Target screening and optimization of candidate compounds for breast cancer treatment using bioinformatics and computational chemistry approaches.

ABSTRACT:

Objectives

This study aimed to identify critical therapeutic targets and design potent antitumor compounds for breast cancer treatment through an integrated bioinformatics and computational chemistry approach.

Methods

We conducted initial screening and target intersection analysis to identify potential protein targets, highlighting the adenosine A1 receptor as a key candidate. Molecular docking and molecular dynamics (MD) simulations were performed to evaluate the binding stability between selected compounds and the human adenosine A1 receptor-Gi2 protein complex (PDB ID: 7LD3). A pharmacophore model was constructed based on binding information to guide the virtual screening of additional compounds with activity. Furthermore, we designed and synthesized a novel molecule base

SUBMITTER: Xu J 

PROVIDER: S-EPMC12098522 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature