Quantum computing in drug discovery

Ruby Srivastava
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Abstract

Quantum computers are recently being developed in wide varieties, but the computational results from quantum computing have been largely confined to constructing artificial assignments. The applications of quantum computers to real-world problems are still an active area of research. However, challenges arise when the limits of scale and complexity in biological problems are pushed, which has affected drug discovery. The fast-evolving quantum computing technology has transformed the computational capabilities in drug research by searching for solutions for complicated and tedious calculations. Quantum computing (QC) is exponentially more efficient in drug discovery, treatment, and therapeutics, generating profitable business for the pharmaceutical industry. In principle, it can be stated that quantum computing can solve complex problems exponentially faster than classical computing. Here it is needed to mention that QC will not be able to take on every task that classical computers perform—at least not now. It may be classical and quantum-coupled computational technologies combined with machine learning (ML) and artificial intelligence (AI) will solve each task in the future. This review is an overview of quantum computing, which may soon revolutionize the pharmaceutical industry in drug discovery.
量子计算在药物发现中的应用
量子计算机近来得到了广泛的发展,但量子计算的计算成果主要局限于构建人工赋值。量子计算机在实际问题中的应用仍是一个活跃的研究领域。然而,当生物问题的规模和复杂性达到极限时,就会出现挑战,这已经影响到药物的发现。快速发展的量子计算技术已经改变了药物研究的计算能力,为复杂繁琐的计算寻找解决方案。量子计算(QC)在药物发现、治疗和疗法方面的效率呈指数级增长,为制药业带来了丰厚的利润。原则上可以说,量子计算解决复杂问题的速度是经典计算的数倍。这里需要提及的是,量子计算无法承担经典计算机所执行的所有任务--至少现在还不能。未来,经典计算和量子耦合计算技术与机器学习(ML)和人工智能(AI)相结合,可能会解决每项任务。本综述概述了量子计算,它可能很快会在药物发现方面给制药行业带来革命性的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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