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Big Data Approach to Cancer Drug Discovery Adds 3D Details

"Cancer scientists will be armed with the data they need to carry out life-saving research into the most exciting drugs of the future."

By Frank Irving

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 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.

Launched in 2011 with the goal of using big data approaches to build a detailed picture of how the majority of known human molecules behave, has collated billions of experimental measurements mapping the actions of one million drugs and chemicals on human proteins. It has combined those data with genetic information and results from clinical trials.

The new version of canSAR uses artificial intelligence to identify “nooks and crannies” on the surface of faulty cancer-causing molecules, revealing new information that can be used to design new cancer-fighting drugs. In particular, it helps researchers identify communication lines that can be intercepted within tumor cells.

canSAR now holds the 3D structures of almost 3 million cavities on the surface of nearly 110,000 molecules. The resource is free to use by researchers around the world.

Corresponding author Bissan Al-Lazikani, team leader in computational biology at ICR who also led the development of canSAR, commented in a public statement:

"Our database is constantly growing with information and is the largest of its kind — with more than 140,000 users from over 175 countries. And we regularly develop new artificial intelligence technologies that help scientists make predictions and design experiments. Our aim is that cancer scientists will be armed with the data they need to carry out life-saving research into the most exciting drugs of the future.”

Al-Lazikani added that information about faulty genes or proteins could help scientists understand whether a new drug might work. canSAR brings together such scattered data and “adds value by identifying hidden links and presenting key information easily,” according to Al-Lazikani

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.

Paul Workman, chief executive of ICR and a Cancer Research UK Life Fellow, said: "The canSAR database is an important part of the overall drive to use big data approaches to understand and treat cancer more effectively. canSAR is a massively powerful resource that's used globally by researchers to gain rapid and easy to use access to a huge wealth of integrated knowledge in biology, chemistry and cancer medicine. This latest research has greatly enhanced the power of canSAR to enable scientists to select the best possible targets for future cancer drug discovery and also to help them develop really innovative drugs much more rapidly and effectively than ever before for the benefit of cancer patients worldwide."

The canSAR database is available here.





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