World's Largest Database Boosts Cancer Drug Discovery Through 3D Structures - HPC ASIA
News

World’s Largest Database Boosts Cancer Drug Discovery Through 3D Structures

Cancer

“Cancer scientists will be armed with the data they need to carry out life-saving research into the most exciting drugs of the future.” The addition of 3D structures to healthcare data standards for cancer drug discovery will bring a big data approach to the development of new treatments, according to authors of a newly published journal article.

Scientists add 3D detail to the world’s largest cancer drug discovery database. Scientists from London’s Institute of Cancer Research (ICR) describe the update to canSAR — touted as the world’s largest database for cancer drug discovery — in the January issue of Nucleic Acids Research. They write that the database has been “revolutionized by adding 3D structures of faulty proteins and maps of cancer’s communication networks.

The database has already collated billions of experimental measurements mapping the actions of one million drugs and chemicals on human proteins, and has combined these data with genetic information and results from clinical trials, researchers said.

It allows scientists to identify communication lines that can be intercepted within tumour cells, opening up potential new approaches for cancer treatment. The growing database now holds the 3D structures of almost three million cavities on the surface of nearly 110,000 molecules.

Dr. Al-Lazikani explains why the resource is so useful:

“Scientists need to find all the information there is about a faulty gene or protein to understand whether a new drug might work. These data are vast and scattered, but the canSAR database brings them together and adds value by identifying hidden links and presenting the key information easily.”

Users can search canSAR using text queries, protein/gene name searches, keyword searches, chemical structure searches and sequence similarity searches. Additionally, users can explore and filter chemical compound sets, view experimental data and produce summary plots.

Comments

comments

Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>

To Top
error: Content is protected !!
/body /html