Bioinformatics and Biology Insights最新文献

{"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}

{"title":"Malivhu: A Comprehensive Bioinformatics Resource for Filtering SARS and MERS Virus Proteins by Their Classification, Family and Species, and Prediction of Their Interactions Against Human Proteins.","authors":"David Guevara-Barrientos, Rakesh Kaundal","doi":"10.1177/11779322241263671","DOIUrl":"10.1177/11779322241263671","url":null,"abstract":"<p><p>COVID 19 pandemic is still ongoing, having taken more than 6 million human lives with it, and it seems that the world will have to learn how to live with the virus around. In consequence, there is a need to develop different treatments against it, not only with vaccines, but also new medicines. To do this, human-virus protein-protein interactions (PPIs) play a key part in drug-target discovery, but finding them experimentally can be either costly or sometimes unreliable. Therefore, computational methods arose as a powerful alternative to predict these interactions, reducing costs and helping researchers confirm only certain interactions instead of trying all possible combinations in the laboratory. Malivhu is a tool that predicts human-virus PPIs through a 4-phase process using machine learning models, where phase 1 filters ssRNA(+) class virus proteins, phase 2 filters <i>Coronaviridae</i> family proteins and phase 3 filters severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) species proteins, and phase 4 predicts human-SARS-CoV/SARS-CoV-2/MERS protein-protein interactions. The performance of the models was measured with Matthews correlation coefficient, F1-score, specificity, sensitivity, and accuracy scores, getting accuracies of 99.07%, 99.83%, and 100% for the first 3 phases, respectively, and 94.24% for human-SARS-CoV PPI, 94.50% for human-SARS-CoV-2 PPI, and 95.45% for human-MERS PPI on independent testing. All the prediction models developed for each of the 4 phases were implemented as web server which is freely available at https://kaabil.net/malivhu/.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241263671"},"PeriodicalIF":2.3,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11325310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141987315","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":"Elucidation of the CadA Protein 3D Structure and Affinity for Metals.","authors":"Rajkumar Prabhakaran, Rajkumar Thamarai","doi":"10.1177/11779322241266701","DOIUrl":"10.1177/11779322241266701","url":null,"abstract":"<p><p>The mitigation of cadmium (Cd) pollution, a significant ecological threat, is of paramount importance. <i>Pseudomonas aeruginosa</i> harbors 2 Cd resistance genes, namely, <i>cadR</i> and <i>cadA</i>. Presently, our focus is on the identification and characterization of the cation-transporting P-type ATPase (cadA) in <i>Pseudomonas aeruginosa</i> BC15 through <i>in silico</i> methods. The CadA protein and its binding capacities remain poorly understood, with no available structural elucidation. The presence of the <i>cadA</i> gene in <i>P aeruginosa</i> was confirmed, showing a striking 99% sequence similarity with both <i>P aeruginosa</i> and <i>P putida</i>. Phylogenetic analysis unveiled the evolutionary relationship between CadA protein sequences from various <i>Pseudomonas</i> species. Physicochemical analysis demonstrated the stability of CadA, revealing a composition of 690 amino acids, a molecular weight of 73 352.85, and a predicted isoelectric point (PI) of 5.39. Swiss-Model homology modelling unveiled a 33.73% sequence homology with CopA (3J09), and the projected structure indicated that 89.3% of amino acid residues were situated favourably within the Ramachandran plot, signifying energetic stability. Notably, the study identified metal-binding sites in CadA, namely, H3, C30, C32, C35, H48, C89, and C106. Docking studies revealed a higher efficiency of Cd binding with CadA compared to other heavy metals. This underscores the crucial role of N-terminal cysteine residues in Cd removal. It is evident that CadA of <i>P aeruginosa</i> BC15 plays a crucial role in Cd tolerance, rendering it a potential microorganism for Cd toxicity bioremediation. The structural and functional elucidation of CadA, facilitated by this study, holds promise for advancing cost-effective strategies in the remediation of cadmium-contaminated environments.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241266701"},"PeriodicalIF":2.3,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11311160/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141916136","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":"Reproduction of Awassi and Hamdani Sheep Is Associated With a Novel Missense SNP (p.24Ile>Thr) of the <i>GnIH</i> Gene.","authors":"Waleed A Abd Al-Jabar, Tahreer M Al-Thuwaini","doi":"10.1177/11779322241267188","DOIUrl":"10.1177/11779322241267188","url":null,"abstract":"<p><strong>Objectives: </strong>Litter size is a crucial economic factor in the sheep industry. Several factors and genes influence litter size, making the identification of genes or loci involved a genetic challenge. Gonadotropin-inhibitory hormone (<i>GnIH</i>) is one of several genes that influence sheep's reproductive traits. Thus, this study aimed to investigate whether variations in the <i>GnIH</i> gene affect the reproductive performance of Awassi and Hamdani ewes.</p><p><strong>Methods: </strong>DNA was extracted from 99 single-progeny ewes and 101 twin ewes. The polymerase chain reaction (PCR) produced amplicons of 262 bp, 275 bp, and 284 bp from exons 1, 2, and 3 of the <i>GnIH</i> gene. Single-strand conformational polymorphism (SSCP) technique was used for genotyping experiments. Sequencing and in silico analysis were performed on each set of SSCP-resolved bands.</p><p><strong>Results: </strong>Two genotypes of 262 bp amplicons were found: TT and TC. Sequence analysis revealed a novel missense mutation in the TC genotype at position c.122T>C. Five in silico tools were used to assess the impact of this mutation on GnIH protein structure, function, and stability, all of them demonstrated a deleterious effect. An analysis of statistical data revealed a strong correlation between the c.122T>C single-nucleotide polymorphism (SNP) and reproductive performance. Ewes with the SNP 122T>C exhibited a significant increase in litter size, twinning rates, lambing rates, and days to lambing when compared with ewes with the TT genotype. A lower number of lambs were born to ewes with the TT genotype than those with the TC genotype.</p><p><strong>Conclusion: </strong>These results concluded that the c.122T>C SNP variant positively influences the reproductive performance of Awassi and Hamdani sheep. Sheep that carry the c.122T>C SNP show higher litter size and increased productivity.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241267188"},"PeriodicalIF":2.3,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11304492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141900987","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 an Allele-Specific Transcription Factor Binding Interaction that May Regulate PLA2G2A Gene Expression.","authors":"Aki Hara, Eric Lu, Laurel Johnstone, Michelle Wei, Shudong Sun, Brian Hallmark, Joseph C Watkins, Hao Helen Zhang, Guang Yao, Floyd H Chilton","doi":"10.1177/11779322241261427","DOIUrl":"10.1177/11779322241261427","url":null,"abstract":"<p><p>The secreted phospholipase A₂ (sPLA₂) isoform, sPLA₂-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA₂-IIA. The work in the manuscript leveraged 4 publicly available datasets to investigate the mechanism by which rs11573156 influences sPLA₂-IIA levels via bioinformatics and modeling analysis. Through genotype-tissue expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA₂-IIA, <i>PLA2G2A</i>. SNP2TFBS was used to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified eQTL SNPs. Subsequently, candidate TF-SNP interactions were cross-referenced with the ChIP-seq results in matched tissues from ENCODE. SP1-rs11573156 emerged as the significant TF-SNP pair in the liver. Further analysis revealed that the upregulation of <i>PLA2G2A</i> transcript levels through the rs11573156 variant was likely affected by tissue SP1 protein levels. Using an ordinary differential equation based on Michaelis-Menten kinetic assumptions, we modeled the dependence of <i>PLA2G2A</i> transcription on SP1 protein levels, incorporating the SNP influence. Collectively, our analysis strongly suggests that the difference in the binding dynamics of SP1 to different rs11573156 alleles may underlie the allele-specific PLA2G2A expression in different tissues, a mechanistic model that awaits future direct experimental validation. This mechanism likely contributes to the variation in circulating sPLA₂-IIA protein levels in the human population, with implications for a wide range of human diseases.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241261427"},"PeriodicalIF":2.3,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11287738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854739","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":"Devising Isolation Forest-Based Method to Investigate the sRNAome of <i>Mycobacterium tuberculosis</i> Using sRNA-seq Data.","authors":"Upasana Maity, Ritika Aggarwal, Rami Balasubramanian, Divya Lakshmi Venkatraman, Shubhada R Hegde","doi":"10.1177/11779322241263674","DOIUrl":"10.1177/11779322241263674","url":null,"abstract":"<p><p>Small non-coding RNAs (sRNAs) regulate the synthesis of virulence factors and other pathogenic traits, which enables the bacteria to survive and proliferate after host infection. While high-throughput sequencing data have proved useful in identifying sRNAs from the intergenic regions (IGRs) of the genome, it remains a challenge to present a complete genome-wide map of the expression of the sRNAs. Moreover, existing methodologies necessitate multiple dependencies for executing their algorithm and also lack a targeted approach for the <i>de novo</i> sRNA identification. We developed an Isolation Forest algorithm-based method and the tool Prediction Of sRNAs using Isolation Forest for the <i>de novo</i> identification of sRNAs from available bacterial sRNA-seq data (http://posif.ibab.ac.in/). Using this framework, we predicted 1120 sRNAs and 46 small proteins in <i>Mycobacterium tuberculosis</i>. Besides, we highlight the context-dependent expression of novel sRNAs, their probable synthesis, and their potential relevance in stress response mechanisms manifested by <i>M. tuberculosis.</i></p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241263674"},"PeriodicalIF":2.3,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11292719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141874122","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":"Machine Learning-Based Approach to Identify Inhibitors of Sterol-14-Alpha Demethylase: A Study on Chagas Disease.","authors":"Jamiyu A Saliu","doi":"10.1177/11779322241262635","DOIUrl":"10.1177/11779322241262635","url":null,"abstract":"<p><strong>Objectives: </strong>Chagas Disease, caused by the parasite <i>Trypanosoma cruzi</i>, remains a significant public health concern, particularly in Latin America. The current standard treatment for Chagas Disease, benznidazole, is associated with various side effects, necessitating the search for alternative therapeutic options. In this study, we aimed to identify potential therapeutics for Chagas Disease through a comprehensive computational analysis.</p><p><strong>Methods: </strong>A library of compounds derived from <i>Cananga odorata</i> was screened using a combination of pharmacophore modeling, structure-based screening, and quantitative structure-activity relationship (QSAR) analysis. The pharmacophore model facilitated the efficient screening of the compound library, while the structure-based screening identified hit compounds with promising inhibitory potential against the target enzyme, sterol-14-alpha demethylase.</p><p><strong>Results: </strong>The QSAR model predicted the bioactivity of the hit compounds, revealing one compound to exhibit superior activity compared to benznidazole. Evaluation of the physicochemical, pharmacokinetic, toxicity, and medicinal chemistry properties of the hit compounds indicated their drug-like characteristics, oral bioavailability, ease of synthesis, and reduced toxicity profiles.</p><p><strong>Conclusion: </strong>Overall, our findings present a promising avenue for the discovery of novel therapeutics for Chagas Disease. The identified hit compounds possess favorable drug-like properties and demonstrate potent inhibitory effects against the target enzyme. Further in vitro and in vivo studies are warranted to validate their efficacy and safety profiles.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241262635"},"PeriodicalIF":2.3,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11287730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854740","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":"Nilotinib: Disrupting the MYC-MAX Heterocomplex.","authors":"Kamilla Shah, Maham Ansari, Samina Saeed, Abdul Wali, Muhammad Mushtaq Yasinzai","doi":"10.1177/11779322241267056","DOIUrl":"10.1177/11779322241267056","url":null,"abstract":"<p><p>MYC is a transcription factor crucial for maintaining cellular homeostasis, and its dysregulation is associated with highly aggressive cancers. Despite being considered \"undruggable\" due to its unstable protein structure, MYC gains stability through its interaction with its partner protein, MAX. The MYC-MAX heterodimer orchestrates the expression of numerous genes that contribute to an oncogenic phenotype. Previous efforts to develop small molecules, disrupting the MYC-MAX interaction, have shown promise in vitro but none have gained clinical approval. Our current computer-aided study utilizes an approach to explore drug repurposing as a strategy for inhibiting the c-MYC-MAX interaction. We have focused on compounds from DrugBank library, including Food and Drug Administration-approved drugs or those under investigation for other medical conditions. First, we identified a potential druggable site on flat interface of the c-MYC protein, which served as the target for virtual screening. Using both activity-based and structure-based screening, we comprehensively assessed the entire DrugBank library. Structure-based virtual screening was performed on AutoDock Vina and Glide docking tools, while activity-based screening was performed on two independent quantitative structure-activity relationship models. We focused on the top 2% of hit molecules from all screening methods. Ultimately, we selected consensus molecules from these screenings-those that exhibited both a stable interaction with c-MYC and superior inhibitory activity against c-MYC-MAX interaction. Among the evaluated molecules, we identified a protein kinase inhibitor (tyrosine kinase inhibitor [TKI]) known as nilotinib as a promising candidate targeting c-MYC-MAX dimer. Molecular dynamic simulations demonstrated a stable interaction between MYC and nilotinib. The interaction with nilotinib led to the stabilization of a region of the MYC protein that is distorted in apo-MYC and is important for MAX binding. Further analysis of differentially expressed gene revealed that nilotinib, uniquely among the tested TKIs, induced a gene expression program in which half of the genes were known to be responsive to c-MYC. Our findings provide the foundation for subsequent in vitro and in vivo investigations aimed at evaluating the efficacy of nilotinib in managing MYC oncogenic activity.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"18 ","pages":"11779322241267056"},"PeriodicalIF":2.3,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11287739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141854741","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}