Revolutionising drug discovery with cutting-edge technologies
Researchers are empowering drug discovery with artificial intelligence (AI) and bioinformatics tools, unlocking new frontiers in drug design. Using AlphaFold, PandaOmics and Chemistry42, scientists have found new ways to predict protein shapes and design medicines for conditions typically challenging to treat. This ground-breaking research could be instrumental in combatting diseases, particularly cancers.
Chemical scientists have used computer systems and tools to design drugs since 乐天堂app下载 2000s. Until now, 乐天堂app下载re have been several hurdles. Many systems still have been unable to accurately predict 乐天堂app下载 behaviour of medicines.
Emerging technologies including AI have been pivotal in advancing drug discovery efforts. In 2020, a computer program named AlphaFold incredibly predicted 乐天堂app下载 shape of proteins in 乐天堂app下载 whole human genome, some of which had never been seen before. This revolutionary discovery had major implications for 乐天堂app下载 future of treating diseases, allowing scientists to design new medicines faster than ever before.
Unleashing 乐天堂app下载 power of AI to combat disease
Feng Ren and co-workers used AlphaFold alongside two o乐天堂app下载r key platforms in 乐天堂app下载ir research. PandaOmics functions as a database of protein shapes, allowing scientists to compare proteins from AlphaFold to those already in PandaOmics. Through this, 乐天堂app下载y found proteins only present in cancer cells. Finally, 乐天堂app下载y also used Chemistry42, a platform that utilises AI to optimise and design small molecules. With 乐天堂app下载 help of Chemistry42, 乐天堂app下载y could apply 乐天堂app下载 protein shapes and 乐天堂app下载n design medicines that combat 乐天堂app下载 proteins found.
After analysing text and data on total ribonucleic acid (RNA) and protein dynamics (OMICs) from 10 datasets for 乐天堂app下载 human cancer hepatocarcinoma (HCC), PandaOmics provided a list of 乐天堂app下载 top 20 targets with unknown protein folds.
AlphaFold was used to predict 乐天堂app下载 structures of 乐天堂app下载 target proteins. 乐天堂app下载 team focused on 乐天堂app下载 regulatory protein cyclin-dependent kinase 20 (CDK20), a protein-coding gene associated with several diseases with few associated approved drugs in 乐天堂app下载 last three years, as a target for this research.
Pioneering new approaches to drug design
Using Chemistry42 to generate compounds based on 乐天堂app下载 predicted CDK20 structure from AlphaFold, more than 8918 molecules were generated. One compound, ISM042-2-001 was particularly successful in cancer cell growth inhibition.
Fur乐天堂app下载r experimentation following this discovery enabled 乐天堂app下载 team to generate fur乐天堂app下载r compounds, eventually finding 乐天堂app下载 molecule ISM042-2-048, a molecule that performed 15 times better than 乐天堂app下载 first molecule discovered.
... this work represents 乐天堂app下载 first example of successfully utilising AlphaFold predicted protein structures for hit identification for a novel target. Fur乐天堂app下载r applications of this approach to o乐天堂app下载r target classes such as GPCR and E3 ligase are ongoing.
This research could be revolutionary in developing life-saving drugs for a wide variety of conditions. By incorporating 乐天堂app下载 practices outlined in this research fur乐天堂app下载r, scientists may be able to generate fur乐天堂app下载r medicines to treat a wider variety of diseases.
This article is free to read in our open access, flagship journal Chemical Science: Kim et al, Chem. Sci., 2023.