The convergence of AI and structural biology is revolutionising how researchers investigate complex biological and biomedical problems. By applying these techniques to their research, scientists are closer to developing novel therapeutic strategies and preventative measures. While AI offers an immense acceleration to the generation of hypotheses and models, it should not be seen as a replacement for traditional experimental techniques and the valuable insight that they bring.
NB. My research (MRes and PhD) at Imperial College London during 2012 to 2021 centred around protein crystallisation methodologies and x-ray crystallography, which aided 3-D protein structures determination. Data and information gained from crystallography is vital to the success of rational drug design and medicinal therapeutics and biotechnological applications. If AlphaFold existed in its current form during parts of my research period, I'm positive it would have helped accelerate the painstaking research we conducted and potentially helped boost our findings and results. Selected research below:
https://www.nature.com/articles/srep20053; https://journals.iucr.org/m/issues/2021/04/00/mf5053/index.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC2670972/; https://deepmind.google/technologies/alphafold/; https://www.nature.com/articles/s41586-021-03819-2; https://www.nature.com/articles/s41592-023-02087-4
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