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Researchers have updated the canSAR database, a tool designed to aid cancer drug discovery, by adding 3D structures of faulty proteins and maps of cancer’s communication networks.
The canSAR database brings together biological, chemical, and pharmacological data.
The goal of the database is to make these data accessible to researchers worldwide to help with hypothesis generation and support drug discovery decisions.
Users can search canSAR using text queries, protein/gene name searches, any keyword searches, chemical structure searches, and sequence similarity searches. Users can also explore and filter chemical compound sets, view experimental data, and produce summary plots.
The canSAR database was 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.
The database has already collated billions of experimental measurements, mapping the actions of 1 million drugs and chemicals on human proteins, and it has combined these data with genetic information and results from clinical trials.
The updated version of canSAR uses artificial intelligence to identify nooks and crannies on the surface of faulty cancer-causing molecules as a key step in designing new drugs to block them. It also allows researchers to identify communication lines that can be intercepted within tumor cells, opening up potential new approaches for cancer treatment.
The growing database now holds the 3D structures of almost 3 million cavities on the surface of nearly 110,000 molecules.
“Our database is constantly growing with information and is the largest of its kind, with more than 140,000 users from over 175 countries,” said Bissan Al-Lazikani, PhD, of The Institute of Cancer Research in London, UK.
“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.”
“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.”
Details on the updates to canSAR have been published in Nucleic Acid Research. The database is available online at https://cansar.icr.ac.uk/. 
Photo by Rhoda Baer
Researchers have updated the canSAR database, a tool designed to aid cancer drug discovery, by adding 3D structures of faulty proteins and maps of cancer’s communication networks.
The canSAR database brings together biological, chemical, and pharmacological data.
The goal of the database is to make these data accessible to researchers worldwide to help with hypothesis generation and support drug discovery decisions.
Users can search canSAR using text queries, protein/gene name searches, any keyword searches, chemical structure searches, and sequence similarity searches. Users can also explore and filter chemical compound sets, view experimental data, and produce summary plots.
The canSAR database was 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.
The database has already collated billions of experimental measurements, mapping the actions of 1 million drugs and chemicals on human proteins, and it has combined these data with genetic information and results from clinical trials.
The updated version of canSAR uses artificial intelligence to identify nooks and crannies on the surface of faulty cancer-causing molecules as a key step in designing new drugs to block them. It also allows researchers to identify communication lines that can be intercepted within tumor cells, opening up potential new approaches for cancer treatment.
The growing database now holds the 3D structures of almost 3 million cavities on the surface of nearly 110,000 molecules.
“Our database is constantly growing with information and is the largest of its kind, with more than 140,000 users from over 175 countries,” said Bissan Al-Lazikani, PhD, of The Institute of Cancer Research in London, UK.
“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.”
“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.”
Details on the updates to canSAR have been published in Nucleic Acid Research. The database is available online at https://cansar.icr.ac.uk/.
Photo by Rhoda Baer
Researchers have updated the canSAR database, a tool designed to aid cancer drug discovery, by adding 3D structures of faulty proteins and maps of cancer’s communication networks.
The canSAR database brings together biological, chemical, and pharmacological data.
The goal of the database is to make these data accessible to researchers worldwide to help with hypothesis generation and support drug discovery decisions.
Users can search canSAR using text queries, protein/gene name searches, any keyword searches, chemical structure searches, and sequence similarity searches. Users can also explore and filter chemical compound sets, view experimental data, and produce summary plots.
The canSAR database was 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.
The database has already collated billions of experimental measurements, mapping the actions of 1 million drugs and chemicals on human proteins, and it has combined these data with genetic information and results from clinical trials.
The updated version of canSAR uses artificial intelligence to identify nooks and crannies on the surface of faulty cancer-causing molecules as a key step in designing new drugs to block them. It also allows researchers to identify communication lines that can be intercepted within tumor cells, opening up potential new approaches for cancer treatment.
The growing database now holds the 3D structures of almost 3 million cavities on the surface of nearly 110,000 molecules.
“Our database is constantly growing with information and is the largest of its kind, with more than 140,000 users from over 175 countries,” said Bissan Al-Lazikani, PhD, of The Institute of Cancer Research in London, UK.
“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.”
“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.”
Details on the updates to canSAR have been published in Nucleic Acid Research. The database is available online at https://cansar.icr.ac.uk/.