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'Once in a generation advance' as Google AI researchers crack a 50-year-old biological challenge.

Wednesday, December 2, 2020

'Once in a generation advance' as Google AI (artificial intelligence) researchers crack a 50-year-old biological challenge.

Every now and then a genuinely exciting ‘game changing’ breakthrough is made. This last week of November it has been revealed that a ‘once in a generation advance’ has been made. In this breakthrough, Google AI (artificial intelligence) has helped researchers crack a 50year old biological challenge that could ‘significantly’ accelerate drug development for many diseases like cancer and perhaps kidney (renal) illness.

'Once in a generation advance' as Google AI (artificial intelligence) researchers crack a 50-year-old biological challenge.

In what has been a hugely difficult year for so many with Covid-19 touching virtually every country on our planet and impacting all of our lives, we have heard of the many negative effects on medical research that this will cause. However, exciting research in renal research continues. It is also exciting and encouraging to see what can happen and be achieved when scientists are fully funded and there is a common aim and so in a dramatic time frame we have a number of Covid-19 vaccines developed promising great hope for our world.

Every now and then a genuinely exciting ‘game changing’ breakthrough is made. This last week of November it has been revealed that a ‘once in a generation advance’ has been made. In this breakthrough, Google AI (artificial intelligence) has helped researchers crack a 50year old biological challenge that could ‘significantly’ accelerate drug development for many diseases like cancer and perhaps kidney (renal) illness.

A three-dimensional digital rendering of a protein - The 50-year-old "protein folding problem" has been cracked by artificial intelligence created in the UK by Google-owned AI lab DeepMind based in London in their AlphaFold programme, paving the way for faster development of treatments and drug discoveries.

The so-called "protein folding problem" has long been one of biology's biggest hurdles, as researchers have sought to predict the shape of proteins to understand how they perform specific tasks in the body. Proteins start off in a cell as a long chain and then fold upon themselves into a 3D shape in order to perform their biological function, however sometimes this folding process fails, which can impact the health of the cell or cause other misfolded proteins to clump together. This failure can cause several known diseases. There are 200 million known proteins at present but only a fraction have been “unfolded” to fully understand what they do and how they work. This new system is able to determine “unparalleled levels of accuracy” in the structures in a matter of days.

"Proteins are extremely complicated molecules, and their precise three-dimensional structure is key to the many roles they perform. The discovery could change the way we approach biology, the researchers said, by speeding up drug development for certain diseases and "opening up new avenues of exploration".

Arthur Levinson, founder and CEO Calico, said: “AlphaFold is a once in a generation advance, predicting protein structures with incredible speed and precision. "This leap forward demonstrates how computational methods are poised to transform research in biology and hold much promise for accelerating the drug discovery process.” But researchers behind the project say there is still more work to be done, including figuring out how multiple proteins form complexes and how they interact with DNA.

So how might this breakthrough help with research in Nephrotic Syndome?

NeST trustee and senior scientist at Bristol Research Laboratories, Dr Gavin Welsh writes: ‘This research is very interesting. Understanding how proteins fold and how this changes in disease, is critical in medical research and especially developing new drugs. More work needs to be done on this to validate the findings but hopefully this work will lead to new ways of quickly identifying structural changes in proteins and potential drug binding sites which may modify disease causing mutations’.

So, this in more good news potentially in our battle to find a cure and therapies for NS.

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