{"id":"https://openalex.org/W4393459833","doi":"https://doi.org/10.5281/zenodo.10029195","title":"Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease","display_name":"Machine learning-based q-RASAR approach for the in silico identification of novel multi-target inhibitors against Alzheimer's disease","publication_year":2023,"publication_date":"2023-10-21","ids":{"openalex":"https://openalex.org/W4393459833","doi":"https://doi.org/10.5281/zenodo.10029195"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.10029195","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.10029195","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.10029195","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100656114","display_name":"Vinay Kumar","orcid":"https://orcid.org/0000-0002-6809-7633"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Kumar, Vinay","raw_affiliation_strings":["Jadavpur University"],"affiliations":[{"raw_affiliation_string":"Jadavpur University","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066162636","display_name":"Arkaprava Banerjee","orcid":"https://orcid.org/0000-0001-8468-0784"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Banerjee, Arkaprava","raw_affiliation_strings":["Jadavpur University"],"affiliations":[{"raw_affiliation_string":"Jadavpur University","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087029647","display_name":"Kunal Roy","orcid":"https://orcid.org/0000-0003-4486-8074"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Roy, Kunal","raw_affiliation_strings":["Jadavpur University"],"affiliations":[{"raw_affiliation_string":"Jadavpur University","institution_ids":["https://openalex.org/I170979836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100656114"],"corresponding_institution_ids":["https://openalex.org/I170979836"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9973000288009644,"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":0.9973000288009644,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9861999750137329,"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/in-silico","display_name":"In silico","score":0.9236552715301514},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7472672462463379},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.6986604332923889},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.5909039378166199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44827696681022644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4384339153766632},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4151769280433655},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.39481306076049805},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.20829811692237854},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14671576023101807},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.08891263604164124},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.05381473898887634},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.045506805181503296}],"concepts":[{"id":"https://openalex.org/C2775905019","wikidata":"https://www.wikidata.org/wiki/Q192572","display_name":"In silico","level":3,"score":0.9236552715301514},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7472672462463379},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.6986604332923889},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.5909039378166199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44827696681022644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4384339153766632},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4151769280433655},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.39481306076049805},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.20829811692237854},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14671576023101807},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.08891263604164124},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.05381473898887634},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.045506805181503296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.10029195","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.10029195","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.10029195","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.10029195","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2003194288","https://openalex.org/W2513589746","https://openalex.org/W2153919606","https://openalex.org/W2213189664","https://openalex.org/W2074002899","https://openalex.org/W2062254828","https://openalex.org/W4237480606","https://openalex.org/W2936968863","https://openalex.org/W4392342240","https://openalex.org/W2941821699"],"abstract_inverted_index":{"In":[0,61],"the":[1,10,21,33,55,89,98,111,124,146,158,164,168,182,195,200,204,219,233,241,268],"present":[2],"research,":[3],"we":[4,64,142,172,191],"propose":[5],"a":[6,43,115],"novel":[7,101],"approach,":[8],"termed":[9],"Machine":[11],"Learning":[12],"(ML)-Based":[13],"q-RASAR":[14,30,59,68,154,186,197],"(quantitative":[15,148],"read-across":[16,37,149],"structure-activity":[17],"relationship)":[18,151],"method,":[19],"for":[20,97,132,255,264],"identification":[22],"of":[23,35,57,86,100,114,117,135,185,244,271],"potential":[24,262],"multi-target":[25,272],"inhibitors":[26],"against":[27,70,167],"AD.":[28],"The":[29,104],"effectively":[31],"combines":[32],"principles":[34],"both":[36],"and":[38,83,128,152,187,225],"2D":[39,94],"QSAR":[40,95],"approaches.":[41],"As":[42],"result,":[44],"it":[45],"is":[46],"imperative":[47],"to":[48,109,156,163,180,215],"take":[49],"into":[50,218],"account":[51],"similarity-related":[52],"aspects":[53,243],"in":[54,93],"process":[56],"developing":[58],"models.":[60,189],"this":[62],"investigation,":[63],"have":[65,143,173,192,212],"implemented":[66],"ML-based":[67],"modeling":[69],"seven":[71,175],"major":[72],"targets":[73],"(AChE,":[74],"BuChE,":[75],"BACE1,":[76],"5-HT6,":[77],"CDK-5":[78],"enzymes,":[79],"Amyloid":[80],"precursor":[81],"protein,":[82],"Tau":[84],"aggregation)":[85],"AD":[87],"using":[88],"initially":[90],"selected":[91],"features":[92,161],"models":[96,105,155,238,249],"identifications":[99],"multitarget":[102],"inhibitors.":[103,273],"were":[106],"individually":[107],"used":[108],"check":[110],"applicability":[112],"domain":[113],"pool":[116],"407270":[118],"natural":[119],"products":[120],"(NPs)":[121],"obtained":[122,236],"from":[123,237],"COCONUT":[125],"database":[126],"(https://coconut.naturalproducts.net/download)":[127],"provided":[129],"prioritized":[130],"compounds":[131],"experimental":[133],"detection":[134],"their":[136],"performance":[137],"as":[138,203,252],"anti-Alzheimer's":[139],"drugs.":[140],"Furthermore,":[141,171],"also":[144,193],"developed":[145,194],"q-RASAAR":[147,188],"structure-activity-activity":[150],"selectivity-based":[153],"explore":[157],"most":[159],"important":[160],"contributing":[162],"dual":[165],"inhibition":[166],"respective":[169],"targets.":[170],"applied":[174],"distinct":[176],"machine":[177],"learning":[178],"algorithms":[179],"enhance":[181],"predictive":[183],"abilities":[184],"Moreover,":[190,208],"univariate":[196],"model,":[198],"with":[199,232],"RA":[201],"function":[202],"primary":[205],"independent":[206],"variable.":[207],"molecular":[209,221,258],"docking":[210],"experiments":[211],"been":[213],"conducted":[214],"gain":[216],"insights":[217],"atomic-level":[220],"interactions":[222],"between":[223],"ligands":[224],"enzymes.":[226],"These":[227,247],"observations":[228],"are":[229],"then":[230],"juxtaposed":[231],"structural":[234],"characteristics":[235],"that":[239],"elucidate":[240],"mechanistic":[242],"binding":[245],"events.":[246],"proposed":[248],"may":[250],"serve":[251],"valuable":[253],"tools":[254],"pinpointing":[256],"crucial":[257],"attributes":[259],"when":[260],"designing":[261],"drugs":[263],"Alzheimer's":[265],"therapy":[266],"through":[267],"rational":[269],"design":[270]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
