{"id":"https://openalex.org/W2768118983","doi":"https://doi.org/10.1021/acs.jcim.7b00298","title":"Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization","display_name":"Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization","publication_year":2017,"publication_date":"2017-11-13","ids":{"openalex":"https://openalex.org/W2768118983","doi":"https://doi.org/10.1021/acs.jcim.7b00298","mag":"2768118983","pmid":"https://pubmed.ncbi.nlm.nih.gov/29131617"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.7b00298","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.7b00298","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5067176307","display_name":"Samo Turk","orcid":"https://orcid.org/0000-0003-2044-7670"},"institutions":[{"id":"https://openalex.org/I4210157022","display_name":"BioMed X Institute","ror":"https://ror.org/05drfac92","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210157022"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Samo Turk","raw_affiliation_strings":["BioMed X Innovation Center, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany"],"raw_orcid":"https://orcid.org/0000-0003-2044-7670","affiliations":[{"raw_affiliation_string":"BioMed X Innovation Center, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany","institution_ids":["https://openalex.org/I4210157022"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026450463","display_name":"Benjamin Merget","orcid":"https://orcid.org/0000-0002-3882-596X"},"institutions":[{"id":"https://openalex.org/I4210157022","display_name":"BioMed X Institute","ror":"https://ror.org/05drfac92","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210157022"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benjamin Merget","raw_affiliation_strings":["BioMed X Innovation Center, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-3882-596X","affiliations":[{"raw_affiliation_string":"BioMed X Innovation Center, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany","institution_ids":["https://openalex.org/I4210157022"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013173045","display_name":"Friedrich Rippmann","orcid":"https://orcid.org/0000-0002-4604-9251"},"institutions":[{"id":"https://openalex.org/I164928964","display_name":"Merck KGaA, Darmstadt (Germany)","ror":"https://ror.org/04b2dty93","country_code":"DE","type":"company","lineage":["https://openalex.org/I164928964"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friedrich Rippmann","raw_affiliation_strings":["Global\rComputational Chemistry, Merck KGaA, Frankfurter Strasse 250, 64293 Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Global\rComputational Chemistry, Merck KGaA, Frankfurter Strasse 250, 64293 Darmstadt, Germany","institution_ids":["https://openalex.org/I164928964"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051191427","display_name":"Simone Fulle","orcid":"https://orcid.org/0000-0002-7646-5889"},"institutions":[{"id":"https://openalex.org/I4210157022","display_name":"BioMed X Institute","ror":"https://ror.org/05drfac92","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210157022"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Simone Fulle","raw_affiliation_strings":["BioMed X Innovation Center, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-7646-5889","affiliations":[{"raw_affiliation_string":"BioMed X Innovation Center, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany","institution_ids":["https://openalex.org/I4210157022"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5051191427"],"corresponding_institution_ids":["https://openalex.org/I4210157022"],"apc_list":null,"apc_paid":null,"fwci":1.9141,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.87819937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"57","issue":"12","first_page":"3079","last_page":"3085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9932000041007996,"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/T13180","display_name":"Chemistry and Chemical Engineering","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/2304","display_name":"Environmental Chemistry"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coupling","display_name":"Coupling (piping)","score":0.6930580139160156},{"id":"https://openalex.org/keywords/virtual-screening","display_name":"Virtual screening","score":0.5927633047103882},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5196055769920349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4622255563735962},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.33891764283180237},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.32992827892303467},{"id":"https://openalex.org/keywords/computational-chemistry","display_name":"Computational chemistry","score":0.201825350522995},{"id":"https://openalex.org/keywords/molecular-dynamics","display_name":"Molecular dynamics","score":0.15896248817443848},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.10982537269592285}],"concepts":[{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.6930580139160156},{"id":"https://openalex.org/C103697762","wikidata":"https://www.wikidata.org/wiki/Q4112105","display_name":"Virtual screening","level":3,"score":0.5927633047103882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5196055769920349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4622255563735962},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.33891764283180237},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.32992827892303467},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.201825350522995},{"id":"https://openalex.org/C59593255","wikidata":"https://www.wikidata.org/wiki/Q901663","display_name":"Molecular dynamics","level":2,"score":0.15896248817443848},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.10982537269592285}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","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":"D006801","descriptor_name":"Humans","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":"D008024","descriptor_name":"Ligands","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":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013329","descriptor_name":"Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013329","descriptor_name":"Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013329","descriptor_name":"Structure-Activity Relationship","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":false},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.7b00298","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.7b00298","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:29131617","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29131617","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":"Journal of chemical information and modeling","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4399999976158142,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1604884792","https://openalex.org/W1678356000","https://openalex.org/W1975875968","https://openalex.org/W1984994707","https://openalex.org/W1988037271","https://openalex.org/W2005073192","https://openalex.org/W2005518172","https://openalex.org/W2009550290","https://openalex.org/W2015782150","https://openalex.org/W2021748110","https://openalex.org/W2022476850","https://openalex.org/W2025556769","https://openalex.org/W2026503476","https://openalex.org/W2058015994","https://openalex.org/W2058455284","https://openalex.org/W2059197104","https://openalex.org/W2065651723","https://openalex.org/W2070505319","https://openalex.org/W2071302369","https://openalex.org/W2078047235","https://openalex.org/W2081234188","https://openalex.org/W2083051183","https://openalex.org/W2085379340","https://openalex.org/W2087952495","https://openalex.org/W2095705004","https://openalex.org/W2106525823","https://openalex.org/W2119652738","https://openalex.org/W2189911347","https://openalex.org/W2210141040","https://openalex.org/W2295598076","https://openalex.org/W2320534770","https://openalex.org/W2401258374","https://openalex.org/W2472085920","https://openalex.org/W2526925775","https://openalex.org/W2556014018","https://openalex.org/W2556851635","https://openalex.org/W2562677145","https://openalex.org/W3100704554","https://openalex.org/W3102476541","https://openalex.org/W4250081213"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W2748952813","https://openalex.org/W1531601525","https://openalex.org/W2078814861","https://openalex.org/W2527526854","https://openalex.org/W1976181487","https://openalex.org/W1986764834","https://openalex.org/W657579294"],"abstract_inverted_index":{"Matched":[0],"molecular":[1],"pair":[2],"(MMP)":[3],"analyses":[4],"are":[5],"widely":[6],"used":[7],"in":[8,187,212],"compound":[9,75,92,110,155,214],"optimization":[10,76,215],"projects":[11],"to":[12,38,40,58,174,202],"gain":[13],"insights":[14],"into":[15],"structure-activity":[16],"relationships":[17],"(SAR).":[18],"The":[19,43],"analysis":[20],"is":[21,157],"traditionally":[22],"done":[23],"via":[24],"statistical":[25],"methods":[26,57,122],"but":[27,129],"can":[28,181],"also":[29,140],"be":[30],"employed":[31,119],"together":[32],"with":[33,53,194],"machine":[34,55,120],"learning":[35,56,121],"(ML)":[36],"approaches":[37],"extrapolate":[39],"novel":[41],"compounds.":[42],"here":[44],"introduced":[45],"MMP/ML":[46],"method":[47],"combines":[48],"a":[49,90,108,170,199],"fragment-based":[50],"MMP":[51,193],"implementation":[52],"different":[54,74,213],"obtain":[59],"automated":[60],"SAR":[61,151],"decomposition":[62],"and":[63,70,94,99,146,180,211],"prediction.":[64],"To":[65],"test":[66],"the":[67,105,125,142,154,188],"prediction":[68],"capabilities":[69],"model":[71],"transferability,":[72],"two":[73],"scenarios":[77],"were":[78,115],"designed:":[79],"(1)":[80],"\"new":[81,96],"fragments\"":[82],"which":[83,101],"occurs":[84],"when":[85],"exploring":[86],"new":[87,109,126,143],"fragments":[88,127],"for":[89,103,124,141],"defined":[91],"series":[93,156,179],"(2)":[95],"static":[97,144],"core":[98,145],"transformations\"":[100],"resembles":[102],"instance":[104],"identification":[106],"of":[107,153],"series.":[111],"Very":[112],"good":[113],"results":[114],"achieved":[116],"by":[117],"all":[118,166],"especially":[123],"case,":[128],"overall":[130],"deep":[131,195],"neural":[132,196],"network":[133],"models":[134,163,175],"performed":[135],"best,":[136],"allowing":[137],"reliable":[138],"predictions":[139,206],"transformations":[147],"scenario,":[148],"where":[149],"comprehensive":[150],"knowledge":[152],"missing.":[158],"Furthermore,":[159],"we":[160],"show":[161],"that":[162],"trained":[164,176],"on":[165,177,207],"available":[167],"data":[168,209],"have":[169],"higher":[171],"generalizability":[172],"compared":[173],"focused":[178],"extend":[182],"beyond":[183],"chemical":[184],"space":[185],"covered":[186],"training":[189],"data.":[190],"Thus,":[191],"coupling":[192],"networks":[197],"provides":[198],"promising":[200],"approach":[201],"make":[203],"high":[204],"quality":[205],"various":[208],"sets":[210],"scenarios.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}