Antimicrobial peptides (AMPs) are natural polypeptides with antimicrobial activities and are found in most organisms. AMPs are evolutionarily conservative components that belong to the innate immune system and show potent activity against bacteria, fungi, viruses and in some cases display antitumor activity. Thus, AMPs are major candidates in the development of new antibacterial reagents. In the last few decades, AMPs have attracted significant attention from the research community. During the early stages of the development of this research field, AMPs were experimentally identified, which is an expensive and time-consuming procedure. Therefore, research and development (R&D) of fast, highly efficient computational tools for predicting AMPs has enabled the rapid identification and analysis of new AMPs from a wide range of organisms. Moreover, these computational tools have allowed researchers to better understand the activities of AMPs, which has promoted R&D of antibacterial drugs. In this review, we systematically summarize AMP prediction tools and their corresponding algorithms used.

抗菌肽（AMP）是具有抗菌活性的天然多肽，存在于大多数生物体中。 AMP 是进化上保守的成分，属于先天免疫系统，对细菌、真菌、病毒表现出有效的活性，在某些情况下还表现出抗肿瘤活性。因此，AMP 是开发新型抗菌试剂的主要候选者。在过去的几十年中，AMP 引起了研究界的极大关注。在该研究领域发展的早期阶段，AMP 是通过实验鉴定的，这是一个昂贵且耗时的过程。因此，用于预测 AMP 的快速、高效计算工具的研发 (R&D) 使得能够快速识别和分析来自多种生物体的新 AMP。此外，这些计算工具使研究人员能够更好地了解AMPs的活性，从而促进抗菌药物的研发。在这篇综述中，我们系统地总结了 AMP 预测工具及其所使用的相应算法。