Decoding protein puzzle and brilliance of algorithm accuracy

By: |
December 02, 2020 5:15 AM

AI has made significant strides in decoding proteins, with positive implications for drug delivery and design

The fourth industrial revolution will envelop us at a pace and scale that is mind-boggling. It also presents an opportunity for us as a nation, to carve out a unique development trajectory by leapfrogging technologies and stepping away from conventional models.The fourth industrial revolution will envelop us at a pace and scale that is mind-boggling. It also presents an opportunity for us as a nation, to carve out a unique development trajectory by leapfrogging technologies and stepping away from conventional models.

Google’s DeepMind algorithm’s unprecedented accuracy in decoding of protein structures—this was recently reported in Nature—will help researchers develop better medication in the future. Although scientists have been studying protein structures for long now, the complexity of some molecules and the sheer combinations involved have led to the decoding of only 170,000 proteins, from over 200 million known to humans. Understanding of the structure of complex proteins still eludes mankind. While most approaches to decode structures tend to be experimental, leaps in artificial intelligence has helped speed up the process. In 2018, when DeepMind first participated in the bi-annual competition to determine new protein structures, it scored 15% higher than everyone else and achieving a GDT—a 0-100 scale that determines the accuracy of prediction—score of 60. Other approaches, until then, had only been able to achieve scores close to 40.

However, this year, the algorithm, AlphaFold, was able to achieve a score of 92.4 for less complex structures and 87 for complex molecules. Also, given that each team has to share data on how it arrives at the calculation, this will also help other researchers tweak other techniques for better efficacy. If drug designers can isolate every protein molecule and understand its structure, it will also help deliver more drugs to the market. While AlphaFold wasn’t able to solve some protein structures, with time and training, it will be able to do that as well. For now, it is a significant achievement towards understanding drug responses.

Get live Stock Prices from BSE, NSE, US Market and latest NAV, portfolio of Mutual Funds, Check out latest IPO News, Best Performing IPOs, calculate your tax by Income Tax Calculator, know market’s Top Gainers, Top Losers & Best Equity Funds. Like us on Facebook and follow us on Twitter.

Financial Express is now on Telegram. Click here to join our channel and stay updated with the latest Biz news and updates.

Next Stories
1Government must get it right on oxygen supply
2Relieving Labour’s Pain: Larger MGNREGA allocation, social security scheme needed
3In Ceres: There’s a lot of buzz around space tourism market