Pub Date : 2026-08-19DOI: 10.1038/s41587-026-03238-6
M. Frank Erasmus, Daniel Bedinger, Elizabeth Hopkins, Ginger Ferguson, Justine Strickler, Christilyn P. Graff, Samantha R. Summers, Stacy L. Capehart, Joshua D. Slocum, Crystal Richardson, Sumit Kumar, Zhifei Sun, Yujie Shang, Jixian Zhang, Ming Gu, Lixia Yi, Alon Wellner, Shuangjia Zheng, Wei Lu, Pietro Sormanni, Matthew Greenig, Haiping Zhang, Brendan T. Mann, Mahdi Baghbanzadeh, Ali Rahnavard, Gregory L. Moore, Huaiyu Sun, Ying Ding, Alex Nisthal, Jitendra Kanodia, Matthew J. Bernett, Aurélien Pélissier, Yanjun Shao, Maria Rodriguez Martinez, Karthik Ramesh, Horacio Nastri, Andreas Evers, Anhar Abdelatif, Andrew J. Bordner, Mykola Bordyuh, Lim Heo, Brian A. Kidd, H. Serhat Tetikol, Shuai Wei, Jung-Eun Shin, Ryan Peckner, Leigh Manley, Ajitesh Lunge, Yashas Devasurmutt, Bora Guloglu, Liviu Copoiu, Miles McGibbon, Monica L. Fernandez-Quintero, Nitesh Mishra, Sean M. Callaghan, Olivia M. Swanson
Experimentally validated prospective, blinded benchmarks are needed to separate durable advances from hype in computational antibody design. Here AIntibody, a challenge inspired by the Critical Assessment of Structure Prediction, tests 511 artificial intelligence (AI)-designed or predicted antibodies from 29 organizations on three tasks: in silico affinity maturation from phase 1 sequencing outputs, affinity ranking within heavy-chain complementarity-determining region 3 (HCDR3) clusters of a selection output and CDR design of proteins not included in a selection output. Validated with diverse experimental assays, several groups produced developable antibodies with affinities <100 pM. However, these successes were exceptions that did not transfer across tasks. Affinity-matured antibodies were modeled effectively. Except for one model, predicting high-affinity clones from clustered HCDR3 datasets was worse than random clone picking. Out-of-library design was highly variable for most method submissions, with many failing to outperform standard selections. The AIntibody challenge shows that AI can optimize antibodies in defined, biologically grounded regimes, in addition to highlighting critical gaps including affinity prediction and library-inspired antibody design and cross-task generalization.
{"title":"A blinded, prospective benchmark of in silico antibody discovery anchored to experimental affinity and developability","authors":"M. Frank Erasmus, Daniel Bedinger, Elizabeth Hopkins, Ginger Ferguson, Justine Strickler, Christilyn P. Graff, Samantha R. Summers, Stacy L. Capehart, Joshua D. Slocum, Crystal Richardson, Sumit Kumar, Zhifei Sun, Yujie Shang, Jixian Zhang, Ming Gu, Lixia Yi, Alon Wellner, Shuangjia Zheng, Wei Lu, Pietro Sormanni, Matthew Greenig, Haiping Zhang, Brendan T. Mann, Mahdi Baghbanzadeh, Ali Rahnavard, Gregory L. Moore, Huaiyu Sun, Ying Ding, Alex Nisthal, Jitendra Kanodia, Matthew J. Bernett, Aurélien Pélissier, Yanjun Shao, Maria Rodriguez Martinez, Karthik Ramesh, Horacio Nastri, Andreas Evers, Anhar Abdelatif, Andrew J. Bordner, Mykola Bordyuh, Lim Heo, Brian A. Kidd, H. Serhat Tetikol, Shuai Wei, Jung-Eun Shin, Ryan Peckner, Leigh Manley, Ajitesh Lunge, Yashas Devasurmutt, Bora Guloglu, Liviu Copoiu, Miles McGibbon, Monica L. Fernandez-Quintero, Nitesh Mishra, Sean M. Callaghan, Olivia M. Swanson","doi":"10.1038/s41587-026-03238-6","DOIUrl":"https://doi.org/10.1038/s41587-026-03238-6","url":null,"abstract":"Experimentally validated prospective, blinded benchmarks are needed to separate durable advances from hype in computational antibody design. Here AIntibody, a challenge inspired by the Critical Assessment of Structure Prediction, tests 511 artificial intelligence (AI)-designed or predicted antibodies from 29 organizations on three tasks: in silico affinity maturation from phase 1 sequencing outputs, affinity ranking within heavy-chain complementarity-determining region 3 (HCDR3) clusters of a selection output and CDR design of proteins not included in a selection output. Validated with diverse experimental assays, several groups produced developable antibodies with affinities <100 pM. However, these successes were exceptions that did not transfer across tasks. Affinity-matured antibodies were modeled effectively. Except for one model, predicting high-affinity clones from clustered HCDR3 datasets was worse than random clone picking. Out-of-library design was highly variable for most method submissions, with many failing to outperform standard selections. The AIntibody challenge shows that AI can optimize antibodies in defined, biologically grounded regimes, in addition to highlighting critical gaps including affinity prediction and library-inspired antibody design and cross-task generalization.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"187 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-19DOI: 10.1038/s41587-026-03300-3
DNA writing is entering a period of rapid innovation, with enzymatic and cellular approaches challenging decades-old chemistry. Although none yet delivers long, accurate DNA at the scale biology ultimately requires, continued advances promise to remove one of the field’s most persistent bottlenecks and enable experiments that are currently out of reach.
{"title":"From reading to writing","authors":"","doi":"10.1038/s41587-026-03300-3","DOIUrl":"10.1038/s41587-026-03300-3","url":null,"abstract":"DNA writing is entering a period of rapid innovation, with enzymatic and cellular approaches challenging decades-old chemistry. Although none yet delivers long, accurate DNA at the scale biology ultimately requires, continued advances promise to remove one of the field’s most persistent bottlenecks and enable experiments that are currently out of reach.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 9","pages":"1413-1414"},"PeriodicalIF":44.5,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41587-026-03300-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148795641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-19DOI: 10.1038/s41587-026-03224-y
Pengxia Qin, Qiushi Qin, Yanyun Hao, Ming Liu, Yijia Li, Yunxuan Liu, Ziqiong Jiang, Tao Ma, Weixue Wang, Yu Hou, Ruochuan Liu, Yajuan Wang, Buyao Li, Xiaorong Guo, Kun Wang, Pengting Zhang, Zhiqiang Zhao, Baocai Xing, Bin Ma, Yinuo Wang, Ning Zhang, Chuanhui Han, Lei Miao
The development of cGAS–STING (stimulator of interferon genes) agonists as mRNA vaccine adjuvants has been hampered by widespread STING expression and by the observation that codelivered STING agonists suppress antigen mRNA translation. Here, to address these challenges, we engineer synchronized STING (Syn-STING): a lipid nanoparticle (LNP) codelivering antigen mRNA, mRNA encoding full-length STING transmembrane protein and a bioorthogonal-like delayed-release STING activator, DMXAA. DMXAA release is controlled by a biodegradable linker, enabling localized mouse STING activation while avoiding systemic endogeneous human STING recognition. In humanized STING mouse models, we test human papillomavirus E7 and ovalbumin antigens with mouse STING or a human STING mutant engineered for DMXAA specificity. Intratumoral or subcutaneous LNPs are preferentially internalized by myeloid cells, preserving antigen expression fidelity, achieving localized STING activation in antigen-presenting cells and preventing systemic regulatory B cell differentiation and immunocyte apoptosis. The Syn-STING vaccine elicits robust adaptive responses and Th1-biased T cell immunity. It suppresses tumor growth and prolongs survival while exhibiting negligible anti-STING immunity.
{"title":"Enhanced antitumor immunity of mRNA vaccines by bioorthogonal-like delayed activation of exogeneous STING","authors":"Pengxia Qin, Qiushi Qin, Yanyun Hao, Ming Liu, Yijia Li, Yunxuan Liu, Ziqiong Jiang, Tao Ma, Weixue Wang, Yu Hou, Ruochuan Liu, Yajuan Wang, Buyao Li, Xiaorong Guo, Kun Wang, Pengting Zhang, Zhiqiang Zhao, Baocai Xing, Bin Ma, Yinuo Wang, Ning Zhang, Chuanhui Han, Lei Miao","doi":"10.1038/s41587-026-03224-y","DOIUrl":"https://doi.org/10.1038/s41587-026-03224-y","url":null,"abstract":"The development of cGAS–STING (stimulator of interferon genes) agonists as mRNA vaccine adjuvants has been hampered by widespread STING expression and by the observation that codelivered STING agonists suppress antigen mRNA translation. Here, to address these challenges, we engineer synchronized STING (Syn-STING): a lipid nanoparticle (LNP) codelivering antigen mRNA, mRNA encoding full-length STING transmembrane protein and a bioorthogonal-like delayed-release STING activator, DMXAA. DMXAA release is controlled by a biodegradable linker, enabling localized mouse STING activation while avoiding systemic endogeneous human STING recognition. In humanized STING mouse models, we test human papillomavirus E7 and ovalbumin antigens with mouse STING or a human STING mutant engineered for DMXAA specificity. Intratumoral or subcutaneous LNPs are preferentially internalized by myeloid cells, preserving antigen expression fidelity, achieving localized STING activation in antigen-presenting cells and preventing systemic regulatory B cell differentiation and immunocyte apoptosis. The Syn-STING vaccine elicits robust adaptive responses and Th1-biased T cell immunity. It suppresses tumor growth and prolongs survival while exhibiting negligible anti-STING immunity.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"70 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-18DOI: 10.1038/s41587-026-03278-y
Matthew Vogel, Zander Cowan, Amitabh Chandra
An analysis of FDA-approved drugs reveals uneven timing and concentration of revenue life cycles across modalities and therapeutic areas, offering evidence to guide innovation strategy and policy design in a post-Inflation Reduction Act world.
{"title":"Lessons from drug revenue life cycles: distributions across modalities and therapeutic areas","authors":"Matthew Vogel, Zander Cowan, Amitabh Chandra","doi":"10.1038/s41587-026-03278-y","DOIUrl":"10.1038/s41587-026-03278-y","url":null,"abstract":"An analysis of FDA-approved drugs reveals uneven timing and concentration of revenue life cycles across modalities and therapeutic areas, offering evidence to guide innovation strategy and policy design in a post-Inflation Reduction Act world.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 9","pages":"1437-1440"},"PeriodicalIF":44.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148795702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-18DOI: 10.1038/s41587-026-03293-z
Ken Garber
Each year, Nature Biotechnology highlights companies that received sizeable early-stage funding in the previous year. Dispatch Bio delivers antigens to solid tumors for CAR T immunotherapy.
{"title":"Editor’s pick: Dispatch Biotherapeutics","authors":"Ken Garber","doi":"10.1038/s41587-026-03293-z","DOIUrl":"10.1038/s41587-026-03293-z","url":null,"abstract":"Each year, Nature Biotechnology highlights companies that received sizeable early-stage funding in the previous year. Dispatch Bio delivers antigens to solid tumors for CAR T immunotherapy.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"44 9","pages":"1428-1429"},"PeriodicalIF":44.5,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148795647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-17DOI: 10.1038/s41587-026-03256-4
{"title":"A scalable platform to discover and characterize substrates of molecular glue degraders.","authors":"","doi":"10.1038/s41587-026-03256-4","DOIUrl":"https://doi.org/10.1038/s41587-026-03256-4","url":null,"abstract":"","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":" ","pages":""},"PeriodicalIF":44.5,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148795731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-17DOI: 10.1038/s41587-026-03258-2
Hyuncheol Jung, Pascal Devant, Carter Ching, Mineto Ota, Emma Dann, Ronghui Zhu, Chandrima Modak, Ana Vasquez-Ibarra, Jennifer R. Hamilton, Zachary Steinhart, Wayne Ngo, Luis Sandoval, Jae Hyung Jung, Jae Hyun J. Lee, Da Xu, Meirui An, Esha Urs, Peixin Amy Chen, Vincent Allain, Takuya Tada, Luke A. Gilbert, Brian R. Shy, Jonathan K. Pritchard, James K. Nuñez, Nathaniel R. Landau, David R. Liu, Justin Eyquem, Jennifer A. Doudna, Alexander Marson, Julia Carnevale
Primary human myeloid cells hold promise for immunotherapies, yet efficient, scalable technologies for engineering and screening in these cells remain limited. Here we present a virus-like particle (VLP)-based toolkit that delivers diverse CRISPR editing modalities to human monocytes, macrophages and dendritic cells with high efficiency while preserving viability and innate immune responsiveness. VLP-mediated delivery of ribonucleoproteins supports gene knockout, base editing and epigenetic silencing. Combined with adeno-associated virus-mediated donor delivery, this approach enables site-specific integration of large DNA sequences by homology-directed repair. We developed SLICeVLP, which pairs sgRNA delivery by VPX-lentivirus with Cas9 protein delivery by engineered VLPs, and used it for pooled loss-of-function and Perturb-seq screens in human macrophages. We uncovered regulators of tumor necrosis factor (TNF) and CD80 expression, converging on TNFAIP3 as a central regulator of inflammatory polarization. TNFAIP3 ablation drove a proinflammatory state resistant to suppressive repolarization and enhanced cytotoxicity in chimeric antigen receptor macrophages. This system enables unbiased functional genomics in primary human myeloid cells, with implications for myeloid cell therapy design.
{"title":"Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells","authors":"Hyuncheol Jung, Pascal Devant, Carter Ching, Mineto Ota, Emma Dann, Ronghui Zhu, Chandrima Modak, Ana Vasquez-Ibarra, Jennifer R. Hamilton, Zachary Steinhart, Wayne Ngo, Luis Sandoval, Jae Hyung Jung, Jae Hyun J. Lee, Da Xu, Meirui An, Esha Urs, Peixin Amy Chen, Vincent Allain, Takuya Tada, Luke A. Gilbert, Brian R. Shy, Jonathan K. Pritchard, James K. Nuñez, Nathaniel R. Landau, David R. Liu, Justin Eyquem, Jennifer A. Doudna, Alexander Marson, Julia Carnevale","doi":"10.1038/s41587-026-03258-2","DOIUrl":"https://doi.org/10.1038/s41587-026-03258-2","url":null,"abstract":"Primary human myeloid cells hold promise for immunotherapies, yet efficient, scalable technologies for engineering and screening in these cells remain limited. Here we present a virus-like particle (VLP)-based toolkit that delivers diverse CRISPR editing modalities to human monocytes, macrophages and dendritic cells with high efficiency while preserving viability and innate immune responsiveness. VLP-mediated delivery of ribonucleoproteins supports gene knockout, base editing and epigenetic silencing. Combined with adeno-associated virus-mediated donor delivery, this approach enables site-specific integration of large DNA sequences by homology-directed repair. We developed SLICeVLP, which pairs sgRNA delivery by VPX-lentivirus with Cas9 protein delivery by engineered VLPs, and used it for pooled loss-of-function and Perturb-seq screens in human macrophages. We uncovered regulators of tumor necrosis factor (TNF) and CD80 expression, converging on TNFAIP3 as a central regulator of inflammatory polarization. TNFAIP3 ablation drove a proinflammatory state resistant to suppressive repolarization and enhanced cytotoxicity in chimeric antigen receptor macrophages. This system enables unbiased functional genomics in primary human myeloid cells, with implications for myeloid cell therapy design.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"70 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148769129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-13DOI: 10.1038/s41587-026-03245-7
Fabio Cumbo, Daniel Blankenberg
Accurately characterizing metagenome-assembled genomes remains a substantial challenge due to the presence of sequencing errors, incomplete assembly and contamination. Here, we present MetaSBT, a tool for organizing, indexing and characterizing microbial reference genomes and metagenome-assembled genomes, demonstrated in this study using viruses. MetaSBT identifies clusters of genomes across all seven taxonomic levels using the Sequence Bloom Tree data structure, which relies on Bloom filters to index large amounts of genomes based on their k-mer composition. We built an initial set of databases composed of over 190,000 viral genomes from public sources, grouped into sequence-consistent clusters at different taxonomic levels. We defined over 40,000 candidate species, ~80% of which, to our knowledge, do not match viral species in reference databases to date. Furthermore, we showed that our databases are useful to existing quantitative metagenomic profilers to unlock the detection of unknown microbes and the estimation of their abundance in metagenomic samples. The open-source framework and databases are fully integrated into the Galaxy platform.
{"title":"Characterization of microbial dark matter at scale with MetaSBT and taxonomy-aware Sequence Bloom Trees","authors":"Fabio Cumbo, Daniel Blankenberg","doi":"10.1038/s41587-026-03245-7","DOIUrl":"https://doi.org/10.1038/s41587-026-03245-7","url":null,"abstract":"Accurately characterizing metagenome-assembled genomes remains a substantial challenge due to the presence of sequencing errors, incomplete assembly and contamination. Here, we present MetaSBT, a tool for organizing, indexing and characterizing microbial reference genomes and metagenome-assembled genomes, demonstrated in this study using viruses. MetaSBT identifies clusters of genomes across all seven taxonomic levels using the Sequence Bloom Tree data structure, which relies on Bloom filters to index large amounts of genomes based on their k-mer composition. We built an initial set of databases composed of over 190,000 viral genomes from public sources, grouped into sequence-consistent clusters at different taxonomic levels. We defined over 40,000 candidate species, ~80% of which, to our knowledge, do not match viral species in reference databases to date. Furthermore, we showed that our databases are useful to existing quantitative metagenomic profilers to unlock the detection of unknown microbes and the estimation of their abundance in metagenomic samples. The open-source framework and databases are fully integrated into the Galaxy platform.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"35 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148728866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-08-13DOI: 10.1038/s41587-026-03237-7
Pius Galli, Shuhao Xiao (肖书豪), Yanxiang Meng, Alexander Hanzl, Alexandra M. Bendel, Regina Baur, Jacob D. Aguirre, Anna M. Diaz-Rovira, Maximilian R. Stammnitz, Georg Kempf, Lukas Kater, Kenji Shimada, Ye Wei (韦业), Andreas Scheck, Dominique Klein, Simone Cavadini, Ben Lehner, Guillaume Diss, Bruno E. Correia, Nicolas H. Thomä
Molecular glue degraders (MGDs), such as pomalidomide, induce degradation of non-native substrates by the cullin-RING E3 ligase 4 (CRL4) through its substrate receptor cereblon (CRBN). Here, to explore CRBN programmability, we tested whether reported CRBN–MGD substrates are part of a network of latent CRBN interactors, proteins capable of MGD-induced CRBN binding without detectable degradation. Leveraging a highly parallel protein complementation assay (GluePCA) to measure MGD-induced interaction between CRBN and zinc fingers, we identified ~210 zinc fingers bound to CRBN–pomalidomide, where top binders are already reported as degraded by dedicated MGDs. To map latent CRBN–MGD interactions proteome-wide and define the accessible CRBN interaction space, we combined artificial intelligence-derived protein surface queries (MaSIF-mimicry) with GluePCA. This pipeline identified 6 known and 43 novel CRBN–pomalidomide binders, including orthogonally validated hits. We find that these binders provide privileged starting points for MGD development. We expect this binding-focused workflow to be applicable to other MGD–E3 ligase systems, potentially extending the scope of this emerging drug class.
{"title":"Proteome-wide identification of the druggable CRBN interactome","authors":"Pius Galli, Shuhao Xiao \u0000 (肖书豪), Yanxiang Meng, Alexander Hanzl, Alexandra M. Bendel, Regina Baur, Jacob D. Aguirre, Anna M. Diaz-Rovira, Maximilian R. Stammnitz, Georg Kempf, Lukas Kater, Kenji Shimada, Ye Wei \u0000 (韦业), Andreas Scheck, Dominique Klein, Simone Cavadini, Ben Lehner, Guillaume Diss, Bruno E. Correia, Nicolas H. Thomä","doi":"10.1038/s41587-026-03237-7","DOIUrl":"https://doi.org/10.1038/s41587-026-03237-7","url":null,"abstract":"Molecular glue degraders (MGDs), such as pomalidomide, induce degradation of non-native substrates by the cullin-RING E3 ligase 4 (CRL4) through its substrate receptor cereblon (CRBN). Here, to explore CRBN programmability, we tested whether reported CRBN–MGD substrates are part of a network of latent CRBN interactors, proteins capable of MGD-induced CRBN binding without detectable degradation. Leveraging a highly parallel protein complementation assay (GluePCA) to measure MGD-induced interaction between CRBN and zinc fingers, we identified ~210 zinc fingers bound to CRBN–pomalidomide, where top binders are already reported as degraded by dedicated MGDs. To map latent CRBN–MGD interactions proteome-wide and define the accessible CRBN interaction space, we combined artificial intelligence-derived protein surface queries (MaSIF-mimicry) with GluePCA. This pipeline identified 6 known and 43 novel CRBN–pomalidomide binders, including orthogonally validated hits. We find that these binders provide privileged starting points for MGD development. We expect this binding-focused workflow to be applicable to other MGD–E3 ligase systems, potentially extending the scope of this emerging drug class.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"161 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148729043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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