DRAMP 5.0: an update integrating sequence and structure in a novel FASTS format for AI-driven design of antimicrobial peptides
- 1School of Life Science and Technology, China Pharmaceutical University , Nanjing 211100 ,
- 2The State Key Laboratory of Pharmaceutical Biotechnology, College of Life Sciences, Nanjing University , Nanjing 210023 ,
- 3Changzhou High-Tech Research Institute of Nanjing University and Jiangsu TargetPharma Laboratories Inc. , Changzhou 213164 ,
Abstract
Antimicrobial peptides (AMPs) represent promising candidates for combating multidrug-resistant bacterial infections; however, their clinical translation has been hampered by inherent limitations, including poor proteolytic and serum stability, unfavorable pharmacokinetic profiles, and cytotoxicity or hemolytic effects. In recent years, artificial intelligence (AI)-driven peptide design has emerged as a transformative strategy to accelerate AMP discovery and optimization by navigating vast sequence spaces and predicting multi-objective properties. Nevertheless, existing AMP databases predominantly catalog sequence and activity information, with insufficient annotation of non-natural amino acid and chemical modifications. In this update, the Data Repository of Antimicrobial Peptides (DRAMP) introduces a novel FASTS format, which incorporates SMILES representations into FASTA annotation lines, enabling the simultaneous storage of sequence and structural information within a single text file. This unified format allows accurate representation of peptides containing non-natural residues and chemical modifications, facilitates structure-aware sequence analysis, and supports AI/ML-based peptide prediction and design. DRAMP 5.0 currently contains 32,296 entries (2,036 newly added). In addition, 22,298 peptide sequences have been annotated in the newly proposed FASTS format. The updated DRAMP provides an enhanced resource for AMP research, cheminformatics, and AI-driven peptide discovery, and remains freely available at https://dramp.cpu-bioinfor.org/.
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BibTeX
@article{ma2026dramp,
title = {{DRAMP 5.0: an update integrating sequence and structure in a novel FASTS format for AI-driven design of antimicrobial peptides}},
author = {Tianyue Ma and Yihan Huang and Hongyu Liu and Wentao Wu and Linxin Ren and Fahad Akhtar and Maryam Nawaz and Zichun Hua and Heng Zheng and Xingzhen Lao},
journal = {Nucleic Acids Research},
year = {2026},
month = oct,
doi = {10.1093/nar/gkag989},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag989/8916835},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - DRAMP 5.0: an update integrating sequence and structure in a novel FASTS format for AI-driven design of antimicrobial peptides
AU - Tianyue Ma
AU - Yihan Huang
AU - Hongyu Liu
AU - Wentao Wu
AU - Linxin Ren
AU - Fahad Akhtar
AU - Maryam Nawaz
AU - Zichun Hua
AU - Heng Zheng
AU - Xingzhen Lao
PY - 2026
DA - 2026/10/15
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag989
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag989/8916835
AB - Antimicrobial peptides (AMPs) represent promising candidates for combating multidrug-resistant bacterial infections; however, their clinical translation has been hampered by inherent limitations, including poor proteolytic and serum stability, unfavorable pharmacokinetic profiles, and cytotoxicity or hemolytic effects. In recent years, artificial intelligence (AI)-driven peptide design has emerged as a transformative strategy to accelerate AMP discovery and optimization by navigating vast sequence spaces and predicting multi-objective properties. Nevertheless, existing AMP databases predominantly catalog sequence and activity information, with insufficient annotation of non-natural amino acid and chemical modifications. In this update, the Data Repository of Antimicrobial Peptides (DRAMP) introduces a novel FASTS format, which incorporates SMILES representations into FASTA annotation lines, enabling the simultaneous storage of sequence and structural information within a single text file. This unified format allows accurate representation of peptides containing non-natural residues and chemical modifications, facilitates structure-aware sequence analysis, and supports AI/ML-based peptide prediction and design. DRAMP 5.0 currently contains 32,296 entries (2,036 newly added). In addition, 22,298 peptide sequences have been annotated in the newly proposed FASTS format. The updated DRAMP provides an enhanced resource for AMP research, cheminformatics, and AI-driven peptide discovery, and remains freely available at https://dramp.cpu-bioinfor.org/.
SN - 0305-1048
SN - 1362-4962
ER -