Yang Liu, Cao Suqi, Liu Lei, Zhu Ruixin, Wu Dingfeng
National Center, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, 3333 Binsheng Road, Hangzhou 310052, P. R. China.
Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, 1239 Siping Road, Shanghai 200072, P. R. China.
Brief Bioinform. 2024 Nov 22;26(1). doi: 10.1093/bib/bbae714.
The unique cyclic structure of cyclic peptides grants them remarkable stability and bioactivity, making them powerful candidates for treating various diseases. However, the lack of standardized tools for cyclic peptide data has hindered their potential in today's artificial intelligence-driven efficient drug design landscape. To bridge this gap, here we introduce a Python package named cyclicpeptide specifically for cyclic peptide drug design. This package provides standardized tools such as Structure2Sequence, Sequence2Structure, and format transformation to process, convert, and standardize cyclic peptide structure and sequence data. Additionally, it includes GraphAlignment for cyclic peptide-specific alignment and search and PropertyAnalysis to enhance the understanding of their drug-like properties and potential applications. This comprehensive suite of tools aims to streamline the integration of cyclic peptides into modern drug discovery pipelines, accelerating the development of cyclic peptide-based therapeutics.
环肽独特的环状结构赋予它们显著的稳定性和生物活性，使其成为治疗各种疾病的有力候选药物。然而，缺乏用于环肽数据的标准化工具阻碍了它们在当今人工智能驱动的高效药物设计领域的潜力。为了弥补这一差距，我们在此引入一个名为cyclicpeptide的Python包，专门用于环肽药物设计。该包提供了诸如Structure2Sequence、Sequence2Structure和格式转换等标准化工具，以处理、转换和标准化环肽结构和序列数据。此外，它还包括用于环肽特异性比对和搜索的GraphAlignment以及用于增强对其类药物性质和潜在应用理解的PropertyAnalysis。这一套全面的工具旨在简化环肽融入现代药物发现流程，加速基于环肽的治疗药物的开发。
