INTRODUCTION

To prepare FASTA files from sequences, merge spreadsheets from the DRAMP repository, sort and filter lists based on certain parameters, we used Python code. The Python scripts utilized a master spreadsheet containing relevant information; these scripts have been made open-source and you can find them in this GitHub repository.

GENERATION OF FASTA FILES

AMP sequence data was obtained from the DRAMP database, an open access and manually curated database of AMP sequences. Using these sequence strings, we generated FASTA files. For example, for Pep6 with sequence

GNGVLKTISHECNMNTWQFLFTCC

the corresponding FASTA file would look like

>Peptide_6
GNGVLKTISHECNMNTWQFLFTCC

You can find the script for this here.

FILTERING ANTI-GRAM POSITIVE & NEGATIVE PEPTIDES

To filter AMPs peptides with anti-Gram positive and negative activities, we used scripts which can be found here and here, respectively. B-AMP also has a search section for anti-Gram positive and negative AMPs here and here.

UPDATING THE AMP LISTS

To incorporate new AMP sequences into our repository, we developed a Python script that can be found here.

SORTING RESIDUES BY INTERACTIONS

After protein-peptide docking, peptides were sorted based on interactions and docking energy using Python's Pandas library. You can find the code for this here.

GENERATING WEBSITE ASSETS & RESOURCES

This website is a static one, with no server-side code running in the cloud. It delivers static HTML over GitHub Pages.

To enable a search repository, we built an offline search engine in JavaScript that runs off a compact search index. The Python script to generate these search indexes is here.

We also wrote a Python script to generate thumbnails for the 3D models on the site.