LAMP: A Database Linking Antimicrobial Peptides

By Xiaowei Zhao, Hongyu Wu, Hairong Lu, Guodong Li, Qingshan Huang. PLoS ONE, 2013

327 citations recorded by the source corpus.

The frequent emergence of drug-resistant bacteria has created an urgent demand for new antimicrobial agents. Traditional methods of novel antibiotic development are almost obsolete. Antimicrobial peptides (AMPs) are now regarded as a potential solution to revive the traditional methods of antibiotic development, although, until now, many AMPs have failed in clinical trials. A comprehensive database of AMPs with information about their antimicrobial activity and cytotoxicity will help promote the process of finding novel AMPs with improved antimicrobial activity and reduced cytotoxicity and eventually accelerate the speed of translating the discovery of new AMPs into clinical or preclinical trials. LAMP, a database linking AMPs, serves as a tool to aid the discovery and design of AMPs as new antimicrobial agents. The current version of LAMP has 5,547 entries, comprising 3,904 natural AMPs and 1,643 synthetic peptides. The database can be queried using either simply keywords or combinatorial conditions searches. Equipped with the detailed antimicrobial activity and cytotoxicity data, the cross-linking and top similar AMPs functions implemented in LAMP will help enhance our current understanding of AMPs and this may speed up the development of new AMPs for medical applications. LAMP is freely available at: http://biotechlab.fudan.edu.cn/database/lamp.

Subfields: Microbiology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6603684206f100b299431ecff60afd8ccb17aaa2

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Citations in the corpus

PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences (2018, methodology): “iprot-unlab-1.7M contains just over 1.7M unlabeled sequences. In curating AMP-lab-15K, we created the positive set by extracting experimentally validated AMP sequences from two major databases: LAMP [Zhao et al., 2013], and satPDB [Singh et al., 2015]. LAMP is a comprehensive database of AMPs with i”
Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou’s general PseAAC (2017, unknown): “Specifically, antibacterial peptides were collected from CAMP, APD3 24 and AntiBP2; antiviral peptides were collected from CAMP, APD3, LAMP 25 and AVPpred; antifungal peptides were collected from CAMP, LAMP and APD3.”
CAMPR3: a database on sequences, structures and signatures of antimicrobial peptides (2015, background): “CAMPR3 10247 757 114 (36 Patterns and 78 HMMs) General APD2 2604 350 Absent General (21) AMPer 1298 Absent 186 HMMs Eukaryotic AMPs (30) LAMP 5548 Presenta Absent General (31)”
Antimicrobial Peptides (2013, background): “One of the latest AMP databases, LAMP (linking antimicrobial peptides), currently has 3904 natural and 1643 synthetic peptides [19].”
Identification of antimicrobial peptides from the human gut microbiome using deep learning (2022, methodology): “…proteins with similar functions were based on sequence alignment, such as BLAST, or identifying conserved motifs and domains using hidden Markov models 14,43,44 ; however, it is difficult to apply these approaches with shorter peptides, particularly for those lacking significant homology 45 .”
DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics (2020, methodology): “YADAMP focuses on short alpha-helical peptides interacting with cell membranes (49), and LAMP has been created as a tool to supply information on AMPs within a single platform (50).”
APD3: the antimicrobial peptide database as a tool for research and education (2015, background): “While CAMPR3 (27) collected 5390 predicted sequences without activity data, DBAASP2 collected ∼6000 synthetic peptides (accessed in October 2015) (50).”