Dr Bela Stantic, a senior lecturer from the School of Information and Communication Technology, has been working on computational modelling of protein structures which play important roles in cancer cell apoptosis (the process of programmed cell death that occurs in multicellular organisms).
Using this model as part of an interdisciplinary collaboration with the Griffith School of Medical Science, Dr Stantic is using innovative modelling which uses genetic algorithm feature-based resampling and machine learning techniques for protein structure prediction.
“It is very costly and time consuming to experimentally identify 3D structures of proteins using physical methods such as X-ray crystallography or NMR spectroscopy,” said Dr
“Both these methods require a sample of the protein of interest to work on and that means a long process of identification of the sequence, cloning, expression and purification of the protein. Our computational modelling overcomes these problems and now is at a stage where it can produce a good indication of which structures are useful and should be recommended for further investigation in the laboratory.”
Currently the Griffith Health Institute is using Dr Stantic’s methodology in a bid to target cancer cells using anti-cancer agents that have the capacity to induce apoptosis.
Professor Jiri Neuzil from the School of Medical Science and Griffith Health Institute said: “This computational modelling and experimental research present two very different approaches married together for a better outcome.
“It allows us to obtain a theoretical evaluation of the protein and to design a drug that can have its biological characteristics confirmed more easily following modelling. We can then take it further in being able to both understand the drug’s mode of action and get a direction on its target.”
Professor Neuzil said he has so far seen some encouraging drug development targeting cancers including breast cancer and mesothelioma.