Identification of small molecule inhibitors for differentially expressed miRNAs in gastric cancer

• Published in: Computational biology and chemistry Vol. 77; pp. 442 - 454
• Main Authors: Pavithra, Dhayalan, Sabitha, Kesavan, Rajkumar, Thangarajan
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.12.2018
• Subjects: Antineoplastic Agents - chemistry; Antineoplastic Agents - pharmacology; Carcinogenesis - drug effects; Carcinogenesis - genetics; Drug Discovery - methods; Enrichment analysis; Gastric cancer; Gene Expression Regulation, Neoplastic - drug effects; Humans; Meta-analysis; MicroRNAs - antagonists & inhibitors; MicroRNAs - genetics; MicroRNAs - metabolism; miRNA; Molecular Docking Simulation; Molecular Targeted Therapy; Protein Interaction Maps - drug effects; Signal Transduction - drug effects; Small molecule inhibitors; Small Molecule Libraries - chemistry; Small Molecule Libraries - pharmacology; Stomach Neoplasms - drug therapy; Stomach Neoplasms - genetics; Stomach Neoplasms - metabolism; Target prediction; Up-Regulation - drug effects; miRNA; Enrichment analysis; Small molecule inhibitors; Gastric cancer; Meta-analysis; Target prediction
• ISSN: 1476-9271; 1476-928X
• DOI: 10.1016/j.compbiolchem.2018.07.013

[Display omitted] •Differentially expressed miRNAs in gastric cancer identified by meta-analysis.•Target genes of the differentially expressed miRNAs were found to be involved in pathways of cancer.•Small molecule inhibitors for over expressed miRNAs were identified using bioinformatic methods. Gastric cancer is a common cancer in the world with higher incidence rates. Micro RNAs (miRNAs) are known to control biological processes and are also involved in the initiation and progression of numerous cancers. The aim of this study was to identify small molecule inhibitors using bioinformatics methods for over-expressed miRNAs that are known to play a major role in the genesis of gastric cancer. Our study included three datasets from Gene expression omnibus (GEO) database and we used bioinformatics tool to identify differentially expressed miRNAs in all the three datasets. Gene ontology and pathway enrichment analysis of the experimentally validated miRNA target genes and their linkage to oncogenesis were analyzed. Target genes thus identified were found to be linked with the major pathways of cancer. We were interested in identifying small molecules which are specific to over-expressed miRNAs which can arrest oncogenesis. Thus, the computer aided high throughput virtual screening was carried out to identify potent small molecules for over expressed miRNAs in gastric cancer using Glide. Based on docking score top five ligands specific for each miRNAs were identified.