Nature

An interaction-derived graph learning framework for scoring protein–peptide complexes

Accurate prediction of protein–peptide interactions is critical for peptide drug discovery. However, due to the limited number of protein–peptide structures in the Protein Data Bank, it is challenging ...
Nature

Integrating machine learning and protein–ligand interaction profiling for the discovery ...

RNA modifications are essential for regulating gene expression and cellular functions, influencing various biological processes, and governing non-coding RNAs 1, including tRNAs, rRNAs, and microRNAs.
Phys.org

Machine learning method improves accuracy of inverse protein folding for drug design

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...
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Machine learning method improves accuracy of inverse protein folding for drug design

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. In their study published in the journal ...