3-D View of Mutations May Identify Potential Targets for Cancer Drugs
The HotSpot3D computational tool models how gene mutations (shown as bubble-shaped clusters) may affect the structure of proteins (spiral-shaped ribbons) as well as how those proteins may interact with a drug. Credit: Washington University in St. Louis / Li Ding, Ph.D., and Feng Chen, Ph.D.
A new computational tool may help expand the known number of mutations in cancer cells that could be targeted with new or existing drugs.
Researchers recently reported that the tool, called HotSpot3D, allowed them to model how genetic mutations change the ways proteins function and interact with each other to potentially drive cancer. It also helped them identify more than 800 novel mutations that potentially could be targeted with existing drugs.
The research team that developed HotSpot3D, led by Li Ding, Ph.D., and Feng Chen, Ph.D., of Washington University in St. Louis, published results from this first large-scale testing of the computational tool June 13 in Nature Genetics.
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