{"id":"https://openalex.org/W7117374379","doi":"https://doi.org/10.1016/j.compbiolchem.2025.108862","title":"Efficient drug\u2013target affinity prediction via interaction features and parallel CNN\u2013BiLSTM with attention","display_name":"Efficient drug\u2013target affinity prediction via interaction features and parallel CNN\u2013BiLSTM with attention","publication_year":2025,"publication_date":"2025-12-27","ids":{"openalex":"https://openalex.org/W7117374379","doi":"https://doi.org/10.1016/j.compbiolchem.2025.108862","pmid":"https://pubmed.ncbi.nlm.nih.gov/41478193"},"language":"en","primary_location":{"id":"doi:10.1016/j.compbiolchem.2025.108862","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiolchem.2025.108862","pdf_url":null,"source":{"id":"https://openalex.org/S104924063","display_name":"Computational Biology and Chemistry","issn_l":"1476-9271","issn":["1476-9271","1476-928X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Biology and Chemistry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.compbiolchem.2025.108862","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039545136","display_name":"Jiffriya Mohamed Abdul Cader","orcid":null},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Jiffriya Mohamed Abdul Cader","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Nathan, 4111, Queensland, Australia; Department of IT, Sri Lanka Institute of Advanced Technological Education, Colombo, 01000, Sri Lanka. Electronic address: jiffriya.cader@griffithuni.edu.au"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Nathan, 4111, Queensland, Australia; Department of IT, Sri Lanka Institute of Advanced Technological Education, Colombo, 01000, Sri Lanka. Electronic address: jiffriya.cader@griffithuni.edu.au","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086354302","display_name":"M. A. Hakim Newton","orcid":"https://orcid.org/0000-0001-5655-0683"},"institutions":[{"id":"https://openalex.org/I78757542","display_name":"University of Newcastle Australia","ror":"https://ror.org/00eae9z71","country_code":"AU","type":"education","lineage":["https://openalex.org/I78757542"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"M.A. Hakim Newton","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Nathan, 4111, Queensland, Australia; School of Information and Physical Sciences, The University of Newcastle, University Drive, Callaghan, 2308, New South Wales, Australia. Electronic address: mahakim.newton@newcastle.edu.au"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Nathan, 4111, Queensland, Australia; School of Information and Physical Sciences, The University of Newcastle, University Drive, Callaghan, 2308, New South Wales, Australia. Electronic address: mahakim.newton@newcastle.edu.au","institution_ids":["https://openalex.org/I78757542"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121373045","display_name":"Abdul Sattar","orcid":null},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Abdul Sattar","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Nathan, 4111, Queensland, Australia. Electronic address: a.sattar@griffith.edu.au"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Nathan, 4111, Queensland, Australia. Electronic address: a.sattar@griffith.edu.au","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039545136"],"corresponding_institution_ids":["https://openalex.org/I11701301"],"apc_list":{"value":2960,"currency":"USD","value_usd":2960},"apc_paid":{"value":2960,"currency":"USD","value_usd":2960},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64460376,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"121","issue":null,"first_page":"108862","last_page":"108862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9879000186920166,"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":0.9879000186920166,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.0015999999595806003,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7724000215530396},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6984999775886536},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.657800018787384},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.6093999743461609},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5313000082969666},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5180000066757202},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3955000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8101999759674072},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7724000215530396},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6984999775886536},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.657800018787384},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.6093999743461609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849999785423279},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5313000082969666},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43779999017715454},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C103697762","wikidata":"https://www.wikidata.org/wiki/Q4112105","display_name":"Virtual screening","level":3,"score":0.3912000060081482},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2782000005245209},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.25099998712539673}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1016/j.compbiolchem.2025.108862","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiolchem.2025.108862","pdf_url":null,"source":{"id":"https://openalex.org/S104924063","display_name":"Computational Biology and Chemistry","issn_l":"1476-9271","issn":["1476-9271","1476-928X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Biology and Chemistry","raw_type":"journal-article"},{"id":"pmid:41478193","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41478193","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational biology and chemistry","raw_type":null}],"best_oa_location":{"id":"doi:10.1016/j.compbiolchem.2025.108862","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiolchem.2025.108862","pdf_url":null,"source":{"id":"https://openalex.org/S104924063","display_name":"Computational Biology and Chemistry","issn_l":"1476-9271","issn":["1476-9271","1476-928X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Biology and Chemistry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320981","display_name":"Griffith University","ror":"https://ror.org/02sc3r913"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W2012642228","https://openalex.org/W2035585923","https://openalex.org/W2062941476","https://openalex.org/W2065540447","https://openalex.org/W2086286404","https://openalex.org/W2091223555","https://openalex.org/W2109991441","https://openalex.org/W2125781388","https://openalex.org/W2145962544","https://openalex.org/W2169585233","https://openalex.org/W2169678694","https://openalex.org/W2273267066","https://openalex.org/W2558698012","https://openalex.org/W2605952223","https://openalex.org/W2620998958","https://openalex.org/W2739999456","https://openalex.org/W2767284733","https://openalex.org/W2785947426","https://openalex.org/W2809216727","https://openalex.org/W2919115771","https://openalex.org/W2985881898","https://openalex.org/W3007743886","https://openalex.org/W3018980093","https://openalex.org/W3029836473","https://openalex.org/W3096561213","https://openalex.org/W3099836851","https://openalex.org/W3106449773","https://openalex.org/W3135575113","https://openalex.org/W3146944767","https://openalex.org/W3175786839","https://openalex.org/W3177828909","https://openalex.org/W3210942885","https://openalex.org/W4200547951","https://openalex.org/W4206078729","https://openalex.org/W4206419503","https://openalex.org/W4226098493","https://openalex.org/W4283259285","https://openalex.org/W4322745247","https://openalex.org/W4361985865","https://openalex.org/W4362459640","https://openalex.org/W4386532294","https://openalex.org/W4388006581","https://openalex.org/W4388595306","https://openalex.org/W4388714023","https://openalex.org/W4390460610","https://openalex.org/W4390883205","https://openalex.org/W4391798323","https://openalex.org/W4393255958","https://openalex.org/W4393376079","https://openalex.org/W4400142953","https://openalex.org/W4402697136","https://openalex.org/W4406892770","https://openalex.org/W4407852535","https://openalex.org/W4410897602"],"related_works":[],"abstract_inverted_index":{"Drug\u2013Target":[0,114],"Affinity":[1,115],"(DTA)":[2],"prediction":[3,225],"is":[4],"critical":[5],"for":[6,21,26,79,113,239],"reducing":[7],"failure":[8],"rates":[9],"in":[10,39,127,205],"drug":[11,241],"discovery,":[12],"but":[13,90],"existing":[14],"deep":[15],"learning":[16],"methods":[17,25,175],"often":[18],"trade":[19],"efficiency":[20,213],"accuracy.":[22],"Existing":[23,74],"CNN\u2013LSTM":[24,52],"DTA":[27,174,224],"have":[28],"convolutional":[29,60],"neural":[30,76],"networks":[31,77],"(CNNs)":[32],"and":[33,69,99,123,129,141,169,182,214],"long":[34,96],"short":[35],"term":[36],"memory":[37],"(LSTM)":[38],"series.":[40],"CNNs":[41,122],"capture":[42,85,136],"local":[43,138],"patterns,":[44],"while":[45,176],"LSTMs":[46],"model":[47],"long-range":[48,71],"dependencies.":[49,144],"In":[50],"series":[51],"architectures,":[53],"sequential":[54,143],"dependencies":[55],"are":[56,151],"only":[57],"modeled":[58],"after":[59],"compression,":[61],"leading":[62],"to":[63,134,184],"loss":[64],"of":[65,94,166,195],"raw":[66],"order":[67],"information":[68],"limiting":[70],"interaction":[72],"capture.":[73],"graph":[75],"(GNNs)":[78],"DTA,":[80],"on":[81,192],"the":[82,105,154,193],"other":[83],"hand,":[84],"structural":[86,139],"interactions":[87,150],"more":[88,236],"explicitly":[89],"require":[91],"large":[92],"numbers":[93],"parameters,":[95,179],"training":[97],"times,":[98],"high":[100],"computational":[101,155],"resources.":[102],"To":[103],"address":[104],"challenges,":[106],"we":[107],"propose":[108],"EDTA":[109,160,220],"(Efficient":[110],"Deep":[111],"Learning":[112],"prediction),":[116],"a":[117,235],"lighter":[118],"architecture":[119],"that":[120,148,222],"combines":[121],"bidirectional":[124],"LSTM":[125],"(BiLSTM)":[126],"parallel":[128],"also":[130],"uses":[131],"attention":[132],"mechanism":[133],"simultaneously":[135],"both":[137,212],"patterns":[140],"global":[142],"This":[145],"design":[146],"ensures":[147],"important":[149],"exploited":[152],"without":[153,229],"overhead.":[156],"On":[157],"benchmark":[158],"datasets,":[159],"achieves":[161],"r":[162,216],"m":[163,217],"2":[164,218],"values":[165],"0.783":[167],"(Davis)":[168],"0.787":[170],"(KIBA),":[171],"outperforming":[172],"state-of-the-art":[173],"using":[177],"fewer":[178],"less":[180],"memory,":[181],"up":[183],"five-fold":[185],"faster":[186],"inference.":[187],"A":[188],"virtual":[189],"screening":[190],"experiment":[191],"Database":[194],"Useful":[196],"Decoys:":[197],"Enhanced":[198],"(DUD-E)":[199],"dataset":[200],"further":[201],"confirms":[202],"its":[203],"effectiveness":[204],"distinguishing":[206],"binders":[207],"from":[208],"decoys.":[209],"By":[210],"emphasizing":[211],"strong":[215],"performance,":[219],"demonstrates":[221],"accurate":[223],"can":[226],"be":[227],"achieved":[228],"sacrificing":[230],"scalability":[231],"or":[232],"sustainability,":[233],"offering":[234],"practical":[237],"solution":[238],"modern":[240],"discovery.":[242]},"counts_by_year":[],"updated_date":"2026-01-19T04:01:09.351973","created_date":"2025-12-27T00:00:00"}