Ochoa Rodrigo, Deibler Kristine
Novo Nordisk A/S, Novo Nordisk Park, Måløv, Denmark.
Novo Nordisk Research Center Seattle, Novo Nordisk A/S, Seattle, Washington, USA.
J Pept Sci. 2025 Feb;31(2):e3666. doi: 10.1002/psc.3666.
We present PepFuNN, a new open-source version of the PepFun package with functions to study the chemical space of peptide libraries and perform structure-activity relationship analyses. PepFuNN is a Python package comprising five modules to study peptides with natural amino acids and, in some cases, sequences with non-natural amino acids based on the availability of a public monomer dictionary. The modules allow calculating physicochemical properties, performing similarity analysis using different peptide representations, clustering peptides using molecular fingerprints or calculated descriptors, designing peptide libraries based on specific requirements, and a module dedicated to extracting matched pairs from experimental campaigns to guide the selection of the most relevant mutations in design new rounds. The code and tutorials are available at https://github.com/novonordisk-research/pepfunn.
我们展示了PepFuNN，这是PepFun软件包的一个新的开源版本，具有研究肽库化学空间和进行构效关系分析的功能。PepFuNN是一个Python软件包，包含五个模块，用于研究含有天然氨基酸的肽，在某些情况下，还可基于公共单体字典研究含有非天然氨基酸的序列。这些模块可以计算物理化学性质，使用不同的肽表示法进行相似性分析，使用分子指纹或计算得到的描述符对肽进行聚类，根据特定要求设计肽库，以及一个专门用于从实验活动中提取匹配对的模块，以指导在设计新轮次时选择最相关的突变。代码和教程可在https://github.com/novonordisk-research/pepfunn上获取。
