,118,150,171,195,218,223,241],"virtual":[14],"screening.":[16],"However,":[17],"traditional":[18],"wet":[19],"lab":[20],"experiments":[21],"are":[22,123],"time":[23],"resource-intensive":[25],"owing":[26],"to":[27,44,57,84,147,155,181,197,255],"the":[28,32,51,59,63,138,174,183,207,221],"complex":[29,60],"interactions":[30,61],"within":[31,137],"vast":[33],"biological":[34,64],"chemical":[36],"spaces.":[37],"Computational":[38],"methods":[39],"have":[40,49],"proven":[41],"their":[42],"potential":[43],"predict":[45,182],"DTA,":[46],"but":[47],"none":[48],"considered":[50],"association":[52],"drugs":[54,67,96,117,170],"proteins":[56,98,119],"capture":[58,166],"in":[62,120],"network":[65,94,122,139],"between":[66,169],"proteins.":[69,172],"To":[70],"address":[71],"this,":[72],"we":[73,89,188],"propose":[74],"a":[75,91,151,252],"novel":[76],"framework":[77,229],"leveraging":[78],"knowledge":[79,247],"graph-based":[80,248],"meta-path":[81,131,249],"learning":[82,132,177,250],"(KG-DTA)":[83],"enhance":[85],"DTA":[86],"prediction.":[87],"First,":[88],"construct":[90],"weighted":[92],"heterogeneous":[93],"that":[99,165,202,246],"incorporates":[100],"three":[101],"types":[102],"entities:":[104],"drug-drug":[105],"similarity,":[106,108],"protein-protein":[107],"drug-protein":[110],"scores.":[112],"Node":[113],"features":[114],"both":[116],"this":[121],"enriched":[124],"using":[125],"embeddings":[126],"from":[127,144],"pretrained":[128],"models.":[129],"The":[130],"technique":[133],"extracts":[134],"meaningful":[135],"pathways":[136,164],"by":[140],"focusing":[141],"on":[142,220],"paths":[143],"nodes":[146],"protein":[148],"nodes,":[149],"path":[152],"length":[153],"restricted":[154],"2":[156],"or":[157],"3.":[158],"This":[159],"strategy":[160],"yields":[161],"6":[162],"distinct":[163],"intricate":[167],"relationships":[168],"Finally,":[173],"XGBoost-based":[175],"machine":[176],"algorithm":[178],"used":[180,189],"binding":[184],"score.":[186],"Experimentally,":[187],"two":[190],"standard":[191,235],"benchmark":[192],"datasets:":[193],"Davis":[194,222],"Kiba":[196,224],"evaluate":[198],"KG-DTA.":[199],"Experiments":[200],"show":[201],"our":[203,228],"method":[204],"significantly":[205],"surpasses":[206],"performance":[208,232],"state-of-the-art":[210],"techniques,":[211],"achieving":[212],"mean":[213],"square":[214],"errors":[215],"0.23":[217],"0.11":[219],"datasets,":[225],"respectively.":[226],"Additionally,":[227],"shows":[230],"superior":[231],"across":[233],"four":[234],"evaluation":[236],"metrics,":[237],"underscoring":[238],"its":[239],"effectiveness":[240],"reliability.":[242],"These":[243],"results":[244],"suggest":[245],"promising":[253],"approach":[254],"advance":[256],"computational":[257],"discovery,":[259],"potentially":[260],"accelerating":[261],"development":[263],"timelines.":[264]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
