Research on artificial intelligence-based drug molecule design and screening strategies
基于人工智能的药物分子设计与筛选策略研究

摘要

人工智能（AI）在药物分子设计与筛选领域的应用日益成为提升药物研发效率的关键技术。通过深度学习、机器学习等AI技术，研究人员能够在海量分子数据中快速识别潜在的药物分子，从而大大缩短研发周期，降低成本，提高命中率。本文探讨了基于人工智能的药物分子设计与筛选策略，分析了AI在药物分子筛选中的优势与挑战，探讨了如何通过建立有效的计算模型来优化分子设计，提升药物研发的精确度。本文还重点讨论了AI算法与传统药物筛选方法的结合应用，以及在药物发现中可能遇到的技术难题。综上所述，人工智能的引入不仅优化了药物分子的设计过程，还为药物筛选和精准医学的发展提供了新的动力。

Abstract

The application of artificial intelligence (AI) in the field of drug molecule design and screening has increasingly become a key technology to improve the efficiency of drug research and development. By leveraging AI technologies such as deep learning and machine learning, researchers can quickly identify potential drug molecules from massive molecular datasets, thereby significantly shortening the research and development cycle, reducing costs, and improving hit rates. This paper explores AI-based strategies for drug molecule design and screening, analyzes the advantages and challenges of AI in drug molecule screening, and discusses how to optimize molecular design and enhance the accuracy of drug research and development by establishing effective computational models. It also focuses on the combined application of AI algorithms with traditional drug screening methods, as well as the potential technical difficulties encountered in drug discovery. In summary, the integration of artificial intelligence not only optimizes the design process of drug molecules but also provides new impetus for the development of drug screening and precision medicine.