PLoS Computational Biology最新文献

{"title":"Awake alpha bursting emerges as the dynamic working state in a lateral geniculate thalamocortical cell model.","authors":"Kees McGahan, Michelle McCarthy, Nancy Kopell","doi":"10.1371/journal.pcbi.1014654","DOIUrl":"10.1371/journal.pcbi.1014654","url":null,"abstract":"<p><p>The awake thalamus is known to be able to filter primary sensory input with and without external modulation. Through the construction and analysis of a novel computational model of a lateral geniculate thalamocortical neuron, we demonstrate how the processing of sensory retinal input is influenced by the underlying thalamic dynamic state. Our model, using only currents verified against expression data from publicly available datasets, is the first to produce five experimentally established distinct dynamic firing regimes. We demonstrate that the thalamocortical cell transitions between these dynamic states in response to glutamatergic signals from the cortex or cholinergic arousal signals coming from the brainstem. We focus on signal processing in the model dynamic states associated with the awake thalamic alpha rhythm where we find that the ability of retinal inputs to generate thalamic spikes is a balance between the timing of retinal spikes, the excitability break imposed by the M-current, and the decay time of the L-type calcium current. Finally, we explore how these two currents help the thalamus process extra-retinal rhythmic inputs, showing the model produces entrainment to slower inhibitory and excitatory rhythms, as well as detailing the importance of nesting faster frequency rhythms within slow cycles for successful thalamic transmission. Our results suggest that the awake alpha rhythm is indirectly causal by acting as a marker for the interaction of these two currents. This biophysically-constrained lateral geniculate thalamocortical cell model generates predictions regarding rhythmic dynamics under different arousal states, thalamic control of retinogeniculate transmission, and the possible impacts neurological disorders, like schizophrenia, have on thalamic processing. Variations of this model could be used to explore the functions of higher order thalamic nuclei, thereby extending its use to investigating more complex cognitive processes.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014654"},"PeriodicalIF":3.6,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13649143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149138028","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}

{"title":"DyME: An MD-based engine exploiting HTP mutagenesis for protein engineering and recognition mimicry.","authors":"Pedro M Guillem-Gloria, Gloria Ruiz-Gómez, M Teresa Pisabarro","doi":"10.1371/journal.pcbi.1014221","DOIUrl":"10.1371/journal.pcbi.1014221","url":null,"abstract":"<p><p>Protein recognition mimicry (PRM) is of great interest in the field of molecular bioengineering and rational design, with mutagenesis frequently employed to analyze the effects of altering amino acids involved in molecular recognition. The conformational and energetic effects of such alterations can be investigated in detail with the help of molecular dynamics (MD) methodologies. While existing MD-based computational tools can be used to explore a particular set of mutations at a time, suitable for small-scale studies, high-throughput (HTP) exploration of protein recognition for engineering purposes would greatly benefit from an integrative platform that streamlines preparation, mutagenesis, simulation and post-processing of up to several thousand molecular systems, along with robust tools for comprehensive and straightforward comparative analysis. DyME (Dynamic Mutagenesis Engine) is a distributed platform that enables systematic investigations of protein recognition mimicry by combining HTP mutagenesis, solvated MD simulations and a Toolbox for comparative analysis (TCA), including interfacial water-site mapping. DyME uses 3D structural information of any protein-protein or protein-DNA complex as input. Its automated MD-based mutagenesis engine facilitates systematic investigation of how site-specific alterations affect recognition, enabling the organization of single, double and triple modifications into combinatorial libraries for comprehensive comparative analysis. In DyME, relevant MD trajectory-derived data is scavenged and stored into a central database, providing aggregation capabilities that ease multi-feature analysis across an extensive collection of simulations. An interactive web-GUI and specialized widgets simplify preparation and efficient molecular and numerical comparative exploration. DyME's capabilities are evaluated using available experimental data. Its source code is available at https://github.com/pisabarro-group/DYME.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014221"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128629","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}

{"title":"A physiologically constrained calibration framework for cardiovascular models applied to a paediatric synthetic sepsis population.","authors":"Manuel T Cabeleira, Samiran Ray, Nicholas C Ovenden, Vanessa Díaz-Zuccarini","doi":"10.1371/journal.pcbi.1014847","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014847","url":null,"abstract":"<p><p>Calibration of mechanistic cardiovascular models is a central barrier to their use in population analysis and patient-specific simulation, particularly in settings where key physiological variables are unobservable and multiple parameter combinations can reproduce the same haemodynamic targets. In this work, we present Embedded Feedback Controller (EFC), a calibration framework for ODE-based lumped-parameter cardiovascular models in which selected physiological parameters are promoted to dynamic states and driven toward prescribed targets through embedded controller equations. By exploiting the qualitative structure of the governing equations, EFC enforces physiologically consistent parameter-variable relationships and converges to the single solution admitted by an over-determined set of targets, reproducibly and independently of the initial conditions, at a cost that scales efficiently with model complexity. The framework is demonstrated in silico, using a mechanistic cardiovascular model to generate virtual paediatric populations spanning normal physiology and two septic shock phenotypes (warm and cold shock) from literature-derived target ranges, achieving <1% residual error across pressures, flows, and compartmental volumes. The resulting parameter distributions are consistent, by construction with theoretical haemodynamic adaptations in paediatric sepsis, including alterations in vascular resistance, compliance, cardiac elastance, and effective blood volume. Importantly, persistent calibration residuals arise when target combinations are structurally incompatible with the model and the parameter carrying the residual is held at a bound, providing an explicit and interpretable diagnostic of feasibility limits. These results establish EFC as a general, scalable calibration strategy for mechanistic cardiovascular models and a practical foundation for virtual population generation and future patient-specific digital twin applications in critical care.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014847"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A joint mixture Tobit method with latent microbial abundance improves detection of microbiome-disease associations in zero-inflated data.","authors":"Junrong Deng, Dong Chen, Siyuan Shen, Yuyang Zhou, Hanyu Cui, Yu Qiu, Qiming Li, Yue-Qing Hu","doi":"10.1371/journal.pcbi.1014844","DOIUrl":"10.1371/journal.pcbi.1014844","url":null,"abstract":"<p><p>Zero inflation remains a major challenge in microbiome differential abundance analysis, often resulting in inflated type I error rates or reduced statistical power. Although numerous methods have been proposed to address excess zeros, many existing approaches do not explicitly distinguish between distinct zero-generating mechanisms, and censoring-based modeling perspectives remain relatively underexplored in microbiome data analysis. To advance methodological development in this area, we introduce a novel censoring-based modeling perspective for microbiome differential abundance analysis. Specifically, we develop a joint mixture Tobit (joint mTobit) method for zero-inflated microbiome data. Building on a mixture Tobit formulation, the model incorporates a point-mass component to represent structural zeros, while modeling latent microbial abundance via a Tobit regression component. The proposed framework jointly links disease status, latent true microbial abundance, and relevant covariates within a unified probabilistic model, allowing appropriate adjustment for confounding factors and facilitating more reliable statistical inference. By explicitly modeling the latent abundance underlying observed counts, the joint mTobit method improves estimation stability and enhances detection power under zero inflation. Extensive simulation studies demonstrate that the joint mTobit method achieves effective type I error control while maintaining high statistical power and stable coefficient estimation across a wide range of settings. Application to a real-world colorectal cancer and adenoma microbiome dataset further illustrates its ability to identify biologically meaningful differentially abundant taxa. Overall, this work develops a joint mTobit modeling framework for zero-inflated microbiome data, enabling inference on latent microbial abundance and providing a censoring-based statistical framework for investigating disease-microbiome associations in differential abundance analysis.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014844"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128554","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}

{"title":"Ten simple rules for preparing and delivering effective funding pitches in competitive grant applications.","authors":"Andy Göbel, Tilman D Rachner","doi":"10.1371/journal.pcbi.1014840","DOIUrl":"10.1371/journal.pcbi.1014840","url":null,"abstract":"<p><p>In grant applications, oral presentations can be an integral part of the evaluation process. Funding pitches are a specific form of pitch presentations delivered during competitive review procedures to complement a written proposal. Their goal is to convince reviewers of both your project's strength and excellence as well as your suitability as a researcher. This paper offers ten simple rules on how to prepare and deliver effective funding pitches, with a particular focus on content selection, clear structuring, and convincing scientific argumentation. We also highlight the importance of practice and feedback and share practical strategies on how to handle questions and critical discussion professionally.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014840"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128604","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}

{"title":"Omics data discovery agents: Agent-supported retrieval, reanalysis, and synthesis of published omics data.","authors":"Alexandre Hutton, Jesse G Meyer","doi":"10.1371/journal.pcbi.1014822","DOIUrl":"10.1371/journal.pcbi.1014822","url":null,"abstract":"<p><p>The biomedical literature contains a vast collection of omics studies, yet most published data remain functionally inaccessible for computational reuse. When raw data are deposited in public repositories, essential information for reproducing reported results is dispersed across main text, supplementary files, and code repositories, and in the rarer cases where intermediate data (e.g., protein abundance files) are shared, their location is irregular. Here we present an agentic framework for the agent-supported retrieval, reanalysis, and synthesis of published omics data. The system employs large language model (LLM) agents with access to tools for fetching omics studies, extracting article metadata, identifying and downloading published data, executing containerized quantification pipelines, and synthesizing results across studies. Applied at corpus scale, the pipeline catalogued dataset references across thousands of PubMed Central articles; we report these as descriptive system outputs rather than as a validated measure of extraction accuracy. Using model context protocol (MCP) servers to expose containerized analysis tools, the agents retrieved and re-quantified data in five end-to-end reanalyses spanning data-dependent and data-independent proteomics and bulk RNA-seq. All five reanalyses completed, each with documented human guidance and workflow accommodations, and reproduced the authors' deposited abundances with high per-sample correlation (0.85-0.997) and strongly concordant differentially expressed features (fold-change Spearman 0.88-0.91), with no direction reversals among features called differentially expressed in both analyses; residual differences in significant-feature lists were attributable to threshold placement, tool-version, and preprocessing differences rather than to the underlying quantities. We further demonstrate that agents can identify semantically similar studies, judge data compatibility, and synthesize findings across studies, including a random-effects meta-analysis that recovered consistent protein regulation in liver fibrosis. Rather than a validated benchmark of literature-wide performance, this work is a feasibility demonstration together with an auditable, reusable toolset, establishing a foundation for prospective evaluation of automated omics-data reuse.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014822"},"PeriodicalIF":3.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652336/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149114136","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}

{"title":"HiFIseek: Gene-specific enrichment of high-impact mutations in associated genomic regions.","authors":"Rafael Riudavets Puig, Denise G O'Mahony, Ina Skaara Brorson, Ksenia Sokolova, Vessela N Kristensen, Anthony Mathelier","doi":"10.1371/journal.pcbi.1014842","DOIUrl":"10.1371/journal.pcbi.1014842","url":null,"abstract":"<p><p>Transcription is regulated through the sequence-specific binding of transcription factors (TFs) to cis-regulatory regions (CRRs); DNA variants in CRRs can disrupt TF-DNA interactions and gene regulatory networks through a cascading effect. Despite a few cases of reported recurrent cis-regulatory variants (CRVs), another approach for detecting non-coding functional events relies on combining gene-CRR associations capturing the regulatory elements controlling gene transcription, and functional impact (FI) scores quantifying the deleterious effect of variants. While many methods exist for each, how much they agree and how strongly the choice of CRR-FI score combination impacts the prediction of cis-regulatory altered genes has not been systematically assessed. Here, we demonstrate that gene-CRR associations and FI scoring methods exhibit little consensus, highlighting the impact of the choice of a specific CRR-FI score combination in a given analysis. These observations point to the need for a systematic approach to evaluate several gene-CRR and FI scoring methods in a unified framework. To address this gap, we developed HiFIseek, a Snakemake pipeline of two enrichment detection methods exploring the enrichment of high FI variants in CRRs associated with a gene using all region-score combinations. We applied HiFIseek to detect genes exhibiting high functional impact CRVs in eight cancer cohorts and a set of breast cancer risk-associated single-nucleotide polymorphisms (SNPs). We demonstrate that cancer driver genes exhibit a higher frequency of FI CRVs compared to non-cancer genes. In the cancer cohorts, HiFIseek detected genes pointing to cancer-related pathways with enrichment for high FI CRVs despite a small degree of agreement across CRR-FI score combinations. In the SNP cohort, HiFIseek found again small consensus across CRR-score combinations, one of which returned 18 known cancer-related genes, including BRCA1, showing an enrichment of high-impact CRVs.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014842"},"PeriodicalIF":3.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149114210","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}

{"title":"CardamomOT: A mechanistic optimal transport-based framework for gene regulatory network inference, trajectory reconstruction and generative modeling.","authors":"Yann Maugé, Elias Ventre","doi":"10.1371/journal.pcbi.1014838","DOIUrl":"10.1371/journal.pcbi.1014838","url":null,"abstract":"<p><p>A key challenge in inferring gene regulatory networks (GRNs) governing cellular processes such as differentiation and reprogramming from experimental data lies in the impossibility of directly measuring protein dynamics at the single-cell level, which prevents establishing causal relationships between regulator activity and target responses. In earlier work, we introduced CARDAMOM, an algorithm that uses temporal snapshots of scRNA-seq data to calibrate a GRN-driven mechanistic model of gene expression. However, this method had several limitations: it could only rely on the relative ordering of time points rather than their exact labels, imposed restrictive quasi-stationary assumptions on protein dynamics, and depended on multiple hyperparameters. Here, we present CardamomOT, a new method based on the same mechanistic model that jointly reconstructs the GRN and unobserved protein trajectories from the data within a mechanistic optimal transport framework. By incorporating exact time labels and priors on protein kinetic rates from the literature, and substantially reducing the number of required hyperparameters, our approach addresses these limitations and substantially improves the accuracy and robustness of GRN calibration. We validate our framework on both in silico and experimental datasets, demonstrating computational scalability and consistently improved performance over state-of-the-art methods in both GRN and trajectory reconstruction on simulated datasets, and, on experimental datasets, reconstruction of cellular trajectories, velocity fields and latent protein levels that are mutually consistent, together with GRN structures consistent with known biology. We also show that these improvements make the calibrated mechanistic model suitable to be used as a generative model to generate testable predictions of cellular responses to unseen perturbations. To our knowledge, this is among the first methods to explicitly integrate mechanistic GRN inference, trajectory reconstruction, and simulation of realistic datasets into a unified framework for scRNA-seq time series analysis.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014838"},"PeriodicalIF":3.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13686291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149114045","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}

{"title":"Mobility hinders malaria elimination goals in the Brazilian Amazon.","authors":"Nicholas J Arisco, Pablo S Fontoura, Cassio Peterka, Marcia C Castro","doi":"10.1371/journal.pcbi.1014843","DOIUrl":"10.1371/journal.pcbi.1014843","url":null,"abstract":"<p><strong>Introduction: </strong>Human mobility across the Brazilian Amazon-shaped by frontier development, land-use change, mining activity, and climatic shocks-remains a major barrier to malaria elimination. Brazil aims to eliminate Plasmodium falciparum (Pf) by 2030 and Plasmodium vivax (Pv) by 2035, yet malaria incidence has plateaued since 2020. We quantify parasite-specific mobility and assess how importations drive malaria reintroduction and reestablishment in areas approaching elimination.</p><p><strong>Methods: </strong>We analyzed 5,521,411 de-identified malaria cases from Sivep-Malaria (2003-2023) across 808 municipalities in the nine-state Brazilian Amazon. We (i) used multivariable monthly sequence analysis to classify \"Municipal Malaria Importation Trajectories\" (MMITs) using local/imported composition, incidence per 1,000, and source/sink network typologies; (ii) characterized mobility networks by parasite species and locality type (rural, urban, settlement, indigenous, mining); and (iii) developed a parasite-specific rule-based classification procedure to identify reintroduction, and defined reestablishment as sustained local transmission.</p><p><strong>Results: </strong>Sequence analysis produced five MMIT clusters, spanning municipalities nearing elimination to areas with sustained high local transmission and distinct profiles of declining transmission with intense vs. moderate importation. Overall, 959,281 cases (17.38%) were imported. Cases were predominantly Pv (81.68%), with Pf comprising 17.15%; Pf was more common among imported than locally acquired infections. Mobility patterns shifted after mid-2020: by 2023, > 50% of exported cases originated in mining localities despite ~0.2% land coverage, with Pf importation increasingly concentrated in municipalities overlapping the Yanomami Indigenous Land. From 2006-2023, we identified 63 Pf and 221 Pv reintroduced locally acquired cases following ≥3 years of zero local transmission, leading to reestablishment in 6 and 23 municipalities, respectively, and generating 864 subsequent Pf and 6,524 subsequent Pv cases. Post-reintroduction transmission persisted for long periods (mean 762 days for Pf; 815 days for Pv).</p><p><strong>Conclusion: </strong>Malaria elimination in Brazil is increasingly hindered by parasite-specific mobility, especially linked to mining-indigenous confluences, and by repeated reintroduction in receptive municipalities nearing elimination (notably along the arc of deforestation). Mobility-informed surveillance and targeted reactive strategies are essential to achieve and sustain Brazil's malaria elimination goals.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014843"},"PeriodicalIF":3.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149114141","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}

{"title":"Repurposing ritonavir to induce proteasomal degradation of IE1 for inhibition of human cytomegalovirus replication.","authors":"Wanfeng Liu, Yu Shi, Xudong Guo, Chenyu Lou, Zhangyi Xie, Yitian Shen, Liang Zhang, Sunzhong Mao, Xiangyang Xue, Shiyu Feng","doi":"10.1371/journal.pcbi.1014867","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014867","url":null,"abstract":"<p><p>Human cytomegalovirus (HCMV) is a major pathogen affecting immunocompromised individuals. Current antiviral drugs target the mid-to-late stages of viral replication but are limited by toxicity and drug resistance. The IE1 protein serves as a key early regulator of HCMV replication; however, it has long been considered undruggable due to the lack of conventional drug-binding sites. In this study, by integrating molecular docking-based virtual screening with in-vitro surface plasmon resonance (SPR) validation, we discovered for the first time that the HIV protease inhibitor ritonavir may bind to the IE1 protein. Further experiments demonstrated that ritonavir significantly reduces IE1 protein levels in a time- and dose-dependent manner without affecting its mRNA expression. Mechanistic investigations revealed that ritonavir promotes selective degradation of IE1 through activation of the ubiquitin-proteasome pathway. Functional assays confirmed that ritonavir effectively inhibits HCMV replication, markedly reducing viral DNA loads and the production of infectious viral particles. Notably, ritonavir exhibited synergistic antiviral effects when combined with the first-line drug ganciclovir (GCV). In summary, this study successfully repurposes the approved drug ritonavir as a regulator of IE1 protein expression, demonstrating not only its anti-HCMV activity and synergistic effects with GCV but also providing a new therapeutic strategy for HCMV infection.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014867"},"PeriodicalIF":3.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149114147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}