Tomer Milo, Shiraz Nir Halber, Moriya Raz, Dor Danan, Avi Mayo, Uri Alon
{"title":"Hormone circuit explains why most HPA drugs fail for mood disorders and predicts the few that work.","authors":"Tomer Milo, Shiraz Nir Halber, Moriya Raz, Dor Danan, Avi Mayo, Uri Alon","doi":"10.1038/s44320-024-00083-0","DOIUrl":"10.1038/s44320-024-00083-0","url":null,"abstract":"<p><p>Elevated cortisol in chronic stress and mood disorders causes morbidity including metabolic and cardiovascular diseases. There is therefore interest in developing drugs that lower cortisol by targeting its endocrine pathway, the hypothalamic-pituitary-adrenal (HPA) axis. However, several promising HPA-modulating drugs have failed to reduce long-term cortisol in mood disorders, despite effectiveness in other hypercortisolism conditions such as Cushing's syndrome. The reasons for these failures remain unclear. Here, we use a mathematical model of the HPA axis to demonstrate that the pituitary and adrenal glands compensate for drug effects by adjusting their functional mass, a feedback mechanism absent in Cushing tumors. Our systematic in silico analysis identifies two interventions targeting corticotropin-releasing hormone (CRH) as effective for lowering long-term cortisol. Other targets either fail due to gland mass compensation or harm other aspects of the HPA axis. We propose CRH-neutralizing antibodies and CRH-synthesis inhibitors as potential targets for reducing long-term cortisol in mood disorders and chronic stress. More generally, this study indicates that understanding the slow compensatory mechanisms in endocrine axes can be crucial to prioritize drug targets.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"254-273"},"PeriodicalIF":8.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11876312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029179","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}
{"title":"Epigenetic modifications and metabolic gene mutations drive resistance evolution in response to stimulatory antibiotics.","authors":"Hui Lin, Donglin Wang, Qiaojuan Wang, Jie Mao, Lutong Yang, Yaohui Bai, Jiuhui Qu","doi":"10.1038/s44320-025-00087-4","DOIUrl":"10.1038/s44320-025-00087-4","url":null,"abstract":"<p><p>The antibiotic resistance crisis, fueled by misuse and bacterial evolution, is a major global health threat. Traditional perspectives tie resistance to drug target mechanisms, viewing antibiotics as mere growth inhibitors. New insights revealed that low-dose antibiotics may also serve as signals, unexpectedly promoting bacterial growth. Yet, the development of resistance under these conditions remains unknown. Our study investigated resistance evolution under stimulatory antibiotics and uncovered new genetic mechanisms of resistance linked to metabolic remodeling. We documented a shift from a fast, reversible mechanism driven by methylation in central metabolic pathways to a slower, stable mechanism involving mutations in key metabolic genes. Both mechanisms contribute to a metabolic profile transition from glycolysis to rapid gluconeogenesis. In addition, our findings demonstrated that rising environmental temperatures associated with metabolic evolution accelerated this process, increasing the prevalence of metabolic gene mutations, albeit with a trade-off in interspecific fitness. These findings expand beyond the conventional understanding of resistance mechanisms, proposing a broader metabolic mechanism within the selective window of stimulatory sub-MIC antibiotics, particularly in the context of climate change.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"294-314"},"PeriodicalIF":8.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11876630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008695","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}
Zhong Yao, Jiyoon Kim, Betty Geng, Jinkun Chen, Victoria Wong, Anna Lyakisheva, Jamie Snider, Marina Rudan Dimlić, Sanda Raić, Igor Stagljar
{"title":"A split intein and split luciferase-coupled system for detecting protein-protein interactions.","authors":"Zhong Yao, Jiyoon Kim, Betty Geng, Jinkun Chen, Victoria Wong, Anna Lyakisheva, Jamie Snider, Marina Rudan Dimlić, Sanda Raić, Igor Stagljar","doi":"10.1038/s44320-024-00081-2","DOIUrl":"10.1038/s44320-024-00081-2","url":null,"abstract":"<p><p>Elucidation of protein-protein interactions (PPIs) represents one of the most important methods in biomedical research. Recently, PPIs have started to be exploited for drug discovery purposes and have thus attracted much attention from both the academic and pharmaceutical sectors. We previously developed a sensitive method, Split Intein-Mediated Protein Ligation (SIMPL), for detecting binary PPIs via irreversible splicing of the interacting proteins being investigated. Here, we incorporated tripart nanoluciferase (tNLuc) into the system, providing a luminescence signal which, in conjunction with homogenous liquid phase operation, improves the quantifiability and operability of the assay. Using a reference PPI set, we demonstrated an improvement in both sensitivity and specificity over the original SIMPL assay. Moreover, we designed the new SIMPL-tNLuc ('SIMPL2') platform with an inherent modularity allowing for flexible measurement of molecular modulators of target PPIs, including inhibitors, molecular glues and PROTACs. Our results demonstrate that SIMPL2 is a sensitive, cost- and labor-effective tool suitable for high-throughput screening (HTS) in both PPI mapping and drug discovery applications.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"107-125"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818697","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}
Abel Jansma, Yuelin Yao, Jareth Wolfe, Luigi Del Debbio, Sjoerd V Beentjes, Chris P Ponting, Ava Khamseh
{"title":"High order expression dependencies finely resolve cryptic states and subtypes in single cell data.","authors":"Abel Jansma, Yuelin Yao, Jareth Wolfe, Luigi Del Debbio, Sjoerd V Beentjes, Chris P Ponting, Ava Khamseh","doi":"10.1038/s44320-024-00074-1","DOIUrl":"10.1038/s44320-024-00074-1","url":null,"abstract":"<p><p>Single cells are typically typed by clustering into discrete locations in reduced dimensional transcriptome space. Here we introduce Stator, a data-driven method that identifies cell (sub)types and states without relying on cells' local proximity in transcriptome space. Stator labels the same single cell multiply, not just by type and subtype, but also by state such as activation, maturity or cell cycle sub-phase, through deriving higher-order gene expression dependencies from a sparse gene-by-cell expression matrix. Stator's finer resolution is clear from analyses of mouse embryonic brain, and human healthy or diseased liver. Rather than only coarse-scale labels of cell type, Stator further resolves cell types into subtypes, and these subtypes into stages of maturity and/or cell cycle phases, and yet further into portions of these phases. Among cryptically homogeneous embryonic cells, for example, Stator finds 34 distinct radial glia states whose gene expression forecasts their future GABAergic or glutamatergic neuronal fate. Further, Stator's fine resolution of liver cancer states reveals expression programmes that predict patient survival. We provide Stator as a Nextflow pipeline and Shiny App.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"173-207"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142922177","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}
Kate Sokolina, Saranya Kittanakom, Jamie Snider, Max Kotlyar, Pascal Maurice, Jorge Gandía, Abla Benleulmi-Chaachoua, Kenjiro Tadagaki, Atsuro Oishi, Victoria Wong, Ramy H Malty, Viktor Deineko, Hiroyuki Aoki, Shahreen Amin, Zhong Yao, Xavier Morató, David Otasek, Hiroyuki Kobayashi, Javier Menendez, Daniel Auerbach, Stephane Angers, Natasa Pržulj, Michel Bouvier, Mohan Babu, Francisco Ciruela, Ralf Jockers, Igor Jurisica, Igor Stagljar
{"title":"Author Correction: Systematic protein-protein interaction mapping for clinically relevant human GPCRs.","authors":"Kate Sokolina, Saranya Kittanakom, Jamie Snider, Max Kotlyar, Pascal Maurice, Jorge Gandía, Abla Benleulmi-Chaachoua, Kenjiro Tadagaki, Atsuro Oishi, Victoria Wong, Ramy H Malty, Viktor Deineko, Hiroyuki Aoki, Shahreen Amin, Zhong Yao, Xavier Morató, David Otasek, Hiroyuki Kobayashi, Javier Menendez, Daniel Auerbach, Stephane Angers, Natasa Pržulj, Michel Bouvier, Mohan Babu, Francisco Ciruela, Ralf Jockers, Igor Jurisica, Igor Stagljar","doi":"10.1038/s44320-024-00080-3","DOIUrl":"10.1038/s44320-024-00080-3","url":null,"abstract":"","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":"21 2","pages":"208-209"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790839/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143123016","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}
Seo Jung Hong, Samuel J Resnick, Sho Iketani, Ji Won Cha, Benjamin Alexander Albert, Christopher T Fazekas, Ching-Wen Chang, Hengrui Liu, Shlomi Dagan, Michael R Abagyan, Pavla Fajtová, Bruce Culbertson, Brooklyn Brace, Eswar R Reddem, Farhad Forouhar, J Fraser Glickman, James M Balkovec, Brent R Stockwell, Lawrence Shapiro, Anthony J O'Donoghue, Yosef Sabo, Joel S Freundlich, David D Ho, Alejandro Chavez
{"title":"A multiplex method for rapidly identifying viral protease inhibitors.","authors":"Seo Jung Hong, Samuel J Resnick, Sho Iketani, Ji Won Cha, Benjamin Alexander Albert, Christopher T Fazekas, Ching-Wen Chang, Hengrui Liu, Shlomi Dagan, Michael R Abagyan, Pavla Fajtová, Bruce Culbertson, Brooklyn Brace, Eswar R Reddem, Farhad Forouhar, J Fraser Glickman, James M Balkovec, Brent R Stockwell, Lawrence Shapiro, Anthony J O'Donoghue, Yosef Sabo, Joel S Freundlich, David D Ho, Alejandro Chavez","doi":"10.1038/s44320-024-00082-1","DOIUrl":"10.1038/s44320-024-00082-1","url":null,"abstract":"<p><p>With current treatments addressing only a fraction of pathogens and new viral threats constantly evolving, there is a critical need to expand our existing therapeutic arsenal. To speed the rate of discovery and better prepare against future threats, we establish a high-throughput platform capable of screening compounds against 40 diverse viral proteases simultaneously. This multiplex approach is enabled by using cellular biosensors of viral protease activity combined with DNA-barcoding technology, as well as several design innovations that increase assay sensitivity and correct for plate-to-plate variation. Among >100,000 compound-target interactions explored within our initial screen, a series of broad-acting inhibitors against coronavirus proteases were uncovered and validated through orthogonal assays. A medicinal chemistry campaign was performed to improve one of the inhibitor's potency while maintaining its broad activity. This work highlights the power of multiplex screening to efficiently explore chemical space at a fraction of the time and costs of previous approaches.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":"21 2","pages":"158-172"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143123003","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}
Ralitsa R Madsen, Alix Le Marois, Oliwia N Mruk, Margaritis Voliotis, Shaozhen Yin, Jahangir Sufi, Xiao Qin, Salome J Zhao, Julia Gorczynska, Daniele Morelli, Lindsay Davidson, Erik Sahai, Viktor I Korolchuk, Christopher J Tape, Bart Vanhaesebroeck
{"title":"Oncogenic PIK3CA corrupts growth factor signaling specificity.","authors":"Ralitsa R Madsen, Alix Le Marois, Oliwia N Mruk, Margaritis Voliotis, Shaozhen Yin, Jahangir Sufi, Xiao Qin, Salome J Zhao, Julia Gorczynska, Daniele Morelli, Lindsay Davidson, Erik Sahai, Viktor I Korolchuk, Christopher J Tape, Bart Vanhaesebroeck","doi":"10.1038/s44320-024-00078-x","DOIUrl":"10.1038/s44320-024-00078-x","url":null,"abstract":"<p><p>Technical limitations have prevented understanding of how growth factor signals are encoded in distinct activity patterns of the phosphoinositide 3-kinase (PI3K)/AKT pathway, and how this is altered by oncogenic pathway mutations. We introduce a kinetic, single-cell framework for precise calculations of PI3K-specific information transfer for different growth factors. This features live-cell imaging of PI3K/AKT activity reporters and multiplexed CyTOF measurements of PI3K/AKT and RAS/ERK signaling markers over time. Using this framework, we found that the PIK3CA<sup>H1047R</sup> oncogene was not a simple, constitutive activator of the pathway as often presented. Dose-dependent expression of PIK3CA<sup>H1047R</sup> in human cervical cancer and induced pluripotent stem cells corrupted the fidelity of growth factor-induced information transfer, with preferential amplification of epidermal growth factor receptor (EGFR) signaling responses compared to insulin-like growth factor 1 (IGF1) and insulin receptor signaling. PIK3CA<sup>H1047R</sup> did not only shift these responses to a higher mean but also enhanced signaling heterogeneity. We conclude that oncogenic PIK3CA<sup>H1047R</sup> corrupts information transfer in a growth factor-dependent manner and suggest new opportunities for tuning of receptor-specific PI3K pathway outputs for therapeutic benefit.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"126-157"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872589","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}
David W Morgens, Leah Gulyas, Xiaowen Mao, Alejandro Rivera-Madera, Annabelle S Souza, Britt A Glaunsinger
{"title":"Enhancers and genome conformation provide complex transcriptional control of a herpesviral gene.","authors":"David W Morgens, Leah Gulyas, Xiaowen Mao, Alejandro Rivera-Madera, Annabelle S Souza, Britt A Glaunsinger","doi":"10.1038/s44320-024-00075-0","DOIUrl":"10.1038/s44320-024-00075-0","url":null,"abstract":"<p><p>Complex transcriptional control is a conserved feature of both eukaryotes and the viruses that infect them. Despite viral genomes being smaller and more gene dense than their hosts, we generally lack a sense of scope for the features governing the transcriptional output of individual viral genes. Even having a seemingly simple expression pattern does not imply that a gene's underlying regulation is straightforward. Here, we illustrate this by combining high-density functional genomics, expression profiling, and viral-specific chromosome conformation capture to define with unprecedented detail the transcriptional regulation of a single gene from Kaposi's sarcoma-associated herpesvirus (KSHV). We used as our model KSHV ORF68 - which has simple, early expression kinetics and is essential for viral genome packaging. We first identified seven cis-regulatory regions involved in ORF68 expression by densely tiling the ~154 kb KSHV genome with dCas9 fused to a transcriptional repressor domain (CRISPRi). A parallel Cas9 nuclease screen indicated that three of these regions act as promoters of genes that regulate ORF68. RNA expression profiling demonstrated that three more of these regions act by either repressing or enhancing other distal viral genes involved in ORF68 transcriptional regulation. Finally, we tracked how the 3D structure of the viral genome changes during its lifecycle, revealing that these enhancing regulatory elements are physically closer to their targets when active, and that disrupting some elements caused large-scale changes to the 3D genome. These data enable us to construct a complete model revealing that the mechanistic diversity of this essential regulatory circuit matches that of human genes.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"30-58"},"PeriodicalIF":8.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11696879/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142676266","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}
Deepak T Patel, Peter J Stogios, Lukasz Jaroszewski, Malene L Urbanus, Mayya Sedova, Cameron Semper, Cathy Le, Abraham Takkouche, Keita Ichii, Julie Innabi, Dhruvin H Patel, Alexander W Ensminger, Adam Godzik, Alexei Savchenko
{"title":"Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors.","authors":"Deepak T Patel, Peter J Stogios, Lukasz Jaroszewski, Malene L Urbanus, Mayya Sedova, Cameron Semper, Cathy Le, Abraham Takkouche, Keita Ichii, Julie Innabi, Dhruvin H Patel, Alexander W Ensminger, Adam Godzik, Alexei Savchenko","doi":"10.1038/s44320-024-00076-z","DOIUrl":"10.1038/s44320-024-00076-z","url":null,"abstract":"<p><p>Legionella pneumophila utilizes the Dot/Icm type IVB secretion system to deliver hundreds of effector proteins inside eukaryotic cells to ensure intracellular replication. Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete. By leveraging advancements in 3D protein structure prediction, we provide a comprehensive structural analysis of 368 L. pneumophila effectors, representing a global atlas of predicted functional domains summarized in a database ( https://pathogens3d.org/legionella-pneumophila ). Our analysis identified 157 types of diverse functional domains in 287 effectors, including 159 effectors with no prior functional annotations. Furthermore, we identified 35 cryptic domains in 30 effector models that have no similarity with experimentally structurally characterized proteins, thus, hinting at novel functionalities. Using this analysis, we demonstrate the activity of thirteen functional domains, including three cryptic domains, predicted in L. pneumophila effectors to cause growth defects in the Saccharomyces cerevisiae model system. This illustrates an emerging strategy of exploring synergies between predictions and targeted experimental approaches in elucidating novel effector activities involved in infection.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"59-89"},"PeriodicalIF":8.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11696984/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142676352","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}
Boris Bogdanow, Max Ruwolt, Julia Ruta, Lars Mühlberg, Cong Wang, Wen-Feng Zeng, Arne Elofsson, Fan Liu
{"title":"Redesigning error control in cross-linking mass spectrometry enables more robust and sensitive protein-protein interaction studies.","authors":"Boris Bogdanow, Max Ruwolt, Julia Ruta, Lars Mühlberg, Cong Wang, Wen-Feng Zeng, Arne Elofsson, Fan Liu","doi":"10.1038/s44320-024-00079-w","DOIUrl":"10.1038/s44320-024-00079-w","url":null,"abstract":"<p><p>Cross-linking mass spectrometry (XL-MS) allows characterizing protein-protein interactions (PPIs) in native biological systems by capturing cross-links between different proteins (inter-links). However, inter-link identification remains challenging, requiring dedicated data filtering schemes and thorough error control. Here, we benchmark existing data filtering schemes combined with error rate estimation strategies utilizing concatenated target-decoy protein sequence databases. These workflows show shortcomings either in sensitivity (many false negatives) or specificity (many false positives). To ameliorate the limited sensitivity without compromising specificity, we develop an alternative target-decoy search strategy using fused target-decoy databases. Furthermore, we devise a different data filtering scheme that takes the inter-link context of the XL-MS dataset into account. Combining both approaches maintains low error rates and minimizes false negatives, as we show by mathematical simulations, analysis of experimental ground-truth data, and application to various biological datasets. In human cells, inter-link identifications increase by 75% and we confirm their structural accuracy through proteome-wide comparisons to AlphaFold2-derived models. Taken together, target-decoy fusion and context-sensitive data filtering deepen and fine-tune XL-MS-based interactomics.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"90-106"},"PeriodicalIF":8.5,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11696718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142801791","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}
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