Searching for variant sequences with pinpoint accuracy
The global market for bioengineered protein drugs is expected to reach $228.4 billion by 2021, up from $172.5 billion in 2016, rising at a compound annual growth rate (CAGR) of 5.8% from 2016 through 2021, according to BCC Research.
A journal in APL Bioengineering estimated that by 2018, the global market for industrial enzymes, many of which are sequence variants, will surpass the $7.1 billion mark and its five-year CAGR will be around 8.2%.
With bioengineering and rational design come variant sequences: one or many changes made in a protein or DNA sequence in order to impart desired characteristics to the molecule being studied. A quick text search for patents related to variant proteins uncovered almost 90,000 families and 188,000 patent documents; 24,226 families and almost 40,000 documents in the last two years alone. This large amount of IP requires effective and efficient variant searching.
Using existing tools to do variation search is very difficult and labour-intensive, requiring multiple workarounds to get potentially incomplete results. Because it’s not well-understood and there is minimal training available, variation searching is not as routinely done as other forms of sequence searching. As a result, opportunities are missed and unnecessary risks are taken.
Although sequence variation searching is applicable to a broad diversity of technologies and applications, the challenges and underlying methodology have much in common.
There are two basic types of searches:
