It has nearly taken hundreds of centuries to get where we are today. From the invention of the wheel to the fastest train with speed of 603 Kmph, from the discovery of fire to landing on the moon, all the technological advances that you use in everyday life, unnoticed, is the result of enthusiastic effort and genius of the great legacy. Artificial intelligence is certainly is the next giant step in that series, the rate of technological advancement would be ever high! Following the one such initiative:
- DeepMind is the world leader in artificial intelligence research and its application for positive impact on the world.
- DeepMind was founded in London and backed by some of the most successful technology entrepreneurs in the world and have been acquired by Google in 2014.
- DeepMind, an AI lab is the complete outsider to the field of molecular biology, beat top pharmaceutical companies like Novartis, Pfizer, etc. at predicting protein structures.
- DeepMind has brought together experts from fields if structural biology, physics, machine learning to apply cutting edge techniques to predict the 3D structure of a protein based on its genetic sequence.
- DeepMind Alpha Fold is the system which uses vast genomic data to predict protein structure.
- CASP (Critical assessment of structure prediction) is a virtual protein folding Olympics, where the aim is to predict the 3D structure of the protein based on its genetic sequence data.
- DeepMind has won the CASP13 protein folding competition.
- Alpha Fold scores 127.99 was 20 points higher than the second-ranked team, achieving what CASP called “unprecedented progress in the ability of computational methods to predict protein structure”.
What is protein folding problem?
Proteins are our bodies building blocks and perform a vast array of essential functions.
A protein molecule is made of a string of smaller components called amino acids, which fold into the molecule’s 3D shape. The protein folding problem involves determining how the string of amino acids encodes the 3D shape of a protein molecule. This can produce a better understanding of proteins and enable scientists to change their function for the good of our bodies. For example in treating diseases caused by misfolded proteins, such as Alzheimer’s, Parkinson’s, Huntington’s and cystic fibrosis.
The protein folding problem is regarded as one of the grandest biochemistry challenges of the last 50 years. Current approaches include using algorithms to compute the 3D structure of proteins with amino acids sequence data, or using X-ray crystallography and other techniques to image a protein structure.
The DeepMind’s approach:
- DeepMind researchers used deep neural network to learn the correlation between the shape of a protein molecule and its amino acid sequence.
- The physical properties of a protein molecule include the distance between pairs of amino acids and the angles between chemical bonds that connect those amino acids.
- The model came up with a score that estimates the accuracy of a proposed protein structure, then used gradient descent a common deep learning algorithm that finds the minimum of a function to optimize that score.
- DeepMind has been working on protein folding for two years and has significantly advanced the development of protein engineering.
Thanks for reading.
BY- AJAY KUMAR RACHURI (3rd year EC )
CHEERS, TEAM CEV.
