EVALUATING MOLECULAR TARGETS FOR DRUG REPURPOSING IN ACUTE MYELOID LEUKEMIA: AN INTEGRATIVE BIOINFORMATICS AND NETWORK PHARMACOLOGY STUDY

Abstract

Acute myeloid leukemia (AML) is a biologically heterogeneous hematological malignancy characterized by diverse genomic, epigenomic, transcriptional, and cellular abnormalities that contribute to differences in disease progression, treatment response, relapse, and survival. Although molecular classification has enabled targeted therapies for selected AML subgroups, substantial challenges remain, particularly among patients with adverse-risk disease, treatment resistance, or limited access to newer therapies. This article proposes an integrative bioinformatics and network-pharmacology framework for identifying molecularly relevant therapeutic targets and repurposable drugs in AML. The proposed approach integrates publicly available genomic and transcriptomic resources with differential-expression analysis, functional and pathway enrichment, protein–protein interaction networks, drug–target databases, perturbational transcriptomics, and clinical evidence. The workflow involves data preprocessing, identification of disease-associated molecular signatures, pathway analysis, hub-target prioritization, drug–target mapping, and computational assessment of candidate compounds. Because no AML dataset or completed computational analysis was provided, numerical findings are not reported. Instead, the framework is designed to generate biologically coherent and testable therapeutic hypotheses. Candidate compounds identified through convergent evidence should subsequently undergo experimental, pharmacological, and clinical validation. Integrating multiple molecular and pharmacological evidence layers may support systematic AML drug repurposing while reducing reliance on isolated molecular targets and facilitating translational research.