{"id":"https://openalex.org/W4392644037","doi":"https://doi.org/10.3390/make6010030","title":"Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures","display_name":"Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures","publication_year":2024,"publication_date":"2024-03-11","ids":{"openalex":"https://openalex.org/W4392644037","doi":"https://doi.org/10.3390/make6010030"},"language":"en","primary_location":{"id":"doi:10.3390/make6010030","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6010030","pdf_url":"https://www.mdpi.com/2504-4990/6/1/30/pdf?version=1710157726","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/6/1/30/pdf?version=1710157726","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074671586","display_name":"Heesung Shim","orcid":"https://orcid.org/0000-0002-1468-8120"},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Heesung Shim","raw_affiliation_strings":["Physical and Life Sciences, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical and Life Sciences, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA","institution_ids":["https://openalex.org/I1282311441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035849909","display_name":"Jonathan Allen","orcid":"https://orcid.org/0000-0002-4359-8263"},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]},{"id":"https://openalex.org/I4210138311","display_name":"Lawrence Livermore National Security","ror":"https://ror.org/03z21mf61","country_code":"US","type":"government","lineage":["https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan E. Allen","raw_affiliation_strings":["Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA"],"raw_orcid":"https://orcid.org/0000-0002-4359-8263","affiliations":[{"raw_affiliation_string":"Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA","institution_ids":["https://openalex.org/I4210138311","https://openalex.org/I1282311441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077574182","display_name":"William F. Bennett","orcid":"https://orcid.org/0000-0003-3993-9077"},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"W. F. Drew Bennett","raw_affiliation_strings":["Physical and Life Sciences, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA"],"raw_orcid":"https://orcid.org/0000-0003-3993-9077","affiliations":[{"raw_affiliation_string":"Physical and Life Sciences, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA","institution_ids":["https://openalex.org/I1282311441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074671586","https://openalex.org/A5077574182"],"corresponding_institution_ids":["https://openalex.org/I1282311441"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.6713,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6924425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"6","issue":"1","first_page":"642","last_page":"657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9998000264167786,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.9634000062942505,"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/docking","display_name":"Docking (animal)","score":0.7972314357757568},{"id":"https://openalex.org/keywords/virtual-screening","display_name":"Virtual screening","score":0.6907666921615601},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6463457345962524},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5557434558868408},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5326758623123169},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5062276721000671},{"id":"https://openalex.org/keywords/chemical-space","display_name":"Chemical space","score":0.4795539081096649},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4475117027759552},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.42823341488838196},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4119541049003601},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.3931044638156891},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.14436107873916626},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08388537168502808}],"concepts":[{"id":"https://openalex.org/C41685203","wikidata":"https://www.wikidata.org/wiki/Q1974042","display_name":"Docking (animal)","level":2,"score":0.7972314357757568},{"id":"https://openalex.org/C103697762","wikidata":"https://www.wikidata.org/wiki/Q4112105","display_name":"Virtual screening","level":3,"score":0.6907666921615601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6463457345962524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5557434558868408},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5326758623123169},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5062276721000671},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.4795539081096649},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4475117027759552},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.42823341488838196},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4119541049003601},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.3931044638156891},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.14436107873916626},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08388537168502808},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/make6010030","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6010030","pdf_url":"https://www.mdpi.com/2504-4990/6/1/30/pdf?version=1710157726","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:osti.gov:2473628","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/2473628","pdf_url":"https://www.osti.gov/servlets/purl/2473628","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"pmh:oai:doaj.org/article:7c9e6d013e0c4eb6b3837958e0a4348d","is_oa":true,"landing_page_url":"https://doaj.org/article/7c9e6d013e0c4eb6b3837958e0a4348d","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":"Machine Learning and Knowledge Extraction, Vol 6, Iss 1, Pp 642-657 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make6010030","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make6010030","pdf_url":"https://www.mdpi.com/2504-4990/6/1/30/pdf?version=1710157726","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G2415395197","display_name":null,"funder_award_id":"HDTRA1036045","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G246272211","display_name":null,"funder_award_id":"CB100035","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G2700676748","display_name":null,"funder_award_id":"LLNL-JRNL-858354","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G5522089832","display_name":null,"funder_award_id":"DE-AC52-07NA27344","funder_id":"https://openalex.org/F4320338286","funder_display_name":"Lawrence Livermore National Laboratory"},{"id":"https://openalex.org/G6903820856","display_name":null,"funder_award_id":"DE-AC52-07NA27344","funder_id":"https://openalex.org/F4320332186","funder_display_name":"Defense Threat Reduction Agency"},{"id":"https://openalex.org/G8374966015","display_name":null,"funder_award_id":"AC52-07NA27344","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8769882630","display_name":null,"funder_award_id":"LLNL-JRNL-858354","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G991281326","display_name":null,"funder_award_id":"AC52-07NA27344","funder_id":"https://openalex.org/F4320338286","funder_display_name":"Lawrence Livermore National Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320332186","display_name":"Defense Threat Reduction Agency","ror":"https://ror.org/04tz64554"},{"id":"https://openalex.org/F4320338286","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392644037.pdf"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1592950931","https://openalex.org/W1605578858","https://openalex.org/W1984476711","https://openalex.org/W2014055152","https://openalex.org/W2043429268","https://openalex.org/W2050456292","https://openalex.org/W2060531713","https://openalex.org/W2061079400","https://openalex.org/W2070493638","https://openalex.org/W2079384285","https://openalex.org/W2083725367","https://openalex.org/W2092285329","https://openalex.org/W2096864392","https://openalex.org/W2102697248","https://openalex.org/W2105527266","https://openalex.org/W2118587156","https://openalex.org/W2126996939","https://openalex.org/W2128332459","https://openalex.org/W2128983966","https://openalex.org/W2618530766","https://openalex.org/W2781821160","https://openalex.org/W2789514702","https://openalex.org/W2911964244","https://openalex.org/W2974531988","https://openalex.org/W3001433048","https://openalex.org/W3005043246","https://openalex.org/W3014476516","https://openalex.org/W3015608194","https://openalex.org/W3021453944","https://openalex.org/W3094762523","https://openalex.org/W3098189759","https://openalex.org/W3135935512","https://openalex.org/W3159141234","https://openalex.org/W3168436232","https://openalex.org/W3206116522","https://openalex.org/W3209909976","https://openalex.org/W4206367183","https://openalex.org/W4224291667","https://openalex.org/W4239510810","https://openalex.org/W4281875807","https://openalex.org/W4316507591","https://openalex.org/W4317776906","https://openalex.org/W4380786758","https://openalex.org/W4389696354"],"related_works":["https://openalex.org/W2059230675","https://openalex.org/W2326230513","https://openalex.org/W3185720802","https://openalex.org/W2376003823","https://openalex.org/W2773493604","https://openalex.org/W4232045916","https://openalex.org/W2269591907","https://openalex.org/W2069870126","https://openalex.org/W2027065525","https://openalex.org/W2057846043"],"abstract_inverted_index":{"Decades":[0],"of":[1,18,26,88,96,149],"drug":[2],"development":[3],"research":[4],"have":[5,74],"explored":[6],"a":[7,102,123],"vast":[8],"chemical":[9],"space":[10],"for":[11,40,118],"highly":[12],"active":[13],"compounds.":[14],"The":[15,133],"exponential":[16],"growth":[17],"virtual":[19],"libraries":[20],"enables":[21],"easy":[22],"access":[23],"to":[24,37,58,77,145],"billions":[25],"synthesizable":[27],"molecules.":[28],"Computational":[29],"modeling,":[30],"particularly":[31],"molecular":[32,46,189],"docking,":[33],"utilizes":[34],"physics-based":[35],"calculations":[36],"prioritize":[38],"molecules":[39],"synthesis":[41],"and":[42,142,167,171,184,197],"testing.":[43,63],"Nevertheless,":[44],"the":[45,83,89,94,116,137,152,157,179],"docking":[47,51,140,182,190],"process":[48],"often":[49],"yields":[50],"poses":[52,80],"with":[53,61,110,128],"favorable":[54],"scores":[55,141,183],"that":[56,177],"prove":[57],"be":[59],"inaccurate":[60],"experimental":[62,143,185],"To":[64],"address":[65],"these":[66],"issues,":[67],"several":[68],"approaches":[69],"using":[70],"machine":[71],"learning":[72],"(ML)":[73],"been":[75],"proposed":[76,158],"filter":[78],"incorrect":[79],"based":[81,121],"on":[82,122,151,160],"crystal":[84,119,153],"structures.":[85,154],"However,":[86],"most":[87],"methods":[90],"are":[91],"limited":[92],"by":[93,192],"availability":[95],"structure":[97],"data.":[98],"Here,":[99],"we":[100],"propose":[101],"new":[103,134],"pose":[104],"classification":[105],"approach,":[106],"PECAN2":[107],"(Pose":[108],"Classification":[109],"3D":[111,124],"Atomic":[112],"Network":[113,131],"2),":[114],"without":[115],"need":[117],"structures,":[120],"atomic":[125],"neural":[126],"network":[127],"Point":[129],"Cloud":[130],"(PCN).":[132],"approach":[135],"uses":[136],"correlation":[138,180],"between":[139,181],"data":[144,186],"assign":[146],"labels,":[147],"instead":[148],"relying":[150],"We":[155],"validate":[156],"classifier":[159],"multiple":[161],"datasets":[162],"including":[163],"human":[164],"mu,":[165],"delta,":[166],"kappa":[168],"opioid":[169],"receptors":[170],"SARS-CoV-2":[172],"Mpro.":[173],"Our":[174],"results":[175],"demonstrate":[176],"leveraging":[178],"alone":[187],"enhances":[188],"performance":[191],"filtering":[193],"out":[194],"false":[195,198],"positives":[196],"negatives.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-17T08:19:37.847499","created_date":"2025-10-10T00:00:00"}