Dataset Information

RNA-Sequencing, Connectivity Mapping, and Molecular Docking to Investigate Ligand-Protein Binding for Potential Drug Candidates for the Treatment of Wilms Tumor.

ABSTRACT: BACKGROUND Wilms tumor, or nephroblastoma, is a malignant pediatric embryonal renal tumor that has a poor prognosis. This study aimed to use bioinformatics data, RNA-sequencing, connectivity mapping, molecular docking, and ligand-protein binding to identify potential targets for drug therapy in Wilms tumor. MATERIAL AND METHODS Wilms tumor and non-tumor samples were obtained from high throughput gene expression databases, and differentially expressed genes (DEGs) were analyzed using the voom method in the limma package. The overlapping DEGs were obtained from the intersecting drug target genes using the Connectivity Map (CMap) database, and systemsDock was used for molecular docking. Gene databases were searched for gene expression profiles for complementary analysis, analysis of clinical significance, and prognosis analysis to refine the study. RESULTS From 177 cases of Wilms tumor, there were 648 upregulated genes and 342 down-regulated genes. Gene Ontology (GO) enrichment analysis showed that the identified DEGs that affected the cell cycle. After obtaining 21 candidate drugs, there were seven overlapping genes with 75 drug target genes and DEGs. Molecular docking results showed that relatively high scores were obtained when retinoic acid and the cyclin-dependent kinase inhibitor, alsterpaullone, were docked to the overlapping genes. There were significant standardized mean differences for three overlapping genes, CDK2, MAP4K4, and CRABP2. However, four upregulated overlapping genes, CDK2, MAP4K4, CRABP2, and SIRT1 had no prognostic significance. CONCLUSIONS RNA-sequencing, connectivity mapping, and molecular docking to investigate ligand-protein binding identified retinoic acid and alsterpaullone as potential drug candidates for the treatment of Wilms tumor.

SUBMITTER: Luo JY

PROVIDER: S-EPMC7119447 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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RNA-Sequencing, Connectivity Mapping, and Molecular Docking to Investigate Ligand-Protein Binding for Potential Drug Candidates for the Treatment of Wilms Tumor.

Luo Jia-Yuan JY Yan Shi-Bai SB Chen Gang G Chen Peng P Liang Song-Wu SW Xu Qiong-Qian QQ Gu Jin-Han JH Huang Zhi-Guang ZG Qin Li-Ting LT Lu Hui-Ping HP Mo Wei-Jia WJ Luo Yi-Ge YG Chen Jia-Bo JB

Medical science monitor : international medical journal of experimental and clinical research 20200326

BACKGROUND Wilms tumor, or nephroblastoma, is a malignant pediatric embryonal renal tumor that has a poor prognosis. This study aimed to use bioinformatics data, RNA-sequencing, connectivity mapping, molecular docking, and ligand-protein binding to identify potential targets for drug therapy in Wilms tumor. MATERIAL AND METHODS Wilms tumor and non-tumor samples were obtained from high throughput gene expression databases, and differentially expressed genes (DEGs) were analyzed using the voom met ...[more]

PMID: 32214060

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Project description:BackgroundDrug repositioning is a cost-efficient and time-saving process to drug development compared to traditional techniques. A systematic method to drug repositioning is to identify candidate drug's gene expression profiles on target disease models and determine how similar these profiles are to approved drugs. Databases such as the CMAP have been developed recently to help with systematic drug repositioning.MethodsTo overcome the limitation of connectivity maps on data coverage, we constructed a comprehensive in silico drug-protein connectivity map called DMAP, which contains directed drug-to-protein effects and effect scores. The drug-to-protein effect scores are compiled from all database entries between the drug and protein have been previously observed and provide a confidence measure on the quality of such drug-to-protein effects.ResultsIn DMAP, we have compiled the direct effects between 24,121 PubChem Compound ID (CID), which were mapped from 289,571 chemical entities recognized from public literature, and 5,196 reviewed Uniprot proteins. DMAP compiles a total of 438,004 chemical-to-protein effect relationships. Compared to CMAP, DMAP shows an increase of 221 folds in the number of chemicals and 1.92 fold in the number of ATC codes. Furthermore, by overlapping DMAP chemicals with the approved drugs with known indications from the TTD database and literature, we obtained 982 drugs and 622 diseases; meanwhile, we only obtained 394 drugs with known indication from CMAP. To validate the feasibility of applying new DMAP for systematic drug repositioning, we compared the performance of DMAP and the well-known CMAP database on two popular computational techniques: drug-drug-similarity-based method with leave-one-out validation and Kolmogorov-Smirnov scoring based method. In drug-drug-similarity-based method, the drug repositioning prediction using DMAP achieved an Area-Under-Curve (AUC) score of 0.82, compared with that using CMAP, AUC = 0.64. For Kolmogorov-Smirnov scoring based method, with DMAP, we were able to retrieve several drug indications which could not be retrieved using CMAP. DMAP data can be queried using the existing C2MAP server or downloaded freely at: http://bio.informatics.iupui.edu/cmapsConclusionsReliable measurements of how drug affect disease-related proteins are critical to ongoing drug development in the genome medicine era. We demonstrated that DMAP can help drug development professionals assess drug-to-protein relationship data and improve chances of success for systematic drug repositioning efforts.

Dataset Information

RNA-Sequencing, Connectivity Mapping, and Molecular Docking to Investigate Ligand-Protein Binding for Potential Drug Candidates for the Treatment of Wilms Tumor.

Publications

RNA-Sequencing, Connectivity Mapping, and Molecular Docking to Investigate Ligand-Protein Binding for Potential Drug Candidates for the Treatment of Wilms Tumor.

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