UK scientists create map of licensed drugs to search for future treatments
UK-based scientists at the Institute of Cancer Research (ICR) have created a map of all 1,578 licensed drugs and their mechanisms of action to identify ‘uncharted waters’ in the search for future treatments.
Licensed through the Food and Drug Administration (FDA), the analysis of drugs found that 667 separate proteins in the human body have had drugs developed against them, which represents an estimated 3.5% of the 20,000 human proteins.
So far, as many as 70% of all targeted drugs have been created and operate by acting on just four families of proteins.
The study analyses existing drug treatments across all diseases.
The new map reveals areas where human genes and the proteins they encode could be promising targets for new treatments. It can be used to identify other proteins with similar properties to the most heavily drugged families.
ICR data science head Dr Bissan Al-Lazikani said: “Our new study provides a comprehensive map of the current state of medicines for human disease.
“It identifies areas where drug discovery has been a spectacular success, others where there are major gaps in our armoury of medicines, and opportunities for the future in the form of promising targets and potential drug combinations.”
Scientists said that the new data could be used to improve treatments for all human aliments as diverse as cancer, mental illness, chronic pain and infectious disease.
They obtained information from the canSAR database at ICR, the ChEMBL database from the European Bioinformatics Institute (EMBL-EBI) in Cambridge and the University of New Mexico’s DrugCentral database.
By matching each drug with prescribing information and data from published scientific papers, the scientists built up a picture of how existing medicines work.
Subsequently they discovered that there are 667 unique human proteins targeted by existing approved drugs, and identified a further 189 drug targets in organisms that are dangerous to humans.
The researchers used complex ‘big data’ analytical techniques to identify four very frequently ‘drugged’ families of proteins accounting for 43% of all drug targets, and acting as targets for 70% of all approved small-molecular drugs.