{"id":"https://openalex.org/W7126067282","doi":"https://doi.org/10.1109/bibm66473.2025.11356284","title":"CoLA-DTA: Cross-Modal Latent Alignment for Generalization-Enhanced Drug-Target Affinity Prediction","display_name":"CoLA-DTA: Cross-Modal Latent Alignment for Generalization-Enhanced Drug-Target Affinity Prediction","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126067282","doi":"https://doi.org/10.1109/bibm66473.2025.11356284"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124256378","display_name":"Li Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":null,"type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Zhang","raw_affiliation_strings":["College of Computer Science and Engineering, Changchun University of Technology,Changchun,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Changchun University of Technology,Changchun,China","institution_ids":["https://openalex.org/I4385474403"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124176407","display_name":"Chen Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":null,"type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Cui","raw_affiliation_strings":["College of Computer Science and Engineering, Changchun University of Technology,Changchun,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Changchun University of Technology,Changchun,China","institution_ids":["https://openalex.org/I4385474403"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104230589","display_name":"Xike Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xike Ouyang","raw_affiliation_strings":["Central South University,Department of Pharmacy and Center of Clinical Pharmacology,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Central South University,Department of Pharmacy and Center of Clinical Pharmacology,Changsha,China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118983678","display_name":"Xinying Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4385474403","display_name":"Changchun University of Technology","ror":"https://ror.org/052pakb34","country_code":null,"type":"education","lineage":["https://openalex.org/I4385474403"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinying Wang","raw_affiliation_strings":["College of Computer Science and Engineering, Changchun University of Technology,Changchun,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Changchun University of Technology,Changchun,China","institution_ids":["https://openalex.org/I4385474403"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100446035","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0001-6881-9977"},"institutions":[{"id":"https://openalex.org/I161716053","display_name":"China Pharmaceutical University","ror":"https://ror.org/01sfm2718","country_code":"CN","type":"education","lineage":["https://openalex.org/I161716053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Wang","raw_affiliation_strings":["School of Information Science and Technology, China Pharmaceutical University,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, China Pharmaceutical University,Nanjing,China","institution_ids":["https://openalex.org/I161716053"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5124256378"],"corresponding_institution_ids":["https://openalex.org/I4385474403"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75565657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6660","last_page":"6667"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.840399980545044,"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":0.840399980545044,"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/T12576","display_name":"vaccines and immunoinformatics approaches","score":0.024299999698996544,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.02370000071823597,"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/preprocessor","display_name":"Preprocessor","score":0.6485999822616577},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49140000343322754},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4724999964237213},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4456000030040741},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.4431999921798706},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4090000092983246},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.38269999623298645},{"id":"https://openalex.org/keywords/drug-target","display_name":"Drug target","score":0.3743000030517578},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.3652999997138977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3522999882698059}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7092999815940857},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6485999822616577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5257999897003174},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4456000030040741},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42730000615119934},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4090000092983246},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.38269999623298645},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.3626999855041504},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3522999882698059},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3456999957561493},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.34310001134872437},{"id":"https://openalex.org/C88031987","wikidata":"https://www.wikidata.org/wiki/Q1377767","display_name":"Multiple sequence alignment","level":5,"score":0.3296999931335449},{"id":"https://openalex.org/C45484198","wikidata":"https://www.wikidata.org/wiki/Q827246","display_name":"Sequence alignment","level":4,"score":0.3276999890804291},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C64903051","wikidata":"https://www.wikidata.org/wiki/Q2198549","display_name":"Drug development","level":3,"score":0.30329999327659607},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3021000027656555},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C55105296","wikidata":"https://www.wikidata.org/wiki/Q841382","display_name":"Interaction network","level":3,"score":0.27399998903274536},{"id":"https://openalex.org/C4668613","wikidata":"https://www.wikidata.org/wiki/Q4116110","display_name":"Structural alignment","level":5,"score":0.27250000834465027},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C152662350","wikidata":"https://www.wikidata.org/wiki/Q815297","display_name":"Systems biology","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356284","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.6570820808410645}],"awards":[{"id":"https://openalex.org/G8354632314","display_name":null,"funder_award_id":"62372099","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8416868986","display_name":null,"funder_award_id":"20230201090GX","funder_id":"https://openalex.org/F4320335953","funder_display_name":"Jilin Scientific and Technological Development Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335953","display_name":"Jilin Scientific and Technological Development Program","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W2035585923","https://openalex.org/W2086286404","https://openalex.org/W2096864392","https://openalex.org/W2114162221","https://openalex.org/W2336040088","https://openalex.org/W2615136515","https://openalex.org/W2785947426","https://openalex.org/W2796218413","https://openalex.org/W3096561213","https://openalex.org/W3158002239","https://openalex.org/W3177500196","https://openalex.org/W4200547951","https://openalex.org/W4205167309","https://openalex.org/W4214873089","https://openalex.org/W4225435640","https://openalex.org/W4285791429","https://openalex.org/W4300717171","https://openalex.org/W4309452766","https://openalex.org/W4313256479","https://openalex.org/W4366991255","https://openalex.org/W4379619072","https://openalex.org/W4385330534","https://openalex.org/W4386898749","https://openalex.org/W4387219655","https://openalex.org/W4388615774","https://openalex.org/W4389131280","https://openalex.org/W4393479383","https://openalex.org/W4406139397","https://openalex.org/W4407117450","https://openalex.org/W4407212030"],"related_works":[],"abstract_inverted_index":{"Drug":[0],"discovery,":[1],"a":[2,45,107],"cornerstone":[3],"of":[4,59],"modern":[5],"biomedical":[6],"research,":[7],"is":[8],"critical":[9],"for":[10,22,50,148],"developing":[11],"targeted":[12],"therapies":[13],"against":[14],"complex":[15],"diseases.":[16],"However,":[17],"many":[18],"existing":[19],"computational":[20],"approaches":[21],"DTA":[23],"prediction":[24],"suffer":[25],"from":[26,87],"limited":[27],"accuracy":[28,129],"and":[29,36,61,70,77,84,92,130,156],"poor":[30],"generalization":[31],"across":[32],"diverse":[33],"target":[34],"families":[35],"chemical":[37],"spaces.":[38],"To":[39],"address":[40],"this,":[41],"we":[42],"propose":[43],"CoLA-DTA,":[44],"cross-modal":[46],"alignment":[47],"framework":[48],"designed":[49],"generalizationenhanced":[51],"drug-target":[52],"affinity":[53],"prediction.":[54],"CoLA-DTA":[55,123],"integrates":[56],"multiple":[57],"modalities":[58],"protein":[60,88],"drug":[62,90,149],"representations,":[63],"including":[64],"sequence":[65],"embeddings,":[66],"3D":[67],"structural":[68],"graphs,":[69],"molecular":[71],"graphs.":[72],"Specifically,":[73],"pretrained":[74],"language":[75],"models":[76,126],"graph":[78,95],"neural":[79],"networks":[80],"extract":[81],"semantic,":[82],"spatial,":[83],"topological":[85],"features":[86],"sequences,":[89],"SMILES,":[91],"their":[93],"respective":[94],"representations.":[96],"A":[97,136],"Gated":[98],"Fusion":[99],"module":[100],"effectively":[101],"combines":[102],"multi-source":[103],"features,":[104],"followed":[105],"by":[106],"bidirectional":[108],"cross-attention":[109],"mechanism":[110],"that":[111,122],"captures":[112],"finegrained":[113],"intermolecular":[114],"interactions.":[115],"Experimental":[116],"results":[117],"on":[118,139],"benchmark":[119],"datasets":[120],"demonstrate":[121],"outperforms":[124],"state-of-the-art":[125],"in":[127],"both":[128],"generalization,":[131],"particularly":[132],"under":[133],"cold-start":[134],"settings.":[135],"case":[137],"study":[138],"protooncogene":[140],"tyrosine-protein":[141],"kinase":[142],"ROS(PTKR)":[143],"further":[144],"demonstrated":[145],"CoLA-DTA's":[146],"potential":[147],"discovery.":[150],"CoLADTA's":[151],"source":[152],"code,":[153],"pre-trained":[154],"models,":[155],"data":[157],"preprocessing":[158],"code":[159],"are":[160],"available":[161],"at":[162],"https://github.com/NENUBioCompute/CoLA-DTA.git.":[163]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}