Abstract With the dramatic development of high-performance computing, the emergence of better algorithms and the accumulation of large amounts of chemical and biological data, computer-aided drug design technology is playing an increasingly prominent role in drug discovery and development with its advantages of fast speed, low cost and high efficiency. In recent years, due to the constant development of machine learning (ML) theory, artificial intelligence (AI), a powerful data mining technology has been widely used in various stages of drug design. More recently, drug design has entered the era of big data, ML methods have gradually evolved into a deep learning (DL) method with stronger generalization ability and more effective big data processing, which further promotes the combination of AI technology and computer-aided drug design technology, thus facilitating the discovery and design of new drugs. This paper mainly summarizes the application progress of AI technology in drug design process, analyses and compares its advantages over traditional methods. Finally, the challenges faced by AI technology and its application prospects in the field of drug design are also discussed.

中文翻译：

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大数据时代人工智能助力药物设计

摘要 随着高性能计算的迅猛发展、更好算法的出现以及大量化学和生物数据的积累，计算机辅助药物设计技术以其快速、快速的优势在药物发现和开发中发挥着越来越突出的作用。速度快，成本低，效率高。近年来，由于机器学习（ML）理论的不断发展，人工智能（AI）这一强大的数据挖掘技术被广泛应用于药物设计的各个阶段。最近药物设计进入大数据时代，ML方法逐渐演化为泛化能力更强、大数据处理更有效的深度学习（DL）方法，进一步促进了人工智能技术与计算机辅助药物的结合。设计技术，从而促进新药的发现和设计。本文主要总结了人工智能技术在药物设计过程中的应用进展，分析比较了其相对于传统方法的优势。最后，还讨论了人工智能技术面临的挑战及其在药物设计领域的应用前景。