Overview

This repository contains the raw experimental data associated with the manuscript entitled:
“Amino Acid Composition Drives Peptide Aggregation: Predicting Aggregation for Improved Synthesis.”

The data were generated as part of a study investigating the relationship between amino acid composition and aggregation propensity during solid-phase peptide synthesis (SPPS).
Contents

The repository contains the following files and folders:

    Zip files with peptide names: Contain all the raw experimental data, uHPLC and LCMS done to characterize the syntheses. Labbook.xlsx helps navigating these.

    Synthesis_data.zip contains all raw data which serve as the foundation for the machine learning models and analyses presented in the manuscript.

    UZH_data_clean.csv is the processed synthesis data from our lab used to train the ML algorithms
   

How to Use the Data

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and adaptation of the data, provided appropriate credit is given.

Researchers may, for example:

    Reproduce or extend the machine learning models described in the associated publication

    Conduct independent analyses of peptide sequence–aggregation relationships

    Benchmark novel models or computational approaches using this dataset as a reference

We encourage the reuse of this dataset for both academic and commercial purposes, in line with the principles of open and reproducible science.

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Citation

Please cite this dataset as:

Bálint Tamás, Marvin Alberts, Teodoro Laino, and Nina Hartrampf, (2025). Raw Experimental Data for "Amino Acid Composition Drives Peptide Aggregation: Predicting Aggregation for Improved Synthesis." Zenodo. https://doi.org/10.26434/chemrxiv-2025-wjbmv