{"id":"https://openalex.org/W7225327250","doi":"https://doi.org/10.26434/chemrxiv.15011727/v1","title":"A Scoping Review of Diffusion-Based De Novo Molecular Generation: Architectures, Evaluation, and Open Challenges for Computational Drug Discovery","display_name":"A Scoping Review of Diffusion-Based De Novo Molecular Generation: Architectures, Evaluation, and Open Challenges for Computational Drug Discovery","publication_year":2026,"publication_date":"2026-11-05","ids":{"openalex":"https://openalex.org/W7225327250","doi":"https://doi.org/10.26434/chemrxiv.15011727/v1"},"language":"en","primary_location":{"id":"doi:10.26434/chemrxiv.15011727/v1","doi":"https://doi.org/10.26434/chemrxiv.15011727/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15011727/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15011727/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15011727/v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160881908","display_name":"Thomas Tsuma","orcid":"https://orcid.org/0009-0009-6283-6181","observed_orcids":["https://orcid.org/0009-0009-6283-6181"]},"institutions":[{"id":"https://openalex.org/I12649496","display_name":"INTI International University","ror":"https://ror.org/03fj82m46","country_code":"MY","type":"education","lineage":["https://openalex.org/I12649496"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Thomas Tsuma","raw_affiliation_strings":["Faculty of Data Science and Information Technology , INTI International University , Persiaran Perdana BBN , Putra Nilai , Bandar Baru Nilai , 71800 Nilai , Negeri Sembilan , Malaysia"],"raw_orcid":"https://orcid.org/0009-0009-6283-6181","affiliations":[{"raw_affiliation_string":"Faculty of Data Science and Information Technology , INTI International University , Persiaran Perdana BBN , Putra Nilai , Bandar Baru Nilai , 71800 Nilai , Negeri Sembilan , Malaysia","institution_ids":["https://openalex.org/I12649496"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160812467","display_name":"Zaid Amin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I12649496","display_name":"INTI International University","ror":"https://ror.org/03fj82m46","country_code":"MY","type":"education","lineage":["https://openalex.org/I12649496"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Zaid Amin","raw_affiliation_strings":["Faculty of Data Science and Information Technology , INTI International University , Persiaran Perdana BBN , Putra Nilai , Bandar Baru Nilai , 71800 Nilai , Negeri Sembilan , Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Data Science and Information Technology , INTI International University , Persiaran Perdana BBN , Putra Nilai , Bandar Baru Nilai , 71800 Nilai , Negeri Sembilan , Malaysia","institution_ids":["https://openalex.org/I12649496"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160814649","display_name":"Rahma Santhi Zinaida","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahma Santhi Zinaida","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.0003000000142492354,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/diffusion-models","display_name":"diffusion models","score":0.968999981880188},{"id":"https://openalex.org/keywords/de-novo-molecular-design","display_name":"de novo molecular design","score":0.8949999809265137},{"id":"https://openalex.org/keywords/molecular-generation","display_name":"molecular generation","score":0.48500001430511475},{"id":"https://openalex.org/keywords/molecular-representation","display_name":"molecular representation","score":0.7919999957084656},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.7739999890327454},{"id":"https://openalex.org/keywords/autoencoder","display_name":"autoencoder","score":0.9039999842643738},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.8899999856948853},{"id":"https://openalex.org/keywords/evaluation-indicators","display_name":"evaluation metrics","score":0.6499999761581421},{"id":"https://openalex.org/keywords/controllability","display_name":"controllability","score":0.8529999852180481},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.8859999775886536},{"id":"https://openalex.org/keywords/molecular-symmetry","display_name":"molecular symmetry","score":0.6169999837875366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6358000040054321},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.6151999831199646},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.605400025844574},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5235000252723694},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.44769999384880066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44029998779296875},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.396699994802475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39070001244544983},{"id":"https://openalex.org/C66782513","wikidata":"https://www.wikidata.org/wiki/Q864601","display_name":"Biomedicine","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.3206999897956848},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C2778464652","wikidata":"https://www.wikidata.org/wiki/Q309849","display_name":"Open research","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C189708586","wikidata":"https://www.wikidata.org/wiki/Q1504425","display_name":"Systematic review","level":3,"score":0.26350000500679016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C184356942","wikidata":"https://www.wikidata.org/wiki/Q830382","display_name":"Best practice","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.26434/chemrxiv.15011727/v1","doi":"https://doi.org/10.26434/chemrxiv.15011727/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15011727/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15011727/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.26434/chemrxiv.15011727/v1","doi":"https://doi.org/10.26434/chemrxiv.15011727/v1","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15011727/v1","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15011727/v1","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":null,"raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[{"display_name":"Systematic Review","id":"https://openalex.org/study-designs/systematic-review"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225327250.pdf","grobid_xml":"https://content.openalex.org/works/W7225327250.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2788775653","https://openalex.org/W2806351858","https://openalex.org/W3166372986","https://openalex.org/W4221147853","https://openalex.org/W4288099666","https://openalex.org/W4384918448","https://openalex.org/W4386629205","https://openalex.org/W4388963710","https://openalex.org/W4389761551","https://openalex.org/W4390632065","https://openalex.org/W4391610180","https://openalex.org/W4394293302","https://openalex.org/W4394711270","https://openalex.org/W4400656170","https://openalex.org/W4402635776","https://openalex.org/W4403782810","https://openalex.org/W4405729533","https://openalex.org/W4407590260","https://openalex.org/W4408354097","https://openalex.org/W4415201053","https://openalex.org/W4415312334","https://openalex.org/W4416018549","https://openalex.org/W4416104222","https://openalex.org/W6910616346","https://openalex.org/W6910651039","https://openalex.org/W7115584987","https://openalex.org/W7126185311","https://openalex.org/W7139914847","https://openalex.org/W7196994330"],"related_works":["https://openalex.org/W7197004308","https://openalex.org/W4389818585","https://openalex.org/W7213944779","https://openalex.org/W4412657387","https://openalex.org/W7152535398","https://openalex.org/W4411545606","https://openalex.org/W4402887448","https://openalex.org/W7154313303","https://openalex.org/W4408149544","https://openalex.org/W4409118848"],"abstract_inverted_index":{"Diffusion":[0],"models":[1,35],"form":[2],"the":[3,15,73,90,109,145,166,169,185,199,207,217,231],"bulk":[4],"of":[5,32,45,58,227],"generative":[6,25],"frameworks":[7],"used":[8,114],"in":[9,63,168,202],"de":[10,64],"novo":[11,65],"molecular":[12,22,101,213],"design,":[13],"yet":[14],"literature":[16,91],"remains":[17,190],"fragmented":[18],"across":[19,192],"model":[20],"formulations,":[21],"representations,":[23,102],"and":[24,27,70,81,104,107,111,136,141,160,195,204,215],"tasks,":[26],"inadequate":[28],"systematic":[29],"accounts":[30],"exist":[31],"how":[33],"these":[34],"are":[36],"steered":[37],"towards":[38],"molecules":[39,228],"with":[40],"desired":[41],"properties,":[42],"an":[43],"aspect":[44],"drug":[46,66],"discovery":[47,67],"that":[48,229],"is":[49,177,179],"paramount":[50],"to":[51,152,219],"acceptance.":[52],"We":[53,197],"present":[54],"a":[55,174,180],"scoping":[56],"review":[57],"diffusion-based":[59],"neural":[60],"networks":[61],"applied":[62,178],"between":[68],"2020":[69],"2026.":[71],"Following":[72],"PRISMA-ScR":[74],"(Preferred":[75],"Reporting":[76],"Items":[77],"for":[78,84,211],"Systematic":[79],"Reviews":[80],"Meta-Analyses":[82],"extension":[83],"Scoping":[85],"Reviews)":[86],"protocol,":[87],"we":[88],"categorise":[89],"into":[92],"non-mutually":[93],"exclusive":[94],"themes":[95],"covering":[96],"methodological":[97],"contributions,":[98],"conditioning":[99,149,175],"mechanisms,":[100],"symmetries,":[103],"multi-modal":[105],"integrations,":[106],"outline":[108,216],"datasets":[110],"evaluation":[112,189],"metrics":[113],"throughout.":[115],"Three":[116],"findings":[117],"emerge.":[118],"First,":[119],"diffusion":[120],"did":[121],"not":[122],"displace":[123],"earlier":[124],"architectures":[125],"so":[126],"much":[127],"as":[128,139,206,222],"absorb":[129],"them:":[130],"Graph":[131],"Neural":[132],"Networks":[133],"(GNNs),":[134],"Autoencoders,":[135],"Transformers":[137],"persist":[138],"backbones,":[140],"what":[142],"changed":[143],"was":[144],"training":[146],"objective.":[147],"Second,":[148],"strategies":[150],"reduce":[151],"structural":[153],"anchoring,":[154],"target-aware":[155],"biochemical":[156],"conditioning,":[157],"property-driven":[158],"steering,":[159],"multimodal":[161],"latent":[162],"conditioning;":[163],"within":[164],"these,":[165],"point":[167],"reverse":[170],"trajectory":[171],"at":[172],"which":[173],"signal":[176,186],"design":[181],"variable":[182],"distinct":[183],"from":[184],"itself.":[187],"Third,":[188],"unstandardised":[191],"frameworks,":[193],"datasets,":[194],"definitions.":[196],"identify":[198],"resulting":[200],"gaps":[201],"controllability":[203],"interpretability":[205],"central":[208],"open":[209],"challenge":[210],"conditioned":[212],"generation":[214,226],"direction":[218],"ease":[220],"them":[221],"this":[223],"would":[224],"enable":[225],"match":[230],"preferred":[232],"property":[233],"profiles.":[234]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-11-06T00:00:00"}
