{"id":"https://openalex.org/W3168385357","doi":"https://doi.org/10.1145/3447548.3467120","title":"Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization","display_name":"Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3168385357","doi":"https://doi.org/10.1145/3447548.3467120","mag":"3168385357"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467120","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467120","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","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/A5076405167","display_name":"Guy Barshatski","orcid":null},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Guy Barshatski","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029708595","display_name":"Kira Radinsky","orcid":"https://orcid.org/0009-0007-7918-2204"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Kira Radinsky","raw_affiliation_strings":["Technion, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Technion, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076405167"],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":1.4797,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.8451977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2554","last_page":"2564"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9994999766349792,"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":0.9994999766349792,"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/T11407","display_name":"Innovative Microfluidic and Catalytic Techniques Innovation","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9900000095367432,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6380881071090698},{"id":"https://openalex.org/keywords/chemical-space","display_name":"Chemical space","score":0.43581873178482056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42592257261276245},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.367139995098114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3572819232940674},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.3356776535511017},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.20836088061332703},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1876830756664276}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380881071090698},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.43581873178482056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42592257261276245},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.367139995098114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3572819232940674},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.3356776535511017},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.20836088061332703},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1876830756664276},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467120","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467120","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1556779599","https://openalex.org/W1975147762","https://openalex.org/W1988037271","https://openalex.org/W2016589492","https://openalex.org/W2023818227","https://openalex.org/W2107026277","https://openalex.org/W2151697120","https://openalex.org/W2157331557","https://openalex.org/W2331128040","https://openalex.org/W2529996553","https://openalex.org/W2747329762","https://openalex.org/W2795631711","https://openalex.org/W2913351693","https://openalex.org/W2913668833","https://openalex.org/W2920438880","https://openalex.org/W2970971581","https://openalex.org/W2972741532","https://openalex.org/W3098254076","https://openalex.org/W3098269892","https://openalex.org/W4295312788","https://openalex.org/W4300870773"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2973074952","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Molecular":[0],"lead":[1,113],"optimization":[2,129],"is":[3,196],"an":[4,38,66],"important":[5,160],"task":[6],"of":[7,32,34,46,54,58,79,159],"drug":[8,18,136],"discovery":[9],"focusing":[10],"on":[11,27,125],"generating":[12,115,211],"novel":[13,116],"molecules":[14,117],"similar":[15],"to":[16,82,104,109,153,171,188],"a":[17,35,71,76,80,83,92],"candidate":[19],"but":[20],"with":[21,70,91,118],"enhanced":[22,39,59,119],"properties.":[23,120],"Prior":[24],"works":[25],"focused":[26],"supervised":[28],"models":[29],"requiring":[30],"datasets":[31],"pairs":[33],"molecule":[36,81,97],"and":[37,48,99,135,139,157,183,207],"molecule.":[40],"These":[41],"approaches":[42],"require":[43],"large":[44],"amounts":[45],"data":[47],"are":[49,88,186],"limited":[50],"by":[51],"the":[52,55,110,155,203],"bias":[53],"specific":[56],"examples":[57],"molecules.":[60],"In":[61],"this":[62],"work,":[63],"we":[64,148,166],"present":[65],"unsupervised":[67],"generative":[68],"approach":[69],"molecule-embedding":[72],"component":[73],"that":[74],"maps":[75],"discrete":[77],"representation":[78],"continuous":[84],"space.":[85],"The":[86,194],"components":[87,161],"then":[89],"coupled":[90],"unique":[93],"training":[94],"architecture":[95],"leveraging":[96],"fingerprints":[98],"applying":[100],"double":[101],"cycle":[102],"constraints":[103],"enable":[105],"both":[106],"chemical":[107],"resemblance":[108],"original":[111],"molecular":[112,128],"while":[114],"We":[121],"evaluate":[122],"our":[123,141,163,168],"method":[124,142],"multiple":[126],"common":[127],"tasks,":[130],"including":[131],"dopamine":[132],"receptor":[133],"(DRD2)":[134],"likeness":[137],"(QED),":[138],"show":[140,154],"outperforms":[143],"previous":[144],"state-of-the-art":[145],"baselines.":[146],"Moreover,":[147],"conduct":[149],"thorough":[150],"ablation":[151],"experiments":[152],"effect":[156],"necessity":[158],"in":[162,202],"model.":[164],"Furthermore,":[165],"demonstrate":[167],"method's":[169],"ability":[170],"generate":[172],"FDA-approved":[173],"drugs":[174],"it":[175],"has":[176],"never":[177],"encountered":[178],"before,":[179],"such":[180],"as":[181],"Perazine":[182],"Clozapine,":[184],"which":[185],"used":[187],"treat":[189],"psychotic":[190],"disorders,":[191],"like":[192],"Schizophrenia.":[193],"system":[195],"currently":[197],"being":[198],"deployed":[199],"for":[200],"use":[201],"Targeted":[204],"Drug":[205],"Delivery":[206],"Personalized":[208],"Medicine":[209],"laboratories":[210],"treatments":[212],"using":[213],"nanoparticle-based":[214],"technology.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
