...The response of experts in the field of protein folding was widely very positive, although it was acknowledged that a full analysis of the new AlphaFold2 AI approach must await formal peer review and publication – as duly occurred with the
earlier version of AlphaFold – and some commentators pointed out the current inevitable limitations.
A
news piece in the leading journal Science quoted the expert computational protein scientist
Janet Thornton as saying, ‘What the DeepMind team has managed to achieve is fantastic and will change the future of structural biology and protein research.’ The
Science report also quotes the Nobel Prize-winning structural biologist
Venki Ramakrishnan, who described the work as ‘a stunning advance on the protein folding problem’.
Similarly, in a
Nature news piece the computational biologist and co-founder of CASP
John Moult said: ‘This is a big deal. In some sense the problem is solved.’ And the same news article also quotes
Andrei Lupas, who studies protein evolution, as saying: ‘This will change everything’. Not surprisingly Lupas was impressed that AlphaFold enabled him to determine in half an hour the structure of a protein that he’d failed to solve for 10 years!
.....
The co-founder and CEO of DeepMind – and also last author on the two
Nature papers –
Demis Hassabis told
Fortune magazine that the publication of AlphaFold’s structure predictions was his company’s ‘biggest contribution to science to date [and] an example of the benefits AI can bring to society’. See more comments from Hassabis
in his recent blog post.
Fortune also quoted very positive views from
Elizabeth Blackburn (University of California San Francisco),
Paul Nurse (Francis Crick Institute) and
Ewan Birney (EMBL-EBI). These biomedical research leaders and many others have praised AlphaFold’s accurate and large-scale protein prediction capability, with many seeing it as the biggest breakthrough since the determination of the human genome sequence around 20 years ago – and arguably similar in scale and impact.
A
Nature editorial last month reported a consensus view that ‘it’s too early to predict exactly what impact the application of AI in the life sciences will have, except that any impact will be transformative.’