As artificial intelligence becomes ever more powerful the fear of whether it will be a tool for good or evil, or even whether it will replace us, becomes increasingly important.
Every two years a group of
The Importance of Knowing a Protein’s Structure
Proteins are biological molecules composed of amino acid subunits. They can range in size from
When the first protein structure was determined by Max Perutz and John Kendrew in the late 1950s, the scientific community was dismayed. In comparison to the elegant simplicity of the structure of DNA, determined x years earlier, it seemed ugly and chaotic. Since that time, however, scientists have discovered that protein structures have their own elegance hidden within the jumble of coils, sheets, and strands of amino acids.
Knowing a protein’s 3-dimensional structure is important for understanding how it carries out its function and for how we might develop pharmaceuticals for biological issues that might involve that protein. Determining a protein’s fold and thereby a more complete understanding of its function is also an interesting endeavour in its own right.
At CASP 2018, challengers were given the amino acid sequences of 90 proteins for which the structures were known but not yet published. In the case of 43 of these proteins, only the amino acid sequence was known (in addition to the unpublished structure). That means things like function or protein classification could not be used to aid the structure determination (certain protein folds are common motifs in certain classifications of proteins). Of those 43 ‘unknown’ proteins, AlphaFold was more accurate in predicting their structure than the competition 25 times. The next best challengers won in only 3 cases.
For an insider’s look at the recent CASP challenge and detailed thoughts on
thesignificance, I recommend a read of M. AlQuraishi’s blog article.
While AlphaFold used computational techniques that have been well-known for some time, because of its nature and the massive hardware investment behind it, its machine-learning algorithms could be trained on vastly larger data sets than ever before. This success has led some to question everything from are scientists obsolete
As with the increasing number of fields where AI is succeeding, the initial shock of many specialists leads to a re-evaluation of what they thought they knew both about themselves, about their field, and about human potential in this technological world (and also their job security). Eventually, however, those who are not too discourages allow their thoughts to settle and come to the realisation that this is just another, albeit very amazing and powerful, tool we’ve developed. And, if harnessed well, it can allow us to do amazing new things.