The prospects of quantum computing in computational molecular biology,Wiley Interdisciplinary Reviews: Computational Molecular Science

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The prospects of quantum computing in computational molecular biology
Wiley Interdisciplinary Reviews: Computational Molecular Science ( IF 16.8 ) Pub Date : 2020-05-22 , DOI: 10.1002/wcms.1481
Carlos Outeiral _{1,

2} , Martin Strahm ₃ , Jiye Shi ₄ , Garrett M. Morris ₁ , Simon C. Benjamin ₂ , Charlotte M. Deane ₁

Affiliation

Quantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all scientific disciplines. In this review, we examine how current quantum algorithms could revolutionize computational biology and bioinformatics. There are potential benefits across the entire field, from the ability to process vast amounts of information and run machine learning algorithms far more efficiently, to algorithms for quantum simulation that are poised to improve computational calculations in drug discovery, to quantum algorithms for optimization that may advance fields from protein structure prediction to network analysis. However, these exciting prospects are susceptible to “hype,” and it is also important to recognize the caveats and challenges in this new technology. Our aim is to introduce the promise and limitations of emerging quantum computing technologies in the areas of computational molecular biology and bioinformatics.

中文翻译：

计算分子生物学中量子计算的前景

量子计算机原则上可以比传统计算机更快地指数级地解决某些问题。我们尚未到达有用的量子计算的时代，但是当我们这样做时，它将影响几乎所有的科学学科。在这篇综述中，我们研究了当前的量子算法如何革新计算生物学和生物信息学。从处理大量信息和更高效地运行机器学习算法的能力，到有望改善药物发现中计算计算的量子模拟算法，再到可能优化的量子算法，整个领域都有潜在的收益。从蛋白质结构预测到网络分析领域不断发展。但是，这些令人兴奋的前景容易受到“炒作，”，认识到这项新技术的注意事项和挑战也很重要。我们的目的是介绍计算分子生物学和生物信息学领域新兴的量子计算技术的前景和局限性。

更新日期：2020-05-22

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