Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

B-AMP

General information

URL: https://b-amp.karishmakaushiklab.com
Full name: ANTIMICROBIAL PEPTIDE REPOSITORY FOR BIOFILMS
Description: B-AMP is an Antimicrobial Peptide (AMP) repository for biofilms, consisting of a vast library of 5552 structural AMP models, AMPs annotated to relevant biofilm literature, and protein-peptide interaction models with potential biofilm targets.
Year founded: 2021
Last update:
Version:
Accessibility:
Accessible
Country/Region: India

Classification & Tag

Data type:
Data object:
NA
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Major species:
Keywords:

Contact information

University/Institution: Guru Nanak Khalsa College of Arts, Science and Commerce
Address: Department of Bioinformatics, Guru Nanak Khalsa College of Arts, Science and Commerce (Autonomous), Mumbai, India.
City: Mumbai
Province/State:
Country/Region: India
Contact name (PI/Team): Dr. Karishma S. Kaushik
Contact email (PI/Helpdesk): karishmaskaushik@gmail.com

Publications

36329825
'Targeting' the search: An upgraded structural and functional repository of antimicrobial peptides for biofilm studies (B-AMP v2.0) with a focus on biofilm protein targets. [PMID: 36329825]
Shashank Ravichandran, SaiSupriya Avatapalli, Yatindrapravanan Narasimhan, Karishma S Kaushik, Ragothaman M Yennamalli

Bacterial biofilms, often as multispecies communities, are recalcitrant to conventional antibiotics, making the treatment of biofilm infections a challenge. There is a push towards developing novel anti-biofilm approaches, such as antimicrobial peptides (AMPs), with activity against specific biofilm targets. In previous work, we developed Biofilm-AMP, a structural and functional repository of AMPs for biofilm studies (B-AMP v1.0) with more than 5000 structural models of AMPs and a vast library of AMP annotations to existing biofilm literature. In this study, we present an upgraded version of B-AMP, with a focus on existing and novel bacterial biofilm targets. B-AMP v2.0 hosts a curated collection of 2502 biofilm protein targets across 473 bacterial species, with structural protein models and functional annotations from PDB, UniProt, and PubMed databases. The biofilm targets can be searched for using the name of the source organism, and function and type of protein, and results include designated Target IDs (unique to B-AMP v2.0), UniProt IDs, 3D predicted protein structures, PDBQT files, pre-defined protein functions, and relevant scientific literature. To present an example of the combined applicability of both, the AMP and biofilm target libraries in the repository, we present two case studies. In the first case study, we expand an pipeline to evaluate AMPs against a single biofilm target in the multidrug resistant, bacterial pathogen , using 3D protein-peptide docking models from previous work and Molecular Dynamics simulations (~1.2µs). In the second case study, we build an pipeline to identify candidate AMPs (using AMPs with both anti-Gram positive and anti-Gram negative activity) against two biofilm targets with a common functional annotation in and , widely-encountered bacterial co-pathogens. With its enhanced structural and functional capabilities, B-AMP v2.0 serves as a comprehensive resource for AMP investigations related to biofilm studies. B-AMP v2.0 is freely available at https://b-amp.karishmakaushiklab.com and will be regularly updated with structural models of AMPs and biofilm targets, as well as 3D protein-peptide interaction models for key biofilm-forming pathogens.

Front Cell Infect Microbiol. 2022:12() | 4 Citations (from Europe PMC, 2025-12-13)
34976872
AMPing Up the Search: A Structural and Functional Repository of Antimicrobial Peptides for Biofilm Studies, and a Case Study of Its Application to , an Emerging Pathogen. [PMID: 34976872]
Shreeya Mhade, Stutee Panse, Gandhar Tendulkar, Rohit Awate, Yatindrapravanan Narasimhan, Snehal Kadam, Ragothaman M Yennamalli, Karishma S Kaushik

Antimicrobial peptides (AMPs) have been recognized for their ability to target processes important for biofilm formation. Given the vast array of AMPs, identifying potential anti-biofilm candidates remains a significant challenge, and prompts the need for preliminary investigations prior to extensive and studies. We have developed Biofilm-AMP (B-AMP), a curated 3D structural and functional repository of AMPs relevant to biofilm studies. In its current version, B-AMP contains predicted 3D structural models of 5544 AMPs (from the DRAMP database) developed using a suite of molecular modeling tools. The repository supports a user-friendly search, using source, name, DRAMP ID, and PepID (unique to B-AMP). Further, AMPs are annotated to existing biofilm literature, consisting of a vast library of over 10,000 articles, enhancing the functional capabilities of B-AMP. To provide an example of the usability of B-AMP, we use the sortase C biofilm target of the emerging pathogen as a case study. For this, 100 structural AMP models from B-AMP were subject to protein-peptide molecular docking against the catalytic site residues of the sortase C protein. Based on docking scores and interacting residues, we suggest a preference scale using which candidate AMPs could be taken up for further , and testing. The 3D protein-peptide interaction models and preference scale are available in B-AMP. B-AMP is a comprehensive structural and functional repository of AMPs, and will serve as a starting point for future studies exploring AMPs for biofilm studies. B-AMP is freely available to the community at https://b-amp.karishmakaushiklab.com and will be regularly updated with AMP structures, interaction models with potential biofilm targets, and annotations to biofilm literature.

Front Cell Infect Microbiol. 2021:11() | 8 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
3302/6895 (52.125%)
Structure:
472/967 (51.293%)
Interaction:
611/1194 (48.911%)
3302
Total Rank
12
Citations
3
z-index

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Record metadata

Created on: 2022-04-23
Curated by:
Yue Qi [2023-08-23]
Lina Ma [2022-06-01]
Pei Liu [2022-05-15]
Pei Liu [2022-05-14]
Pei Liu [2022-04-23]