NPJ Systems Biology and Applications最新文献_第2页

Integrative structural profiling and ligand optimisation across the transthyretin mutational landscape. 跨甲状腺素突变景观的综合结构分析和配体优化。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-09-25 DOI: 10.1038/s41540-025-00582-2

Ugo Lomoio, Valentina Carbonari, Federico Manuel Giorgi, Francesco Ortuso, Pietro Lió, Pierangelo Veltri, Pietro Hiram Guzzi

{"title":"Integrative structural profiling and ligand optimisation across the transthyretin mutational landscape.","authors":"Ugo Lomoio, Valentina Carbonari, Federico Manuel Giorgi, Francesco Ortuso, Pietro Lió, Pierangelo Veltri, Pietro Hiram Guzzi","doi":"10.1038/s41540-025-00582-2","DOIUrl":"10.1038/s41540-025-00582-2","url":null,"abstract":"Transthyretin amyloidosis (ATTR) is a genetically diverse disorder caused by destabilising mutations in the transthyretin (TTR) protein, leading to pathological aggregation. While stabilisers like tafamidis and acoramidis are approved, their efficacy across TTR variants remains unclear. This study presents an in silico pipeline combining AlphaFold3 for structure prediction, ESM2 for sequence embeddings, DiffDock-L and AutoDock Vina for molecular docking, and DiffSBDD for ligand generation. Simulations show that binding affinities of approved ligands vary significantly among TTR variants, with some mutations (e.g., W61L, Y98F) reducing binding despite being distant from the binding site. Embedding-based clustering highlights potential benign mutations and supports scalable variant classification. Additionally, customised ligand optimisation can recover binding affinity in specific cases, though effects are mutation-dependent. These findings emphasise the need for variant-aware therapeutic strategies. This integrative approach offers a foundation for precision drug design in ATTR, enabling the development of personalised stabilisers tailored to individual mutational profiles.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"104"},"PeriodicalIF":3.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12462452/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145150216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging. 机器学习和数据驱动的代谢组学逆建模揭示了活跃衰老的关键过程。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-09-24 DOI: 10.1038/s41540-025-00580-4

Jiahang Li, Martin Brenner, Iro Pierides, Barbara Wessner, Bernhard Franzke, Eva-Maria Strasser, Steffen Waldherr, Karl-Heinz Wagner, Wolfram Weckwerth

{"title":"Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.","authors":"Jiahang Li, Martin Brenner, Iro Pierides, Barbara Wessner, Bernhard Franzke, Eva-Maria Strasser, Steffen Waldherr, Karl-Heinz Wagner, Wolfram Weckwerth","doi":"10.1038/s41540-025-00580-4","DOIUrl":"10.1038/s41540-025-00580-4","url":null,"abstract":"Physical inactivity and low fitness have become global health concerns. Metabolomics, as an integrative approach, may link fitness to molecular changes. In this study, we analyzed blood metabolomes from elderly individuals under different treatments. By defining two fitness groups and their corresponding metabolite profiles, we applied several machine learning classifiers to identify key metabolite biomarkers. Aspartate consistently emerged as a dominant fitness marker. We further defined a body activity index (BAI) and analyzed two cohorts with high and low BAI using COVRECON, a novel method for metabolic network interaction analysis. COVRECON identifies causal molecular dynamics in multiomics data. Aspartate-amino-transferase (AST) was among the dominant processes distinguishing the groups. Routine blood tests confirmed significant differences in AST and ALT. Aspartate is also a known biomarker in dementia, related to physical fitness. In summary, we combine machine learning and COVRECON to identify metabolic biomarkers and molecular dynamics supporting active aging.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"103"},"PeriodicalIF":3.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12460594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging quantitative systems pharmacology modeling for elranatamab regimen optimization in relapsed or refractory multiple myeloma. 利用定量系统药理学模型优化elranatumab治疗复发或难治性多发性骨髓瘤的方案。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-09-01 DOI: 10.1038/s41540-025-00585-z

Kamrine E Poels, Mohamed Elmeliegy, Jennifer Hibma, Diane Wang, Cynthia J Musante, Blerta Shtylla

{"title":"Leveraging quantitative systems pharmacology modeling for elranatamab regimen optimization in relapsed or refractory multiple myeloma.","authors":"Kamrine E Poels, Mohamed Elmeliegy, Jennifer Hibma, Diane Wang, Cynthia J Musante, Blerta Shtylla","doi":"10.1038/s41540-025-00585-z","DOIUrl":"10.1038/s41540-025-00585-z","url":null,"abstract":"Elranatamab, an approved bispecific antibody (BsAb) for relapsed/refractory multiple myeloma, forms an immune synapse between the T-cell CD3 marker and B-cell maturation antigen (BCMA) on myeloma cells. Circulating soluble BCMA (sBCMA) is associated with disease burden and may reduce drug exposure, impacting efficacy. A quantitative systems pharmacology model that captures elranatamab's mechanism of action and disease dynamics was developed and calibrated to clinical datasets. Simulations explored model uncertainty and inter-patient variability with respect to biological, pharmacologic, and tumor-related components to inform clinical dose-response relationships and evaluate the effect of baseline sBCMA levels on dose and regimen. Model simulations supported 76 mg weekly as the optimal regimen, including in patients with high sBCMA. A left shift in the dose-response curve among virtual responders supported maintenance of efficacy with less frequent dosing. This work exemplifies how mechanistic models may support BsAb dose and regimen justification within the framework of model-informed drug development.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"102"},"PeriodicalIF":3.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12402305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144962964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Current state and open problems in universal differential equations for systems biology. 系统生物学通用微分方程的现状及有待解决的问题。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-30 DOI: 10.1038/s41540-025-00550-w

Maren Philipps, Nina Schmid, Jan Hasenauer

引用次数: 0

Utility of the continuous spectrum formed by pathological states in characterizing disease properties. 病理状态形成的连续谱在表征疾病特性方面的效用。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-29 DOI: 10.1038/s41540-025-00579-x

Takashi Fujiwara, Yoshiaki Kariya, Kanata Kobayashi, Soma Matsui, Tappei Takada

{"title":"Utility of the continuous spectrum formed by pathological states in characterizing disease properties.","authors":"Takashi Fujiwara, Yoshiaki Kariya, Kanata Kobayashi, Soma Matsui, Tappei Takada","doi":"10.1038/s41540-025-00579-x","DOIUrl":"https://doi.org/10.1038/s41540-025-00579-x","url":null,"abstract":"Understanding diseases as the result of continuous transitions from a healthy system is more realistic than understanding them as discrete states. Here, we designed the spectrum formation approach (SFA), a machine learning-based method that extracts key features contributing to disease state continuity. We applied the SFA to transcriptomic data from patients with progressive liver disease and neurodegenerative movement disorders to examine its effectiveness in identifying biologically relevant gene sets. The SFA identified transcription factors that potentially regulate liver inflammation and voluntary movement. In neurodegenerative disorders, the SFA also identified genes regulated by ETS-1, with unclear effects on movement. In functional assessment using human iPSC-derived neurons, ETS-1 overexpression disrupted dopamine receptor balance, reduced GABA-producing enzyme levels, and promoted cell death. These findings suggest that the SFA enables the discovery of regulatory factors capable of modifying disease states and provides a framework for the continuity-based interpretation of biological systems.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"100"},"PeriodicalIF":3.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397437/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144963096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging agent-based models and deep reinforcement learning to predict taxis in cell migration. 利用基于智能体的模型和深度强化学习来预测细胞迁移的趋向性。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-26 DOI: 10.1038/s41540-025-00576-0

Daniel Camacho-Gomez, Raffaele Sentiero, Maurizio Ventre, Jose Manuel Garcia-Aznar

{"title":"Leveraging agent-based models and deep reinforcement learning to predict taxis in cell migration.","authors":"Daniel Camacho-Gomez, Raffaele Sentiero, Maurizio Ventre, Jose Manuel Garcia-Aznar","doi":"10.1038/s41540-025-00576-0","DOIUrl":"https://doi.org/10.1038/s41540-025-00576-0","url":null,"abstract":"We present a novel computational framework that combines Agent-Based Modeling (ABM) with Reinforcement Learning (RL) using the Double Deep Q-Network (DDQN) algorithm to determine cellular behavior in response to environmental signals. With this approach, the model captures the transduction of environmental cues into biological responses directly from experimental observations, without explicitly predefining cell behavior. This enables the prediction of dynamic, environment-dependent cell behavior and offers a scalable and flexible alternative to traditional rule-based ABM. To illustrate its potential, we present an application to barotactic cell migration data from microfluidic device experiments, where cells adapt their migration behavior based on pressure gradients, demonstrating the model's ability to generalize across varying geometries and pressure configurations. Thus, this approach introduces a novel direction for modeling how cells sense and transduce environmental cues into biological behaviors.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"99"},"PeriodicalIF":3.5,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12378232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144963010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal dosing of anti-cancer treatment under drug-induced plasticity. 药物诱导可塑性下抗癌治疗的最佳剂量。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-25 DOI: 10.1038/s41540-025-00571-5

Einar Bjarki Gunnarsson, Benedikt Vilji Magnússon, Jasmine Foo

{"title":"Optimal dosing of anti-cancer treatment under drug-induced plasticity.","authors":"Einar Bjarki Gunnarsson, Benedikt Vilji Magnússon, Jasmine Foo","doi":"10.1038/s41540-025-00571-5","DOIUrl":"https://doi.org/10.1038/s41540-025-00571-5","url":null,"abstract":"While cancer has traditionally been considered a genetic disease, mounting evidence indicates an important role for non-genetic (epigenetic) mechanisms. Common anti-cancer drugs have recently been observed to induce the adoption of non-genetic drug-tolerant cell states, thereby accelerating the evolution of drug resistance. This confounds conventional high-dose treatment strategies aimed at maximal tumor reduction, since high doses can simultaneously promote non-genetic resistance. In this work, we study optimal dosing of anti-cancer treatment under drug-induced cell plasticity. We show that the optimal dosing strategy steers the tumor to a fixed equilibrium composition between sensitive and tolerant cells, while precisely balancing the trade-off between cell kill and tolerance induction. The optimal equilibrium strategy ranges from applying a low dose continuously to applying the maximum dose intermittently, depending on the dynamics of tolerance induction. We finally discuss how our approach can be integrated with in vitro data to derive patient-specific treatment insights.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"98"},"PeriodicalIF":3.5,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12375710/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144962979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification of first embryonic division stages of multiple Caenorhabditis species by deep learning. 基于深度学习的多种隐杆线虫第一胚胎分裂阶段的分类。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-23 DOI: 10.1038/s41540-025-00566-2

Dhruv Khatri, Prachi Negi, Chaitanya A Athale

{"title":"Classification of first embryonic division stages of multiple Caenorhabditis species by deep learning.","authors":"Dhruv Khatri, Prachi Negi, Chaitanya A Athale","doi":"10.1038/s41540-025-00566-2","DOIUrl":"https://doi.org/10.1038/s41540-025-00566-2","url":null,"abstract":"The first embryonic division of Caenorhabditis elegans is a model for asymmetric cell division, and identifying the stages of cell division across related species could improve our understanding of the divergence of cellular events and mechanisms. Comparative microscopy of evolutionarily divergent species continues to rely on label-free differential interference contrast (DIC) microscopy due to technical challenges in molecular tagging, with the identification of cell division stages still relying on label-free microscopy. Here, we compare multiple deep convolutional neural networks (CNNs) trained to automate cell stage classification in DIC microscopy movies and interpret the results, with code and classification weights released as OpenSource. The networks are trained to identify if a single frame of a time-series belongs to one of the four morphologically distinct stages: (i) pro-nuclear migration, (ii) centration and rotation, (iii) spindle displacement and (iv) cytokinesis, that had been manually labeled. Three previously described networks, ResNet, VggNet, and EfficientNet, and a customized shallow network, which we refer to as EvoCellNet, achieved 91% or greater accuracy in test data from 23 different nematode species. We find activation vectors of the CNNs of the sparse EvoCellNet correlate with spatial localization of intracellular features of multiple species, such as pro-nuclei, spindle, and spindle-poles. While the pipeline is robust when applied to comparable DIC time-series of C. elegans and C. briggsae embryos, distinct from those on which it was trained and tested, successful classification is limited to images with conserved morphological features. Thus, deep learning networks can be used to generalize the morphological changes across species of nematode embryos, capturing chronology based on low-level intracellular features with biological relevance.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"97"},"PeriodicalIF":3.5,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12375112/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144963289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ordinary differential equation model of cancer-associated fibroblast heterogeneity predicts treatment outcomes. 癌症相关成纤维细胞异质性的常微分方程模型预测治疗结果。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-23 DOI: 10.1038/s41540-025-00578-y

Junho Lee, Eunjung Kim

{"title":"Ordinary differential equation model of cancer-associated fibroblast heterogeneity predicts treatment outcomes.","authors":"Junho Lee, Eunjung Kim","doi":"10.1038/s41540-025-00578-y","DOIUrl":"https://doi.org/10.1038/s41540-025-00578-y","url":null,"abstract":"Cancer-associated fibroblasts (CAFs) are key components of the tumor microenvironment (TME). CAF phenotypes are highly heterogeneous and exert anti- and protumorigenic effects. We present a mathematical model that describes cancer-immune-CAF interactions and exploits the heterogeneity of CAF phenotypes to predict cancer progression and treatment response. By simulating multiple treatment options, including targeted monotherapies alone, two different immunotherapies, and a combination of therapies, we have found that CAF composition can impact treatment outcomes, potentially resulting in comparable effectiveness of single-drug treatments and combinatorial approaches or even the ineffectiveness of multicombination therapies. These findings suggest that CAF composition can be a promising indicator, in some cases guiding the choice towards less invasive therapies without compromising effectiveness. Our model indicates that accounting for CAF characteristics might facilitate the matching of targeted treatments, supporting clinical decision-making.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"96"},"PeriodicalIF":3.5,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12375085/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144963137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying genes underlying parallel evolution of stromal resistance to placental and cancer invasion. 鉴定基质抗胎盘和癌症侵袭平行进化的基因。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-08-22 DOI: 10.1038/s41540-025-00577-z

Yasir Suhail, Wenqiang Du, Junaid Afzal, Günter P Wagner, Kshitiz

{"title":"Identifying genes underlying parallel evolution of stromal resistance to placental and cancer invasion.","authors":"Yasir Suhail, Wenqiang Du, Junaid Afzal, Günter P Wagner, Kshitiz","doi":"10.1038/s41540-025-00577-z","DOIUrl":"https://doi.org/10.1038/s41540-025-00577-z","url":null,"abstract":"Stromal regulation of cancer dissemination is well recognized, however causal genes remain unidentified. We previously demonstrated that epitheliochorial species have acquired stromal resistance to placental invasion, correlating with reduced rate of cancer malignancies, identifying stromal genes correlating with depth of placental invasion called ELI (Evolved Levels of Invasibility) genes. Similarly, decidualization of human endometrial fibroblasts confers resistance to placental invasion. We hypothesized that both trajectories may convergently use similar pathways, providing an opportunity to identify stromal genes regulating epithelial invasion. We created a gene-set ELI-D1 (ELI-Decidual 1), putatively underlying stromal vulnerability to invasion. ELI-D1 were negatively enriched in T1-T2 stage transition in many human cancers, typically preceding dissemination. We also identified candidate transcriptional regulators underlying variation in ELI-D1 genes across eutherians, functionally showing Nr2f6, and JDP2 can regulate stromal resistance to invasion in human fibroblasts. Our comparative approach provides us with a gene-set linked to stromal vulnerability in human cancers.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"95"},"PeriodicalIF":3.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144962966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0