Computational Biology and Chemistry最新文献_第6页

PTTG1 as a common promising target for PCOS, Ovarian Cancer, and Major Depressive Disorder patients PTTG1作为PCOS，卵巢癌和重度抑郁症患者的共同有希望的靶点

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-05 DOI: 10.1016/j.compbiolchem.2025.108673

Kavita Kumari, Aakansha Singh, Anjana Dwivedi

{"title":"PTTG1 as a common promising target for PCOS, Ovarian Cancer, and Major Depressive Disorder patients","authors":"Kavita Kumari, Aakansha Singh, Anjana Dwivedi","doi":"10.1016/j.compbiolchem.2025.108673","DOIUrl":"10.1016/j.compbiolchem.2025.108673","url":null,"abstract":"<div><div>Women are susceptible to hormonal imbalances and endocrine-related disorders such as Polycystic Ovary Syndrome (PCOS), Ovarian Cancer (OC), and Major Depressive Disorder (MDD). This study aims to identify gene-level interconnections among these conditions using omics-based bioinformatic approaches. Publicly available GEO datasets, viz., GSE226146 (PCOS), GSE18520 (OC), and GSE125664 (MDD), were analyzed, which in total resulted in 21,366 differentially expressed genes (DEGs), including 11,174 upregulated and 10,198 downregulated genes. Common genes PTTG1 and PID1 were identified using Venny 2.0. A protein–protein interaction (PPI) network was constructed using STRING, and 10 hub genes (ANAPC5, ANAPC2, PTTG1, FZR1, ANAPC4, CDC20, CDC27, ANAPC10, UBE2C, and BUB1) were identified using CytoHubba based on MCC scoring. Functional enrichment analysis showed significant involvement of these genes in oocyte meiosis, progesterone-mediated oocyte maturation, mitotic regulation, and metaphase-anaphase transition (p < 0.05). PTTG1, identified as both a common and hub gene, was downregulated in PCOS and upregulated in OC and MDD. Drug-gene interaction analysis using DSigDB via Enrichr identified Alvespimycin (for PCOS) and Gefitinib (for OC) as drugs targeting PTTG1. Molecular docking using AutoDock 4.2.6 showed that Alvespimycin and Ephedrone bind PTTG1 with a binding affinity of − 4.59 kcal/mol and − 5.81 kcal/mol, respectively, while Gefitinib showed − 4.92 kcal/mol, slightly less than Troglitazone (-5.3 kcal/mol) for OC. This study highlights PTTG1 as a shared molecular link among PCOS, OC, and MDD, suggesting its potential as a therapeutic target and providing insights into the genetic and physiological overlap of these conditions.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108673"},"PeriodicalIF":3.1,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI modeling of Ag-ZnO milk dynamics in a squarely elevated electromagnetic tunnel with dynamic thermal modulation 动态热调制电磁隧道中Ag-ZnO乳动力学的AI建模

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-04 DOI: 10.1016/j.compbiolchem.2025.108668

Sanatan Das , Poly Karmakar

{"title":"AI modeling of Ag-ZnO milk dynamics in a squarely elevated electromagnetic tunnel with dynamic thermal modulation","authors":"Sanatan Das , Poly Karmakar","doi":"10.1016/j.compbiolchem.2025.108668","DOIUrl":"10.1016/j.compbiolchem.2025.108668","url":null,"abstract":"<div><div>This research proposes an advanced technique to manipulating milk flow and its thermal characteristics through a dynamic electromagnetic pathway, effectively managing the non-linear thermal behavior of milk. This study employs advanced artificial intelligence (AI) to create a sophisticated analytical framework for modeling the complex interactions between milk flow, hybrid nanoparticles (Ag-ZnO), and dynamic thermal conditions in a squarely activated electromagnetic tunnel. The research focuses on optimizing key steps in dairy manufacturing-microbial reduction and texture stabilization by analyzing the behavior of Ag-ZnO/milk under oscillating thermal amplification, incorporating radiant heat and Darcy drag effects. Employing the Laplace Transform (LT) approach, this study explores milk flow dynamics through mathematical and physical analyses, successfully solving the key flow equations. Analytical outcomes are thoroughly evaluated, presenting important metrics like flow profiles, shear stress (SS), and heat transfer rate (RHT) through graphical representations. Notable research indicates that the momentum of milk intensifies with a higher modified Hartmann number but diminishes when broader electrodes are employed. Additionally, thermal buildup in milk correlates with an elevated Casson parameter, which enhances SS, whereas an increased frequency parameter abates RHT. Furthermore, an AI-enhanced strategy employing an artificial neural network (ANN) attains flawless precision, achieving 100 % and 99.266 % accuracy in SS prediction, along with perfect 100 % and near-ideal 99.556 % accuracy for RHT forecasting. This research unlocks groundbreaking potential for the food and pharmaceutical industries, enabling innovative processing techniques while significantly improving product quality and safety standards.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108668"},"PeriodicalIF":3.1,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The relationship between fear of negative evaluation and social anxiety in parents of children with ASD: The chain mediating role of perceived social support and coping styles ASD患儿父母对负面评价恐惧与社交焦虑的关系：感知社会支持与应对方式的连锁中介作用

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-03 DOI: 10.1016/j.compbiolchem.2025.108670

Shuqiao Meng , Kai Qi , Panyi Shen , Shuwen Guo , Wenxia Tong

{"title":"The relationship between fear of negative evaluation and social anxiety in parents of children with ASD: The chain mediating role of perceived social support and coping styles","authors":"Shuqiao Meng , Kai Qi , Panyi Shen , Shuwen Guo , Wenxia Tong","doi":"10.1016/j.compbiolchem.2025.108670","DOIUrl":"10.1016/j.compbiolchem.2025.108670","url":null,"abstract":"<div><div>Parents of children with ASD face significantly greater parenting challenges than those raising typically developing children due to prolonged exposure to their children’s developmental disorders, emotional distress, and atypical behaviors, underscoring the urgency of addressing their mental health concerns. This study examined the relationship between fear of negative evaluation (FNE) and social anxiety in parents of children with ASD, with a focus on the mediating roles of perceived social support and coping styles. A cross-sectional survey was conducted among 585 parents of children with ASD using validated instruments: the Brief Fear of Negative Evaluation Scale (BFNE), the Social Anxiety Scale, the Perceived Social Support Scale, and the Simple Coping Style Questionnaire. Data were analyzed through SPSS 29.0 and AMOS 25.0 for structural equation modeling. Key findings revealed: (1) FNE directly predicted social anxiety, with significant standardized direct effects of 0.179 and 0.159 across tested models (p < 0.001); (2) Perceived social support, positive coping styles, and negative coping styles each partially mediated the FNE–social anxiety relationship, with indirect effects of 0.035 (95 % CI [0.025, 0.066]), 0.096 (95 % CI [0.181, 0.242]), and 0.110 (95 % CI [0.115, 0.126]), respectively; (3) Significant chain mediation pathways emerged through perceived social support → positive coping styles (effect = 0.008, 95 % CI [0.012, 0.016]) and perceived social support → negative coping styles (effect = 0.014, 95 % CI [0.031, 0.033]). These findings elucidate the mechanisms linking FNE to social anxiety in this population and provide theoretical foundations for targeted interventions to mitigate parental distress.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108670"},"PeriodicalIF":3.1,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal control strategies for reducing the interrelated issues of food insecurity and disease dynamics: A mathematical modelling approach using Nigeria as a case study 减少粮食不安全和疾病动态相关问题的最佳控制战略：以尼日利亚为个案研究的数学建模方法

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-02 DOI: 10.1016/j.compbiolchem.2025.108664

Obiora C. Collins , Kevin J. Duffy

引用次数: 0

Identifying meaningful drug response biomarkers from public pharmacogenomic datasets with biologically informed interpretable neural networks 利用生物信息可解释的神经网络从公共药物基因组学数据集中识别有意义的药物反应生物标志物

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-02 DOI: 10.1016/j.compbiolchem.2025.108669

Maoxin Ran , Shao-Lin Zhang , Kin Yip Tam

{"title":"Identifying meaningful drug response biomarkers from public pharmacogenomic datasets with biologically informed interpretable neural networks","authors":"Maoxin Ran , Shao-Lin Zhang , Kin Yip Tam","doi":"10.1016/j.compbiolchem.2025.108669","DOIUrl":"10.1016/j.compbiolchem.2025.108669","url":null,"abstract":"<div><div>With the advancements of next-generation sequencing, publicly available pharmacogenomic datasets from cancer cell lines provide a handle for developing predictive models of drug responses and identifying associated biomarkers. However, many currently available predictive models are often just used as black boxes, lacking meaningful biological interpretations. In this study, we made use of open-source drug response data from cancer cell lines, in conjunction with KEGG pathway information, to develop sparse neural networks, K-net, enabling the prediction of drug response in EGFR signaling pathways and the identification of key biomarkers. To explore the rationality of identified biomarkers, we analyzed distribution patterns between drug-resistant and sensitive cell lines and performed simulated perturbation analysis on drug response. We compared K-net with commonly used interpretable algorithms in biomarker identification, such as lasso logistic regression and random forest classifiers. Our results suggested that K-net outperformed other algorithms in identifying key biomarkers linked to osimertinib response, such as KRAS and TP53 mutations, as well as AKT3 overexpression, accurately revealing their associations with osimertinib resistance. Moreover, K-net revealed subtype-specific top biomarkers for osimertinib resistance, with lung adenocarcinoma (LUAD) showing a predisposition to KRAS mutations and small cell lung cancer (SCLC) exhibiting AKT3 overexpression. Our study revealed that K-net was able to precisely identify critical biomarkers linked to drug responses, highlighting the potential to facilitate optimization of cancer treatment strategies.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108669"},"PeriodicalIF":3.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multilocus genetic and functional profiling of Indian-origin Lentinula edodes strains: Implications for cultivation and nutraceutical breeding 印度香菇菌株的多位点遗传和功能分析：对栽培和营养育种的影响

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-02 DOI: 10.1016/j.compbiolchem.2025.108667

Sujata Makkar , Ajay Singh , Sudheer Kumar Annepu , Kiran Nehra

{"title":"Multilocus genetic and functional profiling of Indian-origin Lentinula edodes strains: Implications for cultivation and nutraceutical breeding","authors":"Sujata Makkar , Ajay Singh , Sudheer Kumar Annepu , Kiran Nehra","doi":"10.1016/j.compbiolchem.2025.108667","DOIUrl":"10.1016/j.compbiolchem.2025.108667","url":null,"abstract":"<div><div><em>Lentinula edodes</em> (shiitake mushroom) is a widely cultivated edible and medicinal fungus, valued for its bioactive compounds. While East Asian strains have been well studied, Indian populations remain under-characterized. This study explores the genetic and functional diversity of five Indian-origin <em>L. edodes</em> strains (DMRO-34, DMRO-35, DMRO-356, DMRO-388s, and DMRO-623) using multilocus sequence analysis targeting ITS, LSU, TEF1-α, and β-tubulin regions (660–1200 bp). Phylogenetic analyses (neighbor-joining, maximum likelihood, and Bayesian inference) revealed three well-supported clusters (bootstrap > 90 %; posterior probability > 0.95). AMOVA (p < 0.01) and diversity indices confirmed significant genetic differentiation. DMRO-356 and DMRO-388s showed close genetic relatedness and phenotypic consistency, while DMRO-623 was genetically distinct. Nonsynonymous mutations were identified in genes linked to stress response, metabolism, and β-glucan biosynthesis. Transcriptomic profiling showed higher expression of β-glucan synthesis genes (<em>FKS1</em>, <em>GLS2</em>) in DMRO-356 and DMRO-388s, indicating potential for nutraceutical use. DMRO-623 exhibited upregulation of stress-responsive genes (<em>SOD</em>, <em>HSP70</em>), suggesting adaptation to environmental stress and suitability for resilient cultivation. Compared to traditional markers (RAPD, SSR), the multilocus approach offered improved resolution for distinguishing closely related strains. Strong correlations (r = 0.80–0.88) between genetic variation and key traits (β-glucan content, antioxidant activity, yield) emphasize the functional significance of the observed diversity. This first multilocus-based study of Indian-origin <em>L. edodes</em> strains provides a genomic framework for marker-assisted breeding, trait optimization, and conservation, supporting their commercial and ecological value in diverse environments.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108667"},"PeriodicalIF":3.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145018778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiview-cooperated graph neural network enables novel multi-omics cancer subtype classification 多视图协同图神经网络实现新型多组学癌症亚型分类

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-09-01 DOI: 10.1016/j.compbiolchem.2025.108665

Min Li , Ming Jin , Mingzhu Lou , Shaobo Deng , Lei Wang , Hua Rao

{"title":"Multiview-cooperated graph neural network enables novel multi-omics cancer subtype classification","authors":"Min Li , Ming Jin , Mingzhu Lou , Shaobo Deng , Lei Wang , Hua Rao","doi":"10.1016/j.compbiolchem.2025.108665","DOIUrl":"10.1016/j.compbiolchem.2025.108665","url":null,"abstract":"<div><div>Cancer presents a significant challenge in the field of public health due to its high incidence, mortality rate, and inherent heterogeneity. Integrating multi-omics biological data offers a comprehensive and intricate understanding of biological processes, disease mechanisms, and cancer subtyping, rendering it an influential tool for scientific research. Nevertheless, current approaches to integrating multi-omics data often fail to consider the scale of data in feature information and overlook the analysis of the individual and shared feature expressions in multi-omics data. The proposed study introduces a Multiview-Cooperated graph neural network (MCgnn), an end-to-end cancer subtype classifier that effectively integrates and analyzes complex multi-omics data. Firstly, MCgnn innovatively constructs a similarity network using Mahalanobis distance and density methods. Then, by employing stacked graph convolution layers, MCgnn effectively captures potential local structural features. Subsequently, MCgnn extracts and fuses complementary information from different omics data through the attention mechanism among views to achieve effective integration of multiple views and attain higher classification performance. Finally, MCgnn performs multi-task learning across omics data using a cross-omics tensor to seamlessly integrate the feature learning component with the classification component. Experiments on four publicly available The Cancer Genome Atlas (TCGA) datasets were conducted to demonstrate that MCgnn outperforms most comparison classification algorithms in effectively addressing the cancer subtype classification problem and exhibits remarkable robustness and generalization capabilities. Additionally, MCgnn was employed to identify pivotal biomarkers in cancer, providing a valuable reference for precision medicine.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108665"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structure-based drug design; Computational strategies in drug discovery; Antihypertensive agents; Antiviral drugs; Molecular docking; QSAR; Pharmacological insights 结构药物设计；药物发现中的计算策略；降压药;抗病毒药物;分子对接;构象;药理的见解

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-08-29 DOI: 10.1016/j.compbiolchem.2025.108663

Asmaa M. Fahim

{"title":"Structure-based drug design; Computational strategies in drug discovery; Antihypertensive agents; Antiviral drugs; Molecular docking; QSAR; Pharmacological insights","authors":"Asmaa M. Fahim","doi":"10.1016/j.compbiolchem.2025.108663","DOIUrl":"10.1016/j.compbiolchem.2025.108663","url":null,"abstract":"<div><div>This review meticulously examines the development, design, and pharmacological assessment of both well known antiviral and antihypertensive medications all time employing new chemical techniques and structure-based drug design to design and synthesize vital therapeutic entities such as aliskiren (renin inhibitor), captopril (a2-ACE-Inhibitor), dorzolamide (inhibitor of carbonic anhydrase) the review demonstrates initial steps regarding the significance of stereoselective synthesis, metal chelating pharmacophores, and rational molecular properties. More importantly, protease inhibitors (i.e., saquinavir, ritonavir, indinavir, amprenavir, etc.) and more contemporary agents (i.e., oseltamivir, nirmatrelvir/ritonavir (Paxlovid), etc.) were identified in the review and form a basis of advancement in antiviral therapy. Using the above-mentioned computational applications (i.e., molecular dockings, structure–activity relationships (SAR)), quantitative structure-activity relationships (QSAR modeling), and ADMET profile information, selectivity, safety, and therapeutic reliability of compounds toward antiviral activity and antihypertensive activity have improved further as outcomes of drug discovery research. Through the combinatorial application of computational drug design and experimental chemistry, researchers have significantly optimized the drug discovery process, minimized off-target effects, and expedited the pathway to develop therapeutically useful medications. In conclusion, this review highlights the transformative power of interdisciplinary approaches, including structure-based design, computational modeling, and the emerging approaches of drug repurposing and virtual screening. This hybrid approach provides a greater opportunity to improve drug therapy for cardiovascular disease and viral infections, and represents the rewards of collaboration.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108663"},"PeriodicalIF":3.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Molecular docking and dynamics simulations of 4-heteroarylidenamino-4,5-dihydro-1H-1,2,4-triazol-5-one derivatives as potential anticancer agents 潜在抗癌药物4-杂芳基氨基-4,5-二氢- 1h -1,2,4-三唑-5-酮衍生物的分子对接和动力学模拟

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-08-29 DOI: 10.1016/j.compbiolchem.2025.108657

Jose Siguenza , Haci Baykara

{"title":"Molecular docking and dynamics simulations of 4-heteroarylidenamino-4,5-dihydro-1H-1,2,4-triazol-5-one derivatives as potential anticancer agents","authors":"Jose Siguenza , Haci Baykara","doi":"10.1016/j.compbiolchem.2025.108657","DOIUrl":"10.1016/j.compbiolchem.2025.108657","url":null,"abstract":"<div><div>The search for anticancer therapies remains imperative, as many existing treatments are hindered by drug resistance, limited efficacy, and undesirable side effects. This study explores the anticancer potential of four 4-heteroarylidenamino-4,5-dihydro-1H-1,2,4-triazol-5-one derivatives using molecular docking and molecular dynamics simulations. These compounds were evaluated against crucial cancer-related proteins, including kinases, histone demethylases, and metabolic regulators. Binding affinity analysis revealed that some derivatives exhibited comparable or superior docking scores to commercial inhibitors such as Imatinib. Compound 1d showed high binding affinities, −7.882 kcal/mol, −9.107 kcal/mol, and −8.474 kcal/mol, for human histone deacetylase 6 catalytic domain 2, A2A adenosine receptor, and human tyrosinase-related protein one mutant (TYRP1), respectively, suggesting strong interactions with key cancer targets. Molecular dynamics simulations confirmed the stability of ligand-protein complexes, with root mean square deviation values below 2.5 Å, indicating minimal conformational fluctuations. Additionally, root mean square fluctuation values ranged from 0.8 to 1.5 Å, supporting stable binding interactions, and the radius of gyration values between 20.2 and 22.5 Å highlighted the compact structural integrity of the complexes. Among the tested ligands, compound 1d demonstrated exceptional binding affinity and stability across multiple targets, particularly the A2A adenosine receptor and TYRP1, which are highly related to epigenetic regulation and cancer progression. These findings suggest that triazole derivatives could serve as promising anticancer agents, warranting further experimental validation to assess their therapeutic potential.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108657"},"PeriodicalIF":3.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144916594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sequence- and structure-based bioinformatic screening for potential Theileria parva transport-related proteins 基于序列和结构的潜在细小芽孢杆菌转运相关蛋白的生物信息学筛选

IF 3.1 4区生物学

Computational Biology and Chemistry Pub Date : 2025-08-29 DOI: 10.1016/j.compbiolchem.2025.108653

Nikolaos Kotsovolos , Leonhard Schnittger , Kgomotso Sibeko-Matjila

{"title":"Sequence- and structure-based bioinformatic screening for potential Theileria parva transport-related proteins","authors":"Nikolaos Kotsovolos , Leonhard Schnittger , Kgomotso Sibeko-Matjila","doi":"10.1016/j.compbiolchem.2025.108653","DOIUrl":"10.1016/j.compbiolchem.2025.108653","url":null,"abstract":"<div><div>As an obligate intracellular parasite, <em>Theileria parva</em> is strictly dependent on its host for nutrient acquisition. Transport proteins are expected to play a crucial role in the influx of essential nutrients to sustain the parasite’s rapid growth. Unfortunately, the <em>T. parva</em> transportome is still not comprehensively elucidated, and plagued by the presence of uncharacterized proteins. In this study, we employed a combination of approaches including sequence orthology and structural similarity to identify 188 proteins predicted to be involved in transport-related processes. Among these, 24 were uncharacterized proteins, and 17 of them could be assigned a tentative annotation. Furthermore, the localization of these 188 proteins was investigated, resulting in their assignment to seven cellular compartments. Screening of the proteomes of other <em>Theileria</em> species, <em>T. annulata</em>, <em>T. orientalis</em>, and <em>T. equi</em> revealed that all 188 proteins were present in both transforming and non-transforming <em>Theileria</em> parasites. Among the 188 potential transport-related proteins, 45 were associated with transmembrane transport and most of them (87 %) are conserved across phylum Apicomplexa.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"120 ","pages":"Article 108653"},"PeriodicalIF":3.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0