🧬 Exciting News from McGowan! 🧬
Did you know? Only a tiny fraction of known small molecules have been studied for their impact on microRNA (miRNA) function—yet these tiny RNA strands play a key role in diseases from cancer to cardiovascular disorders. 💡💊
Now, a researcher from McGowan, Dr. Afshin Beheshti, has been involved in developing  sChemNET, a deep learning framework that predicts small molecules capable of targeting miRNAs. This innovation can screen vast chemical libraries to identify potential therapeutic molecules, even for rare or previously unexplored miRNA targets, offering a powerful tool in drug discovery for complex diseases. 🎯
🔍 How does it work? Using sChemNET, researchers can now predict which small molecules may modulate specific miRNAs involved in disease, allowing for precise targeting of cellular pathways linked to health conditions like cancer or metabolic disorders. This predictive model overcomes data limitations by using extensive chemical structure information to anticipate interactions even for untested compounds. 🚀
With further refinement, sChemNET could be instrumental in the rapid repurposing of existing drugs for new therapeutic applications. This approach could pave the way for more personalized treatments for diseases where miRNAs play a critical role, supporting faster and more targeted drug development.🌟
#McGowanResearch #sChemNET #miRNATherapies #DrugDiscovery #Innovation #Pittspace