Ontology highlight
ABSTRACT: Background/objectives
Human epidermal growth factor receptor 2 (HER2) is overexpressed in several malignancies, such as breast, gastric, ovarian, and lung cancers, where it promotes aggressive tumor proliferation and unfavorable prognosis. Targeting HER2 has thus emerged as a crucial therapeutic strategy, particularly for HER2-positive malignancies. The present study focusses on the design and optimization of peptide inhibitors targeting HER2, utilizing machine learning to identify and enhance peptide candidates with elevated binding affinities. The aim is to provide novel therapeutic options for malignancies linked to HER2 overexpression.Methods
This study started with the extraction and structural examination of the HER2 protein, succeeded by designing the peptide sequenc
SUBMITTER: Alkhatabi HA
PROVIDER: S-EPMC11639795 | biostudies-literature | 2024 Nov
REPOSITORIES: biostudies-literature