{"id":"https://openalex.org/W4417454965","doi":"https://doi.org/10.1186/s12859-025-06347-2","title":"A geometric graph-based deep learning model for drug-target affinity prediction","display_name":"A geometric graph-based deep learning model for drug-target affinity prediction","publication_year":2025,"publication_date":"2025-12-18","ids":{"openalex":"https://openalex.org/W4417454965","doi":"https://doi.org/10.1186/s12859-025-06347-2","pmid":"https://pubmed.ncbi.nlm.nih.gov/41413775"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-025-06347-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-025-06347-2","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s12859-025-06347-2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100417997","display_name":"Md Masud Rana","orcid":"https://orcid.org/0000-0001-8931-4329"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Md Masud Rana","raw_affiliation_strings":["Department of Mathematics, Kennesaw State University, Kennesaw, GA, 30144, USA. mrana10@kennesaw.edu","Department of Mathematics, Kennesaw State University, Kennesaw, GA, 30144, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Kennesaw State University, Kennesaw, GA, 30144, USA. mrana10@kennesaw.edu","institution_ids":["https://openalex.org/I172980758"]},{"raw_affiliation_string":"Department of Mathematics, Kennesaw State University, Kennesaw, GA, 30144, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099852998","display_name":"Farjana Tasnim Mukta","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farjana Tasnim Mukta","raw_affiliation_strings":["Department of Mathematics, Kennesaw State University, Kennesaw, GA, 30144, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Kennesaw State University, Kennesaw, GA, 30144, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041275321","display_name":"Duc Duy Nguyen","orcid":"https://orcid.org/0000-0003-2215-0328"},"institutions":[{"id":"https://openalex.org/I2802706902","display_name":"Knoxville College","ror":"https://ror.org/02bxrp522","country_code":"US","type":"education","lineage":["https://openalex.org/I2802706902"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Duc D. Nguyen","raw_affiliation_strings":["Department of Mathematics, University of Tennessee, Knoxville, TN, 37916, USA. ducnguyen@utk.edu","Department of Mathematics, University of Tennessee, Knoxville, TN, 37916, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Tennessee, Knoxville, TN, 37916, USA. ducnguyen@utk.edu","institution_ids":["https://openalex.org/I75027704","https://openalex.org/I2802706902"]},{"raw_affiliation_string":"Department of Mathematics, University of Tennessee, Knoxville, TN, 37916, USA","institution_ids":["https://openalex.org/I75027704"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041275321","https://openalex.org/A5100417997"],"corresponding_institution_ids":["https://openalex.org/I172980758","https://openalex.org/I2802706902","https://openalex.org/I75027704"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2072},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2072},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36203735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"1","first_page":"19","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.835099995136261,"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":0.835099995136261,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.07609999924898148,"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/T12576","display_name":"vaccines and immunoinformatics approaches","score":0.02500000037252903,"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/deep-learning","display_name":"Deep learning","score":0.7042999863624573},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6707000136375427},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5435000061988831},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5414999723434448},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5099999904632568},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4406999945640564},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.4255000054836273},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.39329999685287476},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3596000075340271}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7494999766349792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7152000069618225},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7042999863624573},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6707000136375427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5597000122070312},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5435000061988831},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5099999904632568},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.4255000054836273},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.39329999685287476},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C2989108626","wikidata":"https://www.wikidata.org/wiki/Q904407","display_name":"Drug target","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2888000011444092},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.2777000069618225},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2531000077724457}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000098422","descriptor_name":"Graph Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011485","descriptor_name":"Protein Binding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":true},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D015195","descriptor_name":"Drug Design","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12859-025-06347-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-025-06347-2","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:41413775","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41413775","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":"BMC bioinformatics","raw_type":null},{"id":"pmh:oai:doaj.org/article:48688d85bc1648abafcf876f513b2580","is_oa":true,"landing_page_url":"https://doaj.org/article/48688d85bc1648abafcf876f513b2580","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics, Vol 27, Iss 1, Pp 1-17 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12831358","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12831358/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-025-06347-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-025-06347-2","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","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":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1605578858","https://openalex.org/W1902237438","https://openalex.org/W2013085020","https://openalex.org/W2014704001","https://openalex.org/W2022998385","https://openalex.org/W2030286884","https://openalex.org/W2041541639","https://openalex.org/W2076779488","https://openalex.org/W2094162409","https://openalex.org/W2117620409","https://openalex.org/W2118587156","https://openalex.org/W2128332459","https://openalex.org/W2148512505","https://openalex.org/W2194775991","https://openalex.org/W2610142609","https://openalex.org/W2781821160","https://openalex.org/W2784213390","https://openalex.org/W2785947426","https://openalex.org/W2786477584","https://openalex.org/W2889677957","https://openalex.org/W2902812092","https://openalex.org/W2951676304","https://openalex.org/W2974531988","https://openalex.org/W3033534833","https://openalex.org/W3119774682","https://openalex.org/W3135935512","https://openalex.org/W3136947284","https://openalex.org/W3157078379","https://openalex.org/W3168436232","https://openalex.org/W3212042276","https://openalex.org/W4211219865","https://openalex.org/W4229082107","https://openalex.org/W4315434793","https://openalex.org/W4384564528","https://openalex.org/W4389167887","https://openalex.org/W4400519524","https://openalex.org/W4405877261","https://openalex.org/W4406698124","https://openalex.org/W4411086054"],"related_works":[],"abstract_inverted_index":{"In":[0,53],"structure-based":[1,155],"drug":[2,156],"design,":[3],"accurately":[4],"estimating":[5],"the":[6,44,127,130,134],"binding":[7,151],"affinity":[8,51,152],"between":[9],"a":[10,18,59,73],"candidate":[11],"ligand":[12],"and":[13,36,49,68,105,123,133,148],"its":[14,146],"protein":[15],"receptor":[16],"is":[17],"central":[19],"challenge.":[20],"Recent":[21],"advances":[22],"in":[23,91,154],"artificial":[24],"intelligence,":[25],"particularly":[26],"deep":[27,60],"learning,":[28],"have":[29],"demonstrated":[30],"superior":[31],"performance":[32,111],"over":[33],"traditional":[34],"empirical":[35],"physics-based":[37],"methods":[38],"for":[39,150],"this":[40,54],"task,":[41],"enabled":[42],"by":[43],"growing":[45],"availability":[46],"of":[47],"structural":[48],"experimental":[50],"data.":[52],"work,":[55],"we":[56,125],"introduce":[57],"DeepGGL,":[58],"convolutional":[61],"neural":[62],"network":[63],"that":[64],"integrates":[65],"residual":[66],"connections":[67],"an":[69],"attention":[70],"mechanism":[71],"within":[72],"geometric":[74],"graph":[75],"learning":[76],"framework.":[77],"By":[78],"leveraging":[79],"multiscale":[80],"weighted":[81],"colored":[82],"bipartite":[83],"subgraphs,":[84],"DeepGGL":[85,99,139],"effectively":[86],"captures":[87],"fine-grained":[88],"atom-level":[89],"interactions":[90],"protein-ligand":[92],"complexes":[93],"across":[94,115],"multiple":[95],"scales.":[96],"We":[97],"benchmarked":[98],"against":[100],"established":[101],"models":[102],"on":[103,129],"CASF-2013":[104],"CASF-2016,":[106],"where":[107],"it":[108],"achieved":[109],"state-of-the-art":[110],"with":[112],"significant":[113],"improvements":[114],"diverse":[116],"evaluation":[117],"metrics.":[118],"To":[119],"further":[120],"assess":[121],"robustness":[122],"generalization,":[124],"tested":[126],"model":[128],"CSAR-NRC-HiQ":[131],"dataset":[132],"PDBbind":[135],"v2019":[136],"holdout":[137],"set.":[138],"consistently":[140],"maintained":[141],"high":[142],"predictive":[143],"accuracy,":[144],"highlighting":[145],"adaptability":[147],"reliability":[149],"prediction":[153],"discovery.":[157]},"counts_by_year":[],"updated_date":"2026-06-17T06:14:20.161405","created_date":"2025-12-18T00:00:00"}
