Of all the technologies we cover, those that fall under “life sciences” are least likely to get our researchers motivated. That’s because these domains are extremely complex. But here’s the real problem. Even if you’re a subject matter expert in any particular life sciences theme, you’ll still be unable to gauge a successful investment because the life sciences community ultimately decides with their wallets. What might be perceived as the greatest product since sliced bread may not demonstrate traction for any number of reasons. Drug discovery stocks are the epitome of unforeseen risks because this sector is also highly regulated. Someone dies on your watch and all hell breaks loose.
The Proteomics Thesis in a Nutshell
Here’s a simple life sciences thesis for you which starts with recognizing how important proteins are in life sciences.
Proteins are among the most abundant organic molecules in living systems and are way more diverse in structure and function than other classes of macromolecules. A single cell can contain thousands of proteins, each with a unique function. Although their structures, like their functions, vary greatly, all proteins are made up of one or more chains of amino acids.
Khan Academy
The study of proteins is called proteomics. Why is proteomics suddenly so relevant? Glad you asked Little Johnny. You see, there’s this new technology few people have heard of called “generative AI,” and a year ago it was used to solve one of the greatest challenges in biology. A generative AI beast known as Alphafold (built by Google’s DeepMind) figured out how nearly all proteins are folded.
