A breakthrough study published in the journal Nature Chemistry has uncovered a new method for predicting drug-protein affinity. This method could potentially revolutionize the development of new drugs by helping to identify which proteins are likely to interact with a given drug.

The method, developed by researchers at the University of California, Berkeley, uses machine learning to predict drug-protein affinity from the 3D structure of the drug and the amino acid sequence of the protein. This approach could provide a powerful tool for drug discovery, as it can quickly identify promising targets in a fraction of the time of existing methods. Furthermore, it could reduce the number of failed drug candidates, saving costs and time for drug development.

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source: Phys.org