Should you care about quantum computing? | by Yasmeen Naseer | Jan, 2023
“For some problems, supercomputers aren’t that great.” — IBM
Drug discovery and design they are complex, time-consuming processes – think years, and in most cases decades. They begin with the identification of a biological target, a protein or receptor that is believed to be involved in a specific disease. Small molecules that have the potential to interact with the target are then identified and tested for safety and efficacy before they are optimized to improve their efficacy and reduce their side effects, before they can ultimately be tested in preclinical and clinical trials.
In today’s world, drug design is often based on computational techniques that help simulate the behavior of a molecule and its interaction with a target. While physicists and chemists routinely use computers to simulate the behavior of atoms and molecules, such simulations require massive amounts of computing power because interactions between 3 or more particles quickly become tremendously complex. This complexity is compounded by the fact that electrons obey the laws of quantum mechanics that allow for strange phenomena such as superposition, that is, the ability of a quantum system to exist in multiple states simultaneously. A single quantum particle, like an electron, for example, can surprisingly exist in multiple locations at the same time.
Quantum systems can also become tangled upwhich means that the state of a cog in the system depends on the state of all the others, even when they are separated by great distances, present quantum fluctuations, caused by the Heisenberg Uncertainty Principle, which make it difficult to predict the behavior of a quantum system even when its initial state is known.
Therefore, the states of quantum systems cannot be described by a single set of classical variables such as position and momentum. Instead, they must be described by a wave function that contains information about all possible states of the system. Classical computers that obey the laws of Newtonian physics perform abysmal when faced with simulating quantum phenomena.
Pharmaceutical molecules typically contain 50 to 80 atoms, while the proteins that drugs interact with tend to contain thousands..
Modern supercomputers may have impressive processing power, but they lack the complexity to identify intricate patterns in large data sets.. This is especially true when examining proteins and their possible folding structures, a topic of great importance to biology and medicine since the shape of the protein defines its function. Figuring out how a single 100 amino acid chain folds is no easy feat, as it has trillions of potential configurations and requires more than just the brute force normally harnessed to simulate protein folding, as no computer has the working memory. needed to handle the trillions of possible combinations. of individual folds.
This is where quantum computers come in. Quantum computers are fundamentally different beasts that can perform complex calculations exponentially faster and with only a fraction of the total power required by classical computers, and thus could significantly speed up the process of drug discovery and development.
However, quantum computers go beyond being able to speed up the speed at which classical computers perform computations and also have the potential to open up entirely new avenues for research in the domain in which they are implemented. In the case of our example of ongoing drug development, for example, they could also be used to simulate the behavior of enzymes that are crucial in drug metabolism and help identify new drugs that are metabolized faster or slower than existing ones to help reduce side effects. -effects and enhance effectiveness. They could also be used to optimize the structure of drug candidates by simulating the behavior of different conformations of a molecule, thus helping to identify new drugs that are more stable and have better pharmacokinetic properties than existing ones.
Quantum algorithms are revolutionizing the way complex problems and puzzles such as protein folding can be solved. They create multidimensional spaces to find patterns that link data points. In this case of protein folding, these patterns could tell us the minimum energy configuration of the molecule, which also turns out to be the solution to the problem.
Classical computers just can’t match, they just can’t do what quantum hardware combined with advanced algorithms can do. As quantum hardware scales and quantum algorithms advance, they could tackle protein folding problems, and many others, that are too complex for any supercomputer.
Drug design and discovery was an example of one application that quantum computers have the potential to revolutionize, but certainly not the only one. They can also help us solve many other problems, including one of the most pressing problems of our time: climate change.
Currently, the impact of global warming is forecast by using computer models that simulate the Earth’s climate. These models take into account factors such as greenhouse gas emissions, land use change, and the behavior of the oceans and atmosphere, and use complex mathematical equations to simulate the interactions between these factors and provide projections of conditions. future climates. 
Quantum computers have the potential to not only speed up the creation of climate simulations, but also make them more accurate and efficient because, as we’ve already noted, when combined with the right algorithms, quantum computers can process large amounts of data faster. and more precision than classical computers.
They can, for example, be used to simulate the behavior of the Earth’s oceans. Ocean circulation plays a crucial role in regulating the Earth’s climate and quantum computers can simulate the behavior of ocean currents to predict how currents, sea level, ocean temperature, and acidity will change in the future.
Quantum computers can also be used to simulate the behavior of Earth’s atmosphere by analyzing vast amounts of data from weather stations and satellites to accurately predict future changes in temperature and precipitation patterns. Lastly, just for the purpose of this article, quantum computers can also be used to optimize the parameters of existing climate models to get us out of any delusions we may still have about climate change and its long-term effects.
These are just two of several quantum computing applications that show that quantum computing definitely has its place, which brings us to our next question: how do quantum computers really work, and what makes them different from the classical devices we’re all used to. wear? Subscribe to stay tuned as I dig deeper into topics related to quantum computing. I write almost every day mainly on topics related to business, finance, economics and scientific issues that affect us. Any ideas about what you just read? I’d love to hear them in the comments.
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