Bioinformatics and Biology Insights最新文献

Repurposing of Anti-Infectives for the Management of Onchocerciasis Using Machine Learning and Protein Docking Studies. 利用机器学习和蛋白质对接研究重新利用抗感染药物治疗盘尾丝虫病。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-09-04 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251368252

Cyril Tetteh, Andy Andoh Mensah, Bernice Ampomah, Mahmood B Oppong, Michael Lartey, Paul Owusu Donkor, Kwabena Fm Opuni, Lawrence A Adutwum

{"title":"Repurposing of Anti-Infectives for the Management of Onchocerciasis Using Machine Learning and Protein Docking Studies.","authors":"Cyril Tetteh, Andy Andoh Mensah, Bernice Ampomah, Mahmood B Oppong, Michael Lartey, Paul Owusu Donkor, Kwabena Fm Opuni, Lawrence A Adutwum","doi":"10.1177/11779322251368252","DOIUrl":"10.1177/11779322251368252","url":null,"abstract":"There is a need to improve the discovery of new drugs for neglected tropical diseases (NTDs), as the lack of financial incentives has slowed their development. Currently, ivermectin and moxidectin are used in the management of onchocerciasis. We present a proof-of-concept study based on computational methods to find anti-infectives that can be repurposed or serve as lead compounds for onchocerciasis. A combination of exploratory data analysis, machine learning (ML), and molecular docking studies was used to evaluate 58 anti-infective agents. Out of the 58 test drugs, 14 were predicted by at least 5 ML models to be potentially useful in managing onchocerciasis. Molecular docking studies with the 14 predicted drugs using glutamate-gated chloride channel, a known target of ivermectin, an onchocerciasis drug, yielded good results. Cridanimod, diminazene, and vandetanib were the top 3 agents showing the highest binding affinities of -7.8, -7.2, and 7.1 kcal/mol, respectively, higher than the native ligand glutamate, which has a value of -4.5 kcal/mol. The binding interactions of these agents also showed overlaps with that of doramectin and pyrvinium agents that have demonstrated activity against onchocerciasis and ivermectin, the gold standard for onchocerciasis management. This study highlights the potential of cridanimod, diminazene, and vandetanib as promising candidates for developing new treatments for onchocerciasis.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251368252"},"PeriodicalIF":2.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12411705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145013759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Language Modelling Techniques for Analysing the Impact of Human Genetic Variation. 分析人类遗传变异影响的语言建模技术。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-09-02 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251358314

Megha Hegde, Jean-Christophe Nebel, Farzana Rahman

{"title":"Language Modelling Techniques for Analysing the Impact of Human Genetic Variation.","authors":"Megha Hegde, Jean-Christophe Nebel, Farzana Rahman","doi":"10.1177/11779322251358314","DOIUrl":"10.1177/11779322251358314","url":null,"abstract":"Interpreting the effects of variants within the human genome and proteome is essential for analysing disease risk, predicting medication response, and developing personalised health interventions. Due to the intrinsic similarities between the structure of natural languages and genetic sequences, natural language processing techniques have demonstrated great applicability in computational variant effect prediction. In particular, the advent of the Transformer has led to significant advancements in the field. However, transformer-based models are not without their limitations, and a number of extensions and alternatives have been developed to improve results and enhance computational efficiency. This systematic review investigates over 50 different language modelling approaches to computational variant effect prediction over the past decade, analysing the main architectures, and identifying key trends and future directions. Benchmarking of the reviewed models remains unachievable at present, primarily due to the lack of shared evaluation frameworks and data sets.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251358314"},"PeriodicalIF":2.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12409042/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145013820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

R2eGIN: Residual Reconstruction Enhanced Graph Isomorphism Network for Accurate Prediction of Poly (ADP-Ribose) Polymerase Inhibitors. R2eGIN：残差重建增强图同构网络，用于准确预测聚adp核糖聚合酶抑制剂。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-08-29 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251366087

Candra Zonyfar, Soualihou Ngnamsie Njimbouom, Sophia Mosalla, Jeong-Dong Kim

{"title":"R2eGIN: Residual Reconstruction Enhanced Graph Isomorphism Network for Accurate Prediction of Poly (ADP-Ribose) Polymerase Inhibitors.","authors":"Candra Zonyfar, Soualihou Ngnamsie Njimbouom, Sophia Mosalla, Jeong-Dong Kim","doi":"10.1177/11779322251366087","DOIUrl":"10.1177/11779322251366087","url":null,"abstract":"An advanced graph neural network (GNN) is of great promise to facilitate predicting Poly ADPribose polymerase inhibitors (PARPi). Recent studies design models by leveraging graph representations and molecular descriptor representations, unfortunately, still face challenges in comprehensively capturing spatial relationships and contextual information between atoms. Moreover, combining molecular descriptors with graph representations may introduce information redundancy or lead to the loss of intrinsic molecular structures. To this end, we proposed a novel Residual Reconstruction Enhanced Graph Isomorphism Network (R2eGIN) learning model. Specifically, we first designed a residual GIN to learn molecular representations, reduced the impact of vanishing gradients, and enabled the model to capture long-range dependencies. Then, the reconstruction block, by predicting adjacency matrices and node features, was adopted to reconstruct the input graph. To prove the effectiveness of the proposed model, extensive experiments were conducted on 4 data sets of PARPi and compared with 7 existing models. Our evaluation of R2eGIN, conducted using 4 PARPi data sets, shows that the proposed model is comparable to or even outperforms other state-of-the-art models for PARPi prediction. Furthermore, R2eGIN can revolutionize the drug repurposing process through a substantial reduction in the time and costs commonly encountered in traditional drug development methods.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251366087"},"PeriodicalIF":2.4,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397607/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144942092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In Silico Separation of in Vitro Transcription-Derived Duplicates From PCR Duplicates to Enhance Sequence Data Utilization. 体外转录衍生重复序列与PCR重复序列的硅分离以提高序列数据的利用。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-08-26 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251365042

Ryoga Suzuki, Kenichi Horisawa, Kazumitsu Maehara, Yasuyuki Ohkawa, Atsushi Suzuki

{"title":"In Silico Separation of in Vitro Transcription-Derived Duplicates From PCR Duplicates to Enhance Sequence Data Utilization.","authors":"Ryoga Suzuki, Kenichi Horisawa, Kazumitsu Maehara, Yasuyuki Ohkawa, Atsushi Suzuki","doi":"10.1177/11779322251365042","DOIUrl":"https://doi.org/10.1177/11779322251365042","url":null,"abstract":"The polymerase chain reaction (PCR) amplification process of deoxyribonucleic acid (DNA) libraries can introduce bias in the sequence ratios. Consequently, several recent genomic and transcriptomic methods employing next-generation sequencing (NGS) utilize in vitro transcription (IVT) to amplify template polynucleotide chains. IVT amplifies nucleic acid sequences linearly, making it less susceptible to bias than the exponential amplification of PCR. Chromatin integration labeling sequencing (ChIL-seq), a tool for analyzing transcription factor binding and histone modifications, has incorporated IVT by replacing PCR in the DNA amplification step, enabling the analysis of small sample sizes, including single cells. In this study, we discovered that many of the excluded sequences known as PCR duplicates during the pre-processing step of ChIL-seq data analysis contain amplification products derived from IVT. Furthermore, we developed an in silico method to selectively eliminate PCR duplicates from NGS data while retaining IVT-derived amplification products. The method prevents excessive data reduction and significantly improves the utilization efficiency of NGS data.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251365042"},"PeriodicalIF":2.4,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12381453/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144942153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Repurposing terfenadine and domperidone for inhibition of apoptotic gene association in colorectal cancer: A system pharmacology approach integrated with molecular docking, MD simulations, and post-MD simulation analysis. 重新利用特非那定和多潘立酮抑制结直肠癌中凋亡基因关联：一种结合分子对接、MD模拟和MD后模拟分析的系统药理学方法。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-08-22 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251365019

Pushpaveni C, Hemavathi S, Santosh Prasad Chaudhary Kurmi, Biswa Ranjan Patra, V Angelin Esther, Chandrajeet Kumar Yadav, Mahalakshmi Suresha Biradar, Shankar Thapa

{"title":"Repurposing terfenadine and domperidone for inhibition of apoptotic gene association in colorectal cancer: A system pharmacology approach integrated with molecular docking, MD simulations, and post-MD simulation analysis.","authors":"Pushpaveni C, Hemavathi S, Santosh Prasad Chaudhary Kurmi, Biswa Ranjan Patra, V Angelin Esther, Chandrajeet Kumar Yadav, Mahalakshmi Suresha Biradar, Shankar Thapa","doi":"10.1177/11779322251365019","DOIUrl":"10.1177/11779322251365019","url":null,"abstract":"Colorectal cancer (CRC) remains a leading cause of global cancer mortality, underscoring the need for novel therapeutic strategies. This study used a systems pharmacology approach integrated with molecular docking and molecular dynamics (MD) simulations to evaluate the potential of repurposing terfenadine and domperidone for inhibition of apoptotic gene associations in CRC. Network pharmacology analysis identified 4 principal targets-SLC6A4 (5I6X), DRD2 (7DFP), HTR2A (6WGT), and EGFR (6LUD)-involved in the apoptotic regulatory network. Molecular docking studies demonstrated high binding affinities of both terfenadine and domperidone against all selected targets (-7.1 to -11.5 kcal/mol), with the strongest interaction observed with DRD2, where both compounds exhibited a binding affinity of -11.5 kcal/mol. Detailed interaction profiling revealed critical hydrogen bonding and hydrophobic interactions stabilizing the drug-target complexes. Molecular dynamics simulations over a 100 ns timescale confirmed the structural stability and conformational fidelity of the docked complexes, evidenced by low root mean square deviation values and consistent hydrogen bond occupancy. Furthermore, post-MD simulation study supports the stable score landscape and stability of complex. In conclusion, this integrative computational analysis highlights terfenadine and domperidone as promising candidates capable of modulating key apoptotic pathways in CRC. The findings provide a strong rationale for subsequent in vitro and in vivo studies to validate their therapeutic potential and facilitate clinical translation in CRC management.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251365019"},"PeriodicalIF":2.4,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374098/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144942129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Newly Identified Genetic Associations of Alzheimer Disease by Conditional Selective Inference: Potential Implications for the Tau Hypothesis. 通过条件选择推断新发现的阿尔茨海默病的遗传关联：对Tau假说的潜在影响。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-08-17 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251358309

Scott Hebert, Eric Nels Pederson, Zhengqing Ouyang

{"title":"Newly Identified Genetic Associations of Alzheimer Disease by Conditional Selective Inference: Potential Implications for the Tau Hypothesis.","authors":"Scott Hebert, Eric Nels Pederson, Zhengqing Ouyang","doi":"10.1177/11779322251358309","DOIUrl":"10.1177/11779322251358309","url":null,"abstract":"Over 6 million people are estimated to have been living with Alzheimer disease (AD) in 2020, with another 12 million living with Mild Cognitive Impairment (MCI). Research has been conducted to evaluate genetic links to AD, but more research is needed to improve early disease detection and improve patient outcomes. Diagnostic, demographic information, and single nucleotide polymorphism (SNP) data were collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We performed LASSO regression with conditional selective inference to perform feature selection on the SNPs and other predictors (which included education, race, and marital status), which reduced the number of SNPs from 55 106 to 13 and removed all non-SNP predictors except years of education and marital status. The included SNPs reside in genes that have clinical significance and may be associated with diseases that affect cognitive performance. The results propose the alternative alleles for 7 SNPs are associated with increased risk of AD/MCI diagnosis, while 6 SNPs are associated with decreased risk of diagnosis. The results point to a new potential pathway of disease regarding the PAK5 gene and the Tau protein hypothesis, which is supported by previous research. This research may have clinical implications and should be further studied.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251358309"},"PeriodicalIF":2.4,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12361727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144942083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 Techniques in Chronic Kidney Diseases: A Comparative Study of Classification Model Performance. 慢性肾脏疾病的机器学习技术：分类模型性能的比较研究。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-07-27 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251356563

Nguyen Dong Phuong, Nguyen Trung Tuyen, Vu Thi Thai Linh, Nghi N Nguyen, Thanh Q Nguyen

{"title":"Machine Learning Techniques in Chronic Kidney Diseases: A Comparative Study of Classification Model Performance.","authors":"Nguyen Dong Phuong, Nguyen Trung Tuyen, Vu Thi Thai Linh, Nghi N Nguyen, Thanh Q Nguyen","doi":"10.1177/11779322251356563","DOIUrl":"10.1177/11779322251356563","url":null,"abstract":"The kidneys are vital organs responsible for filtering and eliminating toxins from the body. Chronic kidney disease (CKD) is becoming increasingly prevalent, affecting not only older adults but also younger populations. To minimize kidney damage for those at risk, an accurate assessment and monitoring of CKD are crucial. Machine learning models can assist physicians in this task by providing fast and accurate detection. As a result, many health care systems have adopted machine learning, especially for disease diagnosis. In this study, we developed a system to support the diagnosis of CKD. The data were collected from the UCL machine learning database, with missing values filled using the \"mean/mode\" and the \"random sampling method.\" After data processing, we applied the polynomial technique to generate additional features, allowing the models to be better generalized. Then, we utilized feature-based stratified splitting with K-means and implemented 6 machine learning algorithms (Random Forest, Support Vector Machine [SVM], Naive Bayes, Logistic Regression, K-Nearest Neighbor [KNN], and XGBoost) to compare their performance based on accuracy. Among them, Random Forest, XGBoost, SVM, and logistic regression achieved the highest accuracy of 100%, followed by Naive Bayes (97%) and KNN (93%).","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251356563"},"PeriodicalIF":2.4,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12304504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144741153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trans-Cannabitriol as a Dual Inhibition of MPOX Adhesion Receptors L1R and E8L: An In Silico Perspective. 反式大麻二醇作为MPOX粘附受体L1R和E8L的双重抑制：一个硅视角。

IF 2.4

Bioinformatics and Biology Insights Pub Date : 2025-07-23 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251355315

Hanane Abbou, Razana Zegrari, Zainab Gaouzi, Lahcen Belyamani, Ilhame Bourais, Rachid Eljaoudi

{"title":"Trans-Cannabitriol as a Dual Inhibition of MPOX Adhesion Receptors L1R and E8L: An In Silico Perspective.","authors":"Hanane Abbou, Razana Zegrari, Zainab Gaouzi, Lahcen Belyamani, Ilhame Bourais, Rachid Eljaoudi","doi":"10.1177/11779322251355315","DOIUrl":"10.1177/11779322251355315","url":null,"abstract":"The re-emergence of monkeypox virus (MPXV) as a global public health concern highlights the urgent need for novel therapeutic strategies targeting viral proteins essential for infection. This study investigates the inhibitory potential of Trans-Cannabitriol (trans-CBT), a minor cannabinoid, against MPXV proteins L1R, H3L, and E8L using an integrative in silico framework. Homology modeling was employed to generate 3D structures of these proteins, followed by molecular docking and 1 µs molecular dynamics (MD) simulations. The trans-CBT demonstrated strong binding affinities for L1R (-10.76 kcal/mol) and E8L (-8.531 kcal/mol), with weaker interactions observed for H3L (-5.739 kcal/mol). Four MD simulations of 1 µs revealed that trans-CBT stabilizes L1R by reducing its flexibility and solvent exposure, potentially inhibiting viral entry into host cells. In contrast, trans-CBT increased the flexibility and conformational changes of E8L, possibly impairing its function in viral attachment and pathogenesis. ADMET and target prediction analyses further supported its drug-likeness and safety, with the absence of strong CB1/CB2 binding suggesting that trans-CBT may exert its antiviral effects independently of classical cannabinoid pathways. These findings provide insights into the diverse mechanisms of action of trans-CBT on MPXV proteins and underscore its potential as a broad-spectrum antiviral agent. While promising, further experimental validation and optimization are necessary to assess the real-world applicability of trans-CBT in combating MPXV infections. This work contributes to the expanding field of cannabinoid-derived antivirals and highlights the importance of exploring under-investigated phytochemicals for therapeutic applications.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251355315"},"PeriodicalIF":2.4,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290344/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144727827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bioinformatic Analysis of WNT Family Proteins. WNT家族蛋白的生物信息学分析。

IF 2.3

Bioinformatics and Biology Insights Pub Date : 2025-07-15 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251353347

Konstantin Midlovets, Natalia Volkova, Mykyta Peka

{"title":"Bioinformatic Analysis of WNT Family Proteins.","authors":"Konstantin Midlovets, Natalia Volkova, Mykyta Peka","doi":"10.1177/11779322251353347","DOIUrl":"10.1177/11779322251353347","url":null,"abstract":"WNT proteins constitute a highly conserved family of signaling molecules that play an important role in regulating embryonic development and maintaining adult tissue homeostasis. Their diverse biological functions are mediated through multiple signaling pathways, including both canonical β-catenin-dependent and several non-canonical mechanisms. The regulatory activity of WNT proteins is closely linked to their unique structural organization, the presence of N-terminal signal peptides, and posttranslational modifications. In this study, in silico methods were used to analyze the structural features of WNT proteins. Specifically, the isoelectric points, GRAVY scores, aliphatic indices, and instability indices were determined, and correlation analysis was performed to examine relationships between the latter three parameters. In addition, the characteristics of N-terminal signal peptides in WNT family proteins were investigated, with a particular focus on the bioinformatic prediction of N-terminal peptide lengths in the WNT2B protein isoforms. Furthermore, in silico modeling and molecular dynamics simulations were employed to study the tertiary structure of WNT2B and to assess the significance of O-acylation at serine for the behavior of the mature protein in an aqueous environment. Thus, using computational approaches, new data were obtained on the structural features and dynamic properties of this group of regulatory proteins.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251353347"},"PeriodicalIF":2.3,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12264420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Uncovering the Anti-Herpetic Activity of Anionic Peptides Derived From the Cytoplasmic Domain of Nectin-1. 揭示从Nectin-1细胞质结构域衍生的阴离子肽的抗疱疹活性。

IF 2.3

Bioinformatics and Biology Insights Pub Date : 2025-06-21 eCollection Date: 2025-01-01 DOI: 10.1177/11779322251344130

Rakesh Rahangdale, Sumit Birangal, Gautham Shenoy, Fayaz Shaik Mohammad, Mukesh Pasupuleti, Raghu Chandrashekar Hariharapura

{"title":"Uncovering the Anti-Herpetic Activity of Anionic Peptides Derived From the Cytoplasmic Domain of Nectin-1.","authors":"Rakesh Rahangdale, Sumit Birangal, Gautham Shenoy, Fayaz Shaik Mohammad, Mukesh Pasupuleti, Raghu Chandrashekar Hariharapura","doi":"10.1177/11779322251344130","DOIUrl":"10.1177/11779322251344130","url":null,"abstract":"Nectin-1/herpes simplex virus glycoprotein D (HSV gD) interaction is crucial to drive herpes simplex virus (HSV) entry. Polyanions are known to show great potential as antivirals. Thus, we explored a peptide-based biotherapeutic approach and, for the first time, evaluated an anionic peptide derived from nectin-1 designed to bind HSV gD. Peptides enriched in acidic and basic residues were selected and computationally modeled using PEP-FOLD3, PROCHECK, ClusPro 2.0, and Desmond. Their antiviral efficacy was tested through virucidal, cell pretreatment, attachment inhibition, entry inhibition, and cytopathic effect (CPE) inhibition assays using a 10 TCID50 (Tissue Culture Infectious Dose 50%) viral dose. Among 4 designed peptides, C1 and C2 showed strong binding to HSV-1 and HSV-2 gD in molecular dynamic (MD) simulations. Peptide C1 exhibited significant virucidal activity (HSV-1: 64.92%, HSV-2: 67.16%), attachment inhibition (HSV-1: 62.03%, HSV-2: 59.38%), and host cell-entry inhibition (HSV-1: 71.37%, HSV-2: 76.28%) at 250 µg/mL concentration. Combination treatment with peptides C1 and C2 at a final concentration of 250 µg/mL (125 µg/mL each) exhibited an additive effect against HSV-1 (68.57%) and HSV-2 (73.37%) infections when tested by CPE inhibition assay. This highlights the potential of HSV gD-targeted anionic peptides for future anti-HSV therapeutics.","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251344130"},"PeriodicalIF":2.3,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12182627/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144474008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0