Drug Repurposing Approach to Identify Candidate Drug Molecules for Hepatocellular Carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, with a high mortality rate due to the limited therapeutic options. Systemic drug treatments improve the patient's life expectancy by only a few months. Furthermore, the development of novel small molecule chemotherapeutics is time-consuming and costly. Drug repurposing has been a successful strategy for identifying and utilizing new therapeutic options for diseases with limited treatment options. This study aims to identify candidate drug molecules for HCC treatment through repurposing existing compounds, leveraging the machine learning tool MDeePred. The Open Targets Platform, UniProt, ChEMBL, and Expasy databases were used to create a dataset for drug target interaction (DTI) predictions by MDeePred. Enrichment an

SUBMITTER: Baser T 

PROVIDER: S-EPMC11395636 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature