Machine learning can quickly and precisely evaluate binding free energy used in drug discovery, according to a March 15 study published in The Journal of Physical Chemistry Letters.
The new machine learning tool, known as DeepBAR, was discovered by Xinqiang Ding, PhD, and Bin Zhang, PhD, researchers from the Massachusetts Institute of Technology in Cambridge.
Drugs are only effective if they stick to their target proteins in the body, which can slow down drug discovery. Existing techniques struggle to balance efficiency and accuracy, researchers said.
DeepBAR can accelerate the process because it is much quicker than other methods currently available.
The machine learning tool is also exact and does not make estimations like other tools.
It is anticipated to be a valuable tool for computing standard binding free energy used in drug design, the study’s authors said.
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