This review article discusses the critical role of molecular fragmentation in AI-based drug discovery. It highlights the importance of fragmentation in understanding molecular structures and improving the efficiency of drug discovery processes. The article summarizes various molecular fragmentation techniques, including those based on existing fragment libraries, sequence-based methods, and structure-based methods. It also explores the applications of these techniques in fragment-based drug discovery (FBDD), which is a promising approach for identifying new drug candidates. FBDD is particularly effective in identifying small molecular fragments that may be overlooked by traditional high-throughput screening methods. The review emphasizes the advantages of FBDD, such as its ability to explore a broader chemical space, generate high-quality starting points for drug development, and improve the efficiency of drug discovery. The article also discusses the challenges and future directions in molecular fragmentation, including the need for more efficient and accurate fragmentation methods. The review concludes by emphasizing the importance of molecular fragmentation in advancing AI-driven drug discovery and the need for further research to optimize fragmentation techniques for practical applications.This review article discusses the critical role of molecular fragmentation in AI-based drug discovery. It highlights the importance of fragmentation in understanding molecular structures and improving the efficiency of drug discovery processes. The article summarizes various molecular fragmentation techniques, including those based on existing fragment libraries, sequence-based methods, and structure-based methods. It also explores the applications of these techniques in fragment-based drug discovery (FBDD), which is a promising approach for identifying new drug candidates. FBDD is particularly effective in identifying small molecular fragments that may be overlooked by traditional high-throughput screening methods. The review emphasizes the advantages of FBDD, such as its ability to explore a broader chemical space, generate high-quality starting points for drug development, and improve the efficiency of drug discovery. The article also discusses the challenges and future directions in molecular fragmentation, including the need for more efficient and accurate fragmentation methods. The review concludes by emphasizing the importance of molecular fragmentation in advancing AI-driven drug discovery and the need for further research to optimize fragmentation techniques for practical applications.