Back to News

AI-Designed Drugs Can Target 'Undruggable' Proteins in Cancer and Alzheimer's

Hacker News - AI
Jul 22, 2025 16:58
Brajeshwar
1 views
hackernewsaidiscussion

Summary

AI-driven drug discovery is enabling the design of molecules that can target previously "undruggable" proteins involved in diseases like cancer and Alzheimer's. This breakthrough expands the range of treatable conditions and demonstrates AI's transformative potential in accelerating and broadening pharmaceutical innovation.

Article URL: https://singularityhub.com/2025/07/21/ai-designed-drugs-can-now-target-previously-undruggable-proteins-in-cancer-and-alzheimers/ Comments URL: https://news.ycombinator.com/item?id=44649968 Points: 1 # Comments: 0
Read Full ArticleMore News

Related Articles

AI Coding Agents Are Removing Programming Language Barriers

Hacker News - AIJul 23

AI coding agents are increasingly capable of translating high-level instructions into code across multiple programming languages, reducing the need for developers to master specific languages. This advancement lowers barriers to entry in software development and could accelerate innovation by making programming more accessible to a broader audience. The trend highlights AI's growing role in automating complex technical tasks and reshaping the future of coding.

Show HN: Paradigm – Run any AI model locally with a single .exe

Hacker News - AIJul 23

Paradigm is a new Windows-focused desktop tool that enables users to run any Hugging Face AI model locally, supporting both text and audio models with GPU or CPU fallback for lower-end devices. By allowing users to bring their own models and aiming for broad compatibility, Paradigm seeks to become a universal platform for efficient local AI inference, potentially increasing accessibility and privacy in AI model deployment.

Cheaper AI does not mean greener AI

Hacker News - AIJul 23

The article argues that while advancements are making AI models cheaper to train and deploy, this does not necessarily lead to lower environmental impact. Lower costs can drive increased usage and proliferation of AI applications, potentially resulting in greater overall energy consumption and carbon emissions, highlighting the need for sustainable AI practices beyond just cost reduction.