Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Jalal Ale Ahmad Highway, Tehran 14115-111, Iran.
Department of Medical Biotechnology, Faculty of Allied Medical Sciences, Iran University of Medical Sciences, Hemmat Highway, Tehran 1449614535, Iran.
Database (Oxford). 2022 Mar 19;2022. doi: 10.1093/database/baac011.
Antimicrobial Peptides (AMPs) have been considered as potential alternatives for infection therapeutics since antibiotic resistance has been raised as a global problem. The AMPs are a group of natural peptides that play a crucial role in the immune system in various organisms AMPs have features such as a short length and efficiency against microbes. Importantly, they have represented low toxicity in mammals which makes them potential candidates for peptide-based drugs. Nevertheless, the discovery of AMPs is accompanied by several issues which are associated with labour-intensive and time-consuming wet-lab experiments. During the last decades, numerous studies have been conducted on the investigation of AMPs, either natural or synthetic type, and relevant data are recently available in many databases. Through the advancement of computational methods, a great number of AMP data are obtained from publicly accessible databanks, which are valuable resources for mining patterns to design new models for AMP prediction. However, due to the current flaws in assessing computational methods, more interrogations are warranted for accurate evaluation/analysis. Considering the diversity of AMPs and newly reported ones, an improvement in Machine Learning algorithms are crucial. In this review, we aim to provide valuable information about different types of AMPs, their mechanism of action and a landscape of current databases and computational tools as resources to collect AMPs and beneficial tools for the prediction and design of a computational model for new active AMPs.
抗菌肽 (AMPs) 被认为是治疗感染的潜在替代品，因为抗生素耐药性已成为全球性问题。AMPs 是一组天然肽，在各种生物体的免疫系统中发挥着至关重要的作用。AMPs 具有长度短、对微生物高效等特点。重要的是，它们在哺乳动物中表现出低毒性，这使它们成为基于肽的药物的潜在候选物。然而，AMPs 的发现伴随着几个问题，这些问题与劳动密集型和耗时的湿实验室实验有关。在过去的几十年中，已经进行了许多关于 AMPs（无论是天然的还是合成的）的研究，并且最近在许多数据库中都有相关数据。通过计算方法的进步，从公开可访问的数据库中获得了大量的 AMP 数据，这些数据是挖掘模式以设计新的 AMP 预测模型的有价值资源。然而，由于目前评估计算方法存在缺陷，需要进行更多的询问以进行准确的评估/分析。考虑到 AMPs 的多样性和新报告的 AMPs，机器学习算法的改进至关重要。在这篇综述中，我们旨在提供有关不同类型的 AMPs、它们的作用机制以及当前数据库和计算工具的全景图的有价值信息，这些信息是收集 AMPs 的资源，也是用于预测和设计新的活性 AMPs 的计算模型的有益工具。
