Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach.
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Journal of cellular and molecular medicine
2024
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| author | Alkhateeb, Mariam Abdulaziz Aljarba, Nada H Yousafi, Qudsia Anwar, Fatima Biswas, Partha |
| author_facet | Alkhateeb, Mariam Abdulaziz Aljarba, Nada H Yousafi, Qudsia Anwar, Fatima Biswas, Partha Alkhateeb, Mariam Abdulaziz Aljarba, Nada H Yousafi, Qudsia Anwar, Fatima Biswas, Partha |
| collection | PubMed - marine biology |
| contents | Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach. Alkhateeb, Mariam Abdulaziz Aljarba, Nada H Yousafi, Qudsia Anwar, Fatima Biswas, Partha Stomach Neoplasms Humans Gene Expression Regulation, Neoplastic ErbB Receptors Protein Interaction Maps MicroRNAs Drug Design Genomics Gene Regulatory Networks Gene Expression Profiling Computer-Aided Design Molecular Docking Simulation Gene Ontology Computational Biology Antineoplastic Agents Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets. |
| format | Artículo científico |
| id | pubmed_39434198 |
| institution | PubMed |
| language | en |
| publishDate | 2024 |
| publisher | Journal of cellular and molecular medicine |
| record_format | pubmed |
| spellingShingle | Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach. Alkhateeb, Mariam Abdulaziz Aljarba, Nada H Yousafi, Qudsia Anwar, Fatima Biswas, Partha Stomach Neoplasms Humans Gene Expression Regulation, Neoplastic ErbB Receptors Protein Interaction Maps MicroRNAs Drug Design Genomics Gene Regulatory Networks Gene Expression Profiling Computer-Aided Design Molecular Docking Simulation Gene Ontology Computational Biology Antineoplastic Agents Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach. Alkhateeb, Mariam Abdulaziz Aljarba, Nada H Yousafi, Qudsia Anwar, Fatima Biswas, Partha Stomach Neoplasms Humans Gene Expression Regulation, Neoplastic ErbB Receptors Protein Interaction Maps MicroRNAs Drug Design Genomics Gene Regulatory Networks Gene Expression Profiling Computer-Aided Design Molecular Docking Simulation Gene Ontology Computational Biology Antineoplastic Agents Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package. Gene Ontology (GO) analysis of DEGs was performed using DAVID. The protein-protein interaction network was constructed by STRING database plugin in Cytoscape. Subclusters/modules of important interacting genes in main network were extracted by using MCODE. The hub genes from in the network were identified by using Cytohubba. The miRNet tool built a hub gene/mRNA-miRNA network and Kaplan-Meier-Plotter conducted survival analysis. AutoDock Vina and GROMACS MD simulations were used for docking and stability analysis of marine compounds against the 5CNN protein. Total 734 DEGs (507 up-regulated and 228 down-regulated) were identified. Differentially expressed genes (DEGs) were enriched in processes like cell-cell adhesion and ATP binding. Eight hub genes (EGFR, HSPA90AA1, MAPK1, HSPA4, PPP2CA, CDKN2A, CDC20, and ATM) were selected for further analysis. A total of 23 miRNAs associated with hub genes were identified, with 12 of them targeting PPP2CA. EGFR displayed the highest expression and hazard rate in survival analyses. The kinase domain of EGFR (PDBID: 5CNN) was chosen as the drug target. Adociaquinone A from Petrosia alfiani, docked with 5CNN, showed the lowest binding energy with stable interactions across a 50 ns MD simulation, highlighting its potential as a lead molecule against EGFR. This study has identified crucial DEGs and hub genes in gastric cancer, proposing novel therapeutic targets. Specifically, Adociaquinone A demonstrates promising potential as a bioactive drug against EGFR in gastric cancer, warranting further investigation. The predicted miRNA against the hub gene/proteins can also be used as potential therapeutic targets. |
| title | Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach. |
| topic | Stomach Neoplasms Humans Gene Expression Regulation, Neoplastic ErbB Receptors Protein Interaction Maps MicroRNAs Drug Design Genomics Gene Regulatory Networks Gene Expression Profiling Computer-Aided Design Molecular Docking Simulation Gene Ontology Computational Biology Antineoplastic Agents |
| url | https://pubmed.ncbi.nlm.nih.gov/39434198/ |