Bioinformatics and Biology Insights最新文献

{"title":"Emergence of SARS-CoV-2 Variants Are Induced by Coinfections With Dengue.","authors":"Hassan M Al-Emran, Fazlur Rahman, Laxmi Sarkar, Prosanto Kumar Das, Provakar Mondol, Suriya Yesmin, Pipasha Sultana, Toukir Ahammed, Rasel Parvez, Md Shazid Hasan, Shovon Lal Sarkar, M Shaminur Rahman, Anamica Hossain, Mahmudur Rahman, Ovinu Kibria Islam, Md Tanvir Islam, Shireen Nigar, Selina Akter, A S M Rubayet Ul Alam, Mohammad Mahfuzur Rahman, Iqbal Kabir Jahid, M Anwar Hossain","doi":"10.1177/11779322241272399","DOIUrl":"https://doi.org/10.1177/11779322241272399","url":null,"abstract":"<p><p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has accumulated a series of point mutations and evolved into several variants of concern (VOCs), some of which are more transmissible and potentially more severe than the original strain. The most notable VOCs are Alpha, Beta, Gamma, Delta, and Omicron, which have spread to various parts of the world. This study conducted surveillance in Jashore, Bangladesh to identify the prevalence of SARS-CoV-2 coinfected with dengue virus and their genomic effect on the emergence of VOCs. A hospital-based COVID-19 surveillance from June to August, 2021 identified 9 453 positive patients in the surveillance area. The study enrolled 572 randomly selected COVID-19-positive patients, of which 11 (2%) had dengue viral coinfection. Whole genome sequences of SARS-CoV-2 were analyzed and compared between coinfection positive and negative group. In addition, we extracted 185 genome sequences from GISAID to investigate the cross-correlation function between SARS-CoV-2 mutations and VOC; multiple ARIMAX(p,d,q) models were developed to estimate the average number of amino acid (aa) substitution among different SARS-CoV-2 VOCs. The results of the study showed that the coinfection group had an average of 30.6 (±1.7) aa substitutions in SARS-CoV-2, whereas the dengue-negative COVID-19 group had that average of 25.6 (±1.8; <i>P</i> < .01). The coinfection group showed a significant difference of aa substitutions in open reading frame (ORF) and N-protein when compared to dengue-negative group (<i>P</i> = .03). Our ARIMAX models estimated that the emergence of SARS-CoV-2 variants Delta required additional 9 to 12 aa substitutions than Alpha, Beta, or Gamma variant. The emergence of Omicron accumulated additional 19 (95% confidence interval [CI]: 15.74, 21.95) aa substitution than Delta. Increased number of point mutations in SARS-CoV-2 genome identified from coinfected cases could be due to the compromised immune function of host and induced adaptability of pathogens during coinfections. As a result, new variants might be emerged when series of coinfection events occur during concurrent two epidemics.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241272399"},"PeriodicalIF":2.3,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11406487/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142280202","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}

{"title":"Adopting Integrated Bioinformatics and Systems Biology Approaches to Pinpoint the COVID-19 Patients' Risk Factors That Uplift the Onset of Posttraumatic Stress Disorder.","authors":"Sabbir Ahmed, Md Arju Hossain, Sadia Afrin Bristy, Md Shahjahan Ali, Md Habibur Rahman","doi":"10.1177/11779322241274958","DOIUrl":"https://doi.org/10.1177/11779322241274958","url":null,"abstract":"<p><p>Owing to the recent emergence of COVID-19, there is a lack of published research and clinical recommendations for posttraumatic stress disorder (PTSD) risk factors in patients who contracted or received treatment for the virus. This research aims to identify potential molecular targets to inform therapeutic strategies for this patient population. RNA sequence data for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and PTSD (from the National Center for Biotechnology Information [NCBI]) were processed using the GREIN database. Protein-protein interaction (PPI) networks, pathway enrichment analyses, miRNA interactions, gene regulatory network (GRN) studies, and identification of linked drugs, chemicals, and diseases were conducted using STRING, DAVID, Enrichr, Metascape, ShinyGO, and NetworkAnalyst v3.0. Our analysis identified 15 potentially unique hub proteins within significantly enriched pathways, including PSMB9, MX1, HLA-DOB, HLA-DRA, IFIT3, OASL, RSAD2, and so on, filtered from a pool of 201 common differentially expressed genes (DEGs). Gene ontology (GO) terms and metabolic pathway analyses revealed the significance of the extracellular region, extracellular space, extracellular exosome, adaptive immune system, and interleukin (IL)-18 signaling pathways. In addition, we discovered several miRNAs (hsa-mir-124-3p, hsa-mir-146a-5p, hsa-mir-148b-3p, and hsa-mir-21-3p), transcription factors (TF) (WRNIP1, FOXC1, GATA2, CREB1, and RELA), a potentially repurposable drug carfilzomib and chemicals (tetrachlorodibenzodioxin, estradiol, arsenic trioxide, and valproic acid) that could regulate the expression levels of hub proteins at both the transcription and posttranscription stages. Our investigations have identified several potential therapeutic targets that elucidate the probability that victims of COVID-19 experience PTSD. However, they require further exploration through clinical and pharmacological studies to explain their efficacy in preventing PTSD in COVID-19 patients.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241274958"},"PeriodicalIF":2.3,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11402063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142280201","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}

{"title":"RhizoBindingSites v2.0 Is a Bioinformatic Database of DNA Motifs Potentially Involved in Transcriptional Regulation Deduced From Their Genomic Sites.","authors":"Hermenegildo Taboada-Castro, Alfredo José Hernández-Álvarez, Jaime A Castro-Mondragón, Sergio Encarnación-Guevara","doi":"10.1177/11779322241272395","DOIUrl":"10.1177/11779322241272395","url":null,"abstract":"<p><p>RhizoBindingSites is a <i>de novo</i> depurified database of conserved DNA motifs potentially involved in the transcriptional regulation of the <i>Rhizobium</i>, <i>Sinorhizobium</i>, <i>Bradyrhizobium</i>, <i>Azorhizobium</i>, and <i>Mesorhizobium</i> genera covering 9 representative symbiotic species, deduced from the upstream regulatory sequences of orthologous genes (O-matrices) from the Rhizobiales taxon. The sites collected with O-matrices per gene per genome from RhizoBindingSites were used to deduce matrices using the dyad-Regulatory Sequence Analysis Tool (RSAT) method, giving rise to novel S-matrices for the construction of the RizoBindingSites v2.0 database. A comparison of the S-matrix logos showed a greater frequency and/or re-definition of specific-position nucleotides found in the O-matrices. Moreover, S-matrices were better at detecting genes in the genome, and there was a more significant number of transcription factors (TFs) in the vicinity than O-matrices, corresponding to a more significant genomic coverage for S-matrices. O-matrices of 3187 TFs and S-matrices of 2754 TFs from 9 species were deposited in RhizoBindingSites and RhizoBindingSites v2.0, respectively. The homology between the matrices of TFs from a genome showed inter-regulation between the clustered TFs. In addition, matrices of AraC, ArsR, GntR, and LysR ortholog TFs showed different motifs, suggesting distinct regulation. Benchmarking showed 72%, 68%, and 81% of common genes per regulon for O-matrices and approximately 14% less common genes with S-matrices of <i>Rhizobium etli</i> CFN42, <i>Rhizobium leguminosarum</i> bv. <i>viciae</i> 3841, and <i>Sinorhizobium meliloti</i> 1021. These data were deposited in RhizoBindingSites and the RhizoBindingSites v2.0 database (http://rhizobindingsites.ccg.unam.mx/).</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241272395"},"PeriodicalIF":2.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11380129/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142153089","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}

{"title":"Comparing Deep Learning Performance for Chronic Lymphocytic Leukaemia Cell Segmentation in Brightfield Microscopy Images.","authors":"Markéta Vašinková, Vít Doleží, Michal Vašinek, Petr Gajdoš, Eva Kriegová","doi":"10.1177/11779322241272387","DOIUrl":"10.1177/11779322241272387","url":null,"abstract":"<p><strong>Objectives: </strong>This article focuses on the detection of cells in low-contrast brightfield microscopy images; in our case, it is chronic lymphocytic leukaemia cells. The automatic detection of cells from brightfield time-lapse microscopic images brings new opportunities in cell morphology and migration studies; to achieve the desired results, it is advisable to use state-of-the-art image segmentation methods that not only detect the cell but also detect its boundaries with the highest possible accuracy, thus defining its shape and dimensions.</p><p><strong>Methods: </strong>We compared eight state-of-the-art neural network architectures with different backbone encoders for image data segmentation, namely U-net, U-net++, the Pyramid Attention Network, the Multi-Attention Network, LinkNet, the Feature Pyramid Network, DeepLabV3, and DeepLabV3+. The training process involved training each of these networks for 1000 epochs using the PyTorch and PyTorch Lightning libraries. For instance segmentation, the watershed algorithm and three-class image semantic segmentation were used. We also used StarDist, a deep learning-based tool for object detection with star-convex shapes.</p><p><strong>Results: </strong>The optimal combination for semantic segmentation was the U-net++ architecture with a ResNeSt-269 background with a data set intersection over a union score of 0.8902. For the cell characteristics examined (area, circularity, solidity, perimeter, radius, and shape index), the difference in mean value using different chronic lymphocytic leukaemia cell segmentation approaches appeared to be statistically significant (Mann-Whitney <i>U</i> test, <i>P</i> < .0001).</p><p><strong>Conclusion: </strong>We found that overall, the algorithms demonstrate equal agreement with ground truth, but with the comparison, it can be seen that the different approaches prefer different morphological features of the cells. Consequently, choosing the most suitable method for instance-based cell segmentation depends on the particular application, namely, the specific cellular traits being investigated.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241272387"},"PeriodicalIF":2.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11378236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142153142","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}

{"title":"Marine-Derived Furanones Targeting Quorum-Sensing Receptors in <i>Pseudomonas aeruginosa</i>: Molecular Insights and Potential Mechanisms of Inhibition.","authors":"Aaron Boakye, Muntawakilu Padiga Seidu, Alice Adomako, Michael Konney Laryea, Lawrence Sheringham Borquaye","doi":"10.1177/11779322241275843","DOIUrl":"10.1177/11779322241275843","url":null,"abstract":"<p><p>The quorum-sensing (QS) machinery in disease-causing microorganisms is critical in developing antibiotic resistance. In <i>Pseudomonas aeruginosa</i>, QS is involved in biofilm formation, virulence factors production, and general tolerance to antimicrobials. Owing to the major role QS plays, interference in the process is probably a facile route to overcome antimicrobial resistance. Some furanone-derived compounds from marine sources have shown promising anti-QS activity. However, their protein targets and potential mechanisms of action have not been explored. To elucidate their potential protein targets in this study, marine metabolites with furanone backbones similar to their cognitive autoinducers (AIs) were screened against various QS receptors (LasR, RhlR, and PqsR) using molecular docking and molecular dynamics (MD) simulation techniques. The order by which the compounds bind to the receptors follows LasR > RhlR > PqsR. Compounds exhibited remarkable stability against LasR and RhlR, likely because the AIs of these receptors are structural analogs of furanones. Furanones with shorter alkyl side chains bound strongly against RhlR. The presence of halogens improved binding against various receptors. PqsR, with its hydrophobic-binding site and structurally different AIs, showed weaker binding. This study provides a molecular basis for the design of potent antagonists against QS receptors using marine-derived furanones.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241275843"},"PeriodicalIF":2.3,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11378241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142153088","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}

{"title":"Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.","authors":"Md Shahin Alam, Adiba Sultana, Md Kaderi Kibria, Alima Khanam, Guanghui Wang, Md Nurul Haque Mollah","doi":"10.1177/11779322241272386","DOIUrl":"10.1177/11779322241272386","url":null,"abstract":"<p><p>Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (<i>CCNB1</i>, <i>CDK1</i>, <i>TOP2A</i>, <i>CCNA2</i>, <i>ESR1</i>, <i>EGFR</i>, <i>JUN</i>, <i>ACTB</i>, <i>TP53</i>, and <i>CCND1</i>) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs <i>ESR1</i>, AMG-900 vs <i>TOP2A</i>, and CHEMBL1765740 vs <i>EGFR</i>) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241272386"},"PeriodicalIF":2.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11375675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142139264","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}

{"title":"Proteomics Exploration of <i>Brucella melitensis</i> to Design an Innovative Multi-Epitope mRNA Vaccine.","authors":"Maryam Asadinezhad, Iraj Pakzad, Parisa Asadollahi, Sobhan Ghafourian, Behrooz Sadeghi Kalani","doi":"10.1177/11779322241272404","DOIUrl":"10.1177/11779322241272404","url":null,"abstract":"<p><p>Brucellosis is a chronic and debilitating disease in humans, causing great economic losses in the livestock industry. Making an effective vaccine is one of the most important concerns for this disease. The new mRNA vaccine technology due to its accuracy and high efficiency has given promising results in various diseases. The objective of this research was to create a novel mRNA vaccine with multiple epitopes targeting <i>Brucella melitensis</i>. Seventeen antigenic proteins and their appropriate epitopes were selected with immunoinformatic tools and surveyed in terms of toxicity, allergenicity, and homology. Then, their presentation and identification by MHC cells and other immune cells were checked with valid tools such as molecular docking, and a multi-epitope protein was modeled, and after optimization, mRNA was analyzed in terms of structure and stability. Ultimately, the immune system's reaction to this novel vaccine was evaluated and the results disclosed that the designed mRNA construct can be an effective and promising vaccine that requires laboratory and clinical trials.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241272404"},"PeriodicalIF":2.3,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11365029/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142104129","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}

{"title":"Probing the Therapeutic Efficacy of <i>Combretum paniculatum</i> Extract and GC-FID-Identified Phytochemicals as Novel Agents for Diabetes Mellitus.","authors":"Ifeoma F Chukwuma, Chidi E Atikpoh, Victor O Apeh, Florence N Nworah, Lawrence Us Ezeanyika","doi":"10.1177/11779322241271537","DOIUrl":"10.1177/11779322241271537","url":null,"abstract":"<p><strong>Objectives: </strong>Oxidative stress is implicated in several metabolic cascades involved in glucose control. Hence, investigating antioxidant and antidiabetic activities is crucial for discovering an effective diabetes mellitus (DM) agent. This study was aimed at probing the therapeutic efficacy of hydro-ethanolic extract of <i>Combretum paniculatum</i> (HECP) and gas chromatography-flame ionization detector (GC-FID)-identified phytochemicals as novel agents for DM.</p><p><strong>Methods: </strong>We determined the total phenols, flavonoids, and antioxidant vitamins in HECP using standard methods. A GC-FID was used to decipher phytochemicals of HECP. The antioxidant and antidiabetic activities of HECP were assessed using in vitro and in silico approaches.</p><p><strong>Results: </strong>The results revealed that HECP is affluent in phenols, flavonoids, and vitamin E and demonstrated engaging antioxidant activities in 1,1-diphenyl-2-picryl-hydroxyl (DPPH; IC₅₀ = 0.83 µg/mL), thiobarbituric acid-reactive substances TBARS; IC₅₀ = 2.28 µg/mL), and ferric-reducing antioxidant power assay (FRAP; IC₅₀ = 2.89 µg/mL). Compared with the reference drug, acarbose, HECP exhibited good α-amylase and α-glucosidase inhibitory capacity, having IC₅₀ values of 14.21 and 13.23 µg/mL, respectively, against 13.06 and 11.71 µg/mL recorded for acarbose. More so, the extract's top 6 scoring phytochemicals (rutin, kaempferol, epicatechin, ephedrine, naringenin, and resveratrol) had strong interactions with amino acid residues within and around α-amylase and α-glucosidase active site domains. All the compounds but rutin had favourable drug-like characteristics, pharmacokinetics, and safety profiles when compared with acarbose.</p><p><strong>Conclusion: </strong>Altogether, our results vindicate the use of this herb in treating DM locally and reveal that it has pharmaceutically active components that could be used as novel leads in the development of DM drugs.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241271537"},"PeriodicalIF":2.3,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11342321/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142054881","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}

{"title":"Identification of Lupus-Associated Genes in the Pathogenesis of Pre-eclampsia Via Bioinformatic Analysis.","authors":"Qianwen Dai, Mengtao Li, Xinping Tian, Yijun Song, Jiuliang Zhao","doi":"10.1177/11779322241271558","DOIUrl":"10.1177/11779322241271558","url":null,"abstract":"<p><p>Pre-eclampsia (PE) is a severe pregnancy complication that is more common in patients with systemic lupus erythematosus (SLE). Although the exact causes of these conditions are not fully understood, the immune system plays a key role. To investigate the connection between SLE and PE, we analyzed genes associated with SLE that may contribute to the development of PE. We collected 9 microarray data sets from the NCBI GEO database and used Limma to identify the differentially expressed genes (DEGs). In addition, we employed weighted gene co-expression network analysis (WGCNA) to pinpoint the hub genes of SLE and examined immune infiltration using Cibersort. By constructing a protein-protein interaction (PPI) network and using CytoHubba, we identified the top 20 PE hub genes. Subsequently, we created a nomogram and conducted a receiver operating characteristic (ROC) analysis to predict the risk of PE. Our analysis, including gene set enrichment analysis (GSEA) and PE DEGs enrichment analysis, revealed significant involvement in placenta development and immune response. Two pivotal genes, BCL6 and MME, were identified, and their validity was confirmed using 5 data sets. The nomogram demonstrated good diagnostic performance (AUC: 0.82-0.96). Furthermore, we found elevated expression levels of both genes in SLE peripheral blood mononuclear cells (PBMCs) and PE placental specimens within the case group. Analysis of immune infiltration in the SLE data set showed a strong positive correlation between the expression of both genes and neutrophil infiltration. BCL6 and MME emerged as crucial genes in lupus-related pregnancies associated with the development of PE, for which we devised a nomogram. These findings provide potential candidate genes for further research in the diagnosis and understanding of the pathophysiology of PE.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241271558"},"PeriodicalIF":2.3,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11337183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142016354","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}

{"title":"Overcoming Resistance in Cancer Therapy: Computational Exploration of PIK3CA Mutations, Unveiling Novel Non-Toxic Inhibitors, and Molecular Insights Into Targeting PI3Kα.","authors":"Ilham Kandoussi, Ghyzlane El Haddoumi, Mariam Mansouri, Lahcen Belyamani, Azeddine Ibrahimi, Rachid Eljaoudi","doi":"10.1177/11779322241269386","DOIUrl":"10.1177/11779322241269386","url":null,"abstract":"<p><p>Phosphoinositide-3-kinases (PI3 K) are pivotal regulators of cell signaling implicated in various cancers. Particularly, mutations in the PIK3CA gene encoding the p110α catalytic subunit drive oncogenic signaling, making it an attractive therapeutic target. Our study conducted in silico exploration of 31 PIK3CA mutations across breast, endometrial, colon, and ovarian cancers, assessing their impacts on response to PI3Kα inhibitors and identifying potential non-toxic inhibitors and also elucidating their effects on protein stability and flexibility. Specifically, we observed significant alterations in the stability and flexibility of the PI3 K protein induced by these mutations. Through molecular docking analysis, we evaluated the binding interactions between the selected inhibitors and the PI3 K protein. The filtration of ligands involved calculating chemical descriptors, incorporating Veber and Lipinski rules, as well as IC50 values and toxicity predictions. This process reduced the initial dataset of 1394 ligands to 12 potential non-toxic inhibitors, and four reference inhibitors with significant biological activity in clinical trials were then chosen based on their physico-chemical properties. This analysis revealed Lig5's exceptional performance, exhibiting superior affinity and specificity compared to established reference inhibitors such as pictilisib. Lig5 formed robust binding interactions with the PI3 K protein, suggesting its potential as a highly effective therapeutic agent against PI3 K-driven cancers. Furthermore, molecular dynamics simulations provided valuable insights into Lig5's stability and its interactions with PI3 K over 100 ns. These simulations supported Lig5's potential as a versatile inhibitor capable of effectively targeting various mutational profiles of PI3 K, thereby mitigating issues related to resistance and toxicity commonly associated with current inhibitors.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241269386"},"PeriodicalIF":2.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11339747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142035198","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}