Abstract
Prostate cancer (PCa) is one of the leading cancers in men and the lack of suitable biomarkers or their modulators results in poor prognosis. Membrane proteins (MPs) have a crucial role in the development and progression of PCa and can be attractive therapeutic targets. However, experimental limitations in targeting MPs hinder effective biomarker and inhibitor discovery. To overcome this barrier, computational methods can yield structural insights and screen large libraries of compounds, accelerating lead identification and optimization. In this review, we examine current breakthroughs in computer-aided drug design (CADD), with emphasis on structure-based approaches targeting the most relevant membrane-bound PCa biomarkers.
| Original language | English |
|---|---|
| Article number | 104130 |
| Journal | Drug Discovery Today |
| Volume | 29 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Sept 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- biomarkers
- computer-aided drug design
- membrane proteins
- prostate cancer
- structure-based drug design
- virtual screening
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