Predicting The Protein Structures Using AI
By: Vishnu Aravindhan
Tags: AI, Artificial Intelligence, Health, Protein, Science

Proteins are found essentially in all organisms, and they are basically a sequence of amino acids that are arranged in a particular structure. For many decades, scientists have been able to accurately compute the sequence of amino acids, but however, accurately predicting the structure of the protein has always been a challenging task. If we are able to decode the sequence of the amino acids in the protein structure and accurately determine the structure of the protein, then it will serve a number of functions.

Accurate prediction of protein structure will be very helpful in understanding the biological evolution of that particular protein and it will also help us understand the kind of diseases it can cause and the kind of defense it can provide against other diseases.

Essentially, accurate prediction of the structure of the protein is the key to understand the function of proteins and cells and as well as to understand how they can malfunction and cause diseases and this understanding could also be very helpful in the development of treatment and vaccines.

Now, if you look at the SARS-CoV-2, it is the spike protein structure of the Virus that latches onto the AS2 receptor in our cells, thereby leading to the occurrence of the infection. We have been able to develop this understanding quite quickly, mainly because of the progress that we have made with regard to our understanding and prediction of protein structures.

First Discovery

See, this field began evolving many decades ago, and back in 1972, a scientist known as Christian B. Anfinsen predicted that by accurately computing the sequence of amino acids, we will be able to deduce the protein structure. So this discovery won him the Nobel Prize for chemistry and it laid the foundation for analysis and prediction of protein structures.

X-ray Crystallography

Then nearly 60 years ago a scientist known as Max Perutz started to predict protein structures by using experiments. He made use of X-ray crystallography to determine the exact structure of myoglobin and hemoglobin and it was this discovery that helped us understand the true function of hemoglobin in the blood, which is to transport oxygen from the lungs to the tissues and cells. This understanding of the structure of myoglobin and hemoglobin also helped us understand how a change in a single amino acid can cause diseases such as sickle cell anemia.

Genome Sequencing

Today, decoding the sequence of amino acids and accurately completing the sequence has become more advanced, thanks to the progress achieved in genome sequencing. Because at the end of the day, the protein structures in the amino acids are essentially a part of the genome itself and the rapid advances we have made in genome sequencing have helped us to easily compute the sequence of amino acids. But however, when it comes to creating a 3D structure of the protein, these experimental techniques such as X-ray crystallography, nuclear magnetic resonance, etc., can be quite ineffective and they’re also very time consuming and expensive.

India’s Contribution

When it comes to the field of protein structural work. Even India is a leading country because an Indian scientist known as GN Ramachandran developed the Ramachandran plot, which today has become the model for scientists around the world to understand the structure of proteins.

CASP Technique

Then in 1994, a scientist known as John Moult came up with the CASP technique, which stands for Critical Assessment for Protein Structure Prediction, and this is provided for a comparative model through which protein structures can be predicted.

Specialty Of AI

But however, predicting protein structures is a very complex and challenging exercise, especially when you’re relying upon traditional experimental techniques such as X-ray crystallography and nuclear magnetic resonance. This is where the emergence of artificial intelligence has caused a major disruption in the field of protein structure prediction. In 2018, a company known as Deep Mind made use of artificial intelligence and deep learning to come out with a predictive algorithm, which today has emerged as a breakthrough technology that can accurately predict protein structure.

Conclusion

These advances made in the production of protein structure with the usage of artificial intelligence and deep learning algorithms have transformed our understanding of the SARS-CoV-2 and it has definitely enabled the accelerated development of vaccines.

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