Protein Folding: How Quantum Computing can help
Exploring new landscapes that have never before been, and must be, looked at, theorized, or dreamt of — that is the role of Quantum Computing.
Today’s computers cannot do traverse this landscape — and never will. That will be, the role of quantum computing. And it’s essential for us to solve the issues facing us, whether genetic, or environmental, or if we are to be a space-faring world again.
In starting with the body, quantum computing can model complex protein folding mechanisms in the body, which will not reach with today’s computing power.
So why focus on proteins and quantum computing? Because Proteins are the building blocks of ‘everything’ in the universe. Proteins are molecules within all cells that perform functions essential to the cell’s, and thereby the body’s, survival. Their role involves everything from structure to function to the regulation of all tissues in the body. Specific DNA sequences code Proteins, built of amino acids. DNA is transcripted into mRNA, and the mRNA translates these particular DNA sequences into a long chain of amino acids. The 20 different types of amino acids and their combinations contribute to a particular fold of the amino acids to create specific proteins, each folded in a way that maximizes the efficiency of their intended function, exposing active and bonding sites. These specific folding patterns are also created using the lowest energy path, producing a more stable overall protein. Proteins, however, do not always fold in their native (correct) state. Usually, these failed proteins will be inactive, neither helping nor hurting the cell’s function. However, there can be the case that a failure to correctly fold leads to misfolded proteins, which can have toxic effects. These misfolded proteins can lead to many neurodegenerative diseases and other ailments, such as allergies due to a weakened immune system. Both genomic and foreign factors could cause them.
The current problem in addressing these misfolded proteins is that we cannot accurately model the folding pattern of proteins based on the amino acid chain. We are currently learning more and more about the protein structure itself, but researchers are unsure about getting to the formation through folding. We can only have success with modeling protein folding in their native state. We do not, however, can find the folding pattern of misfolded proteins, which would be necessary to help cure a myriad of diseases. Current modeling techniques include lattice protein folding, which provides a very simplified model, due to computational limits, of different amino acid combinations. Protein folding is a problem that can be solved through quantum computing, and more specifically quantum annealing so that the lowest energy path to creating a protein can be found much more quickly, and without limitations.
Quantum computers can model many iterations of possible combinations, allowing researchers to find the one with the lowest energy state. This could open new doors to the interaction between medicine or diseases with specific proteins. Researchers at D-Wave have already begun research in this field, and have created the first quantum-mechanical model of proteins, albeit a very inefficient one.
How vital is quantum computing? Consider the Levinthal paradox. It takes more than the age of the universe (14 billion years) to try all possible combinations of protein folding based on amino acid chains. The body, however, can achieve this folding pattern in a matter of nanoseconds. It’s a complete mystery how the body can accomplish this. We are not even able to fathom this change of state. The quantum computer may be able to…