Researchers Predict Protein Structure Using Quantum Computing

Researchers Predict Protein Structure Using Quantum Computing

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protein-structure-quantum-computing
protein-structure-quantum-computing

Intersection of Quantum and Classical Computing: Researchers Predict Protein Structure Using Quantum Computing

It is not long after the first quantum computer dedicated to the healthcare research officially unveiled, but we have more exciting news! 

In a new finding published in the Journal of Chemical Theory and Computation, researchers from Cleveland Clinic and IBM successfully applied quantum computing methods to predict protein structure.

Introduction to Protein Structure Prediction

Predicting protein structures has challenged researchers for decades. Proteins, essential for numerous bodily functions, interact with various molecules, making it crucial to understand their structures to develop targeted treatments for diseases.

Benefiting from this technological development, scientists combine machine learning with computational chemistry to understand protein structures. Training models with existing experimental proteins allows for the prediction of new protein structures. However, this method is limited to the number of proteins the model has been taught to identify. The nature of the protein is that it can exist in various forms depending on the environment. What about the case in which the shape of the protein has changed or mutated, and the model is no longer able to recognise even if it was trained by other shapes of the molecule? Now, that is the problem.

There is a traditional approach to identify the structure accurately, it involves finding the most stable structure from a certain number of possible shapes by simulating them. Whether enhancing the capability of the machine learning model or scaling up the simulation program, due to the sheer amount of computational power it would require a quantum computer to make the calculations with many tens of thousands of stable qubits.

Not to mention that the bigger the protein, the more challenging it would be for the scientists to model. According to Dr. Raubenolt, a postdoctoral fellow at Cleveland Clinic, 'For a small protein with 100 amino acids, a classical computer would need an amount of time equivalent to the age of the universe to exhaustively search all possible outcomes

protein-structure-quantum-computing

How are Quantum Computers used in Protein Modeling

A research team led by Dr. Raubenolt and Dr. Hakan Doga, a researcher at IBM, applied both quantum and classical computing methods to predict the folding of a small fragment of the Zika virus protein on quantum computer. They employed quantum computing in areas such as determining protein size, intrinsic disorder, mutation and the physics involved in the protein folding – All of them are not easily found even using the state-of art classical HPC methods.

Researchers initially used a quantum algorithm to model the lowest energy conformation of the fragment, then applied classical methods to convert the results obtained from the quantum computer and reconstruct the protein structure with its sidechains and performed the final refinement of the structure with classical molecular mechanical methods.

This work is truly a foundational step for future studies combining classical and quantum approach in a very remarkable way. "One of the most unique things about this project is the number of disciplines involved," says Dr. Raubenolt. "Our team's expertise ranges from computational biology and chemistry, structural biology, software and automation engineering, to experimental atomic and nuclear physics, mathematics, and of course, quantum computing and algorithm design. It took the knowledge from each of these areas to create a computational framework that can mimic one of the most important processes for human life."

What are the future possibilities for Quantum In Chemistry

This advancement opens new avenues for quantum computing in healthcare, potentially revolutionising how we understand and treat diseases. The team is eager to continue developing quantum algorithms that can work for more complex structures. "This work is an important step forward in exploring where quantum computing capabilities could show strengths in protein structure prediction," says Dr. Doga. "Our goal is to design quantum algorithms that can find how to predict protein structures as realistically as possible." 


The link to the research article:

Hakan Doga et al, A Perspective on Protein Structure Prediction Using Quantum Computers, Journal of Chemical Theory and Computation (2024). DOI: 10.1021/acs.jctc.4c00067

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