HAMP: A Knowledge-base of Antimicrobial Peptides from Human Microbiome

Background: Antimicrobial peptides (AMPs) can defend the hosts against various pathogens and are found in almost every life form from microorganisms to humans. As the rapid increase of drug-resistant strains in recent years is presenting a serious challenge to healthcare, antimicrobial peptides (AMPs) can revolutionize the antimicrobial development against the drugresistant microbes. Objective: The objective was to encourage the study on the human microbiome towards the inhibition of drug-resistant bacteria by the development of a database containing antimicrobial peptides from the human microbiome. Methods: This database is an outcome of an extended analysis of human metagenome, involving the prediction of coding regions, extraction of peptides, prediction of antimicrobial peptides, and modeling their structure utilizing different in silico tools. Furthermore, an intelligent hash function-based query engine was designed to validate the novelty of specific candidate peptide over the reported Knowledge-base. Results and Discussion: This Knowledge-base currently focuses on antimicrobial peptide sequences (AMPs) predicted from the human microbiome along with their 3D structures modeled using various modeling and molecular dynamics approaches. It includes a total of 1087 unique AMPs from various body sites, with 454 AMPs from the oral cavity, 180 AMPs from the gastrointestinal tract, 42 AMPs from the skin, 12 AMPs from the airway, 6 AMPs from the urogenital tract and 393 AMPs from undefined body locations. A scoring matrix has been generated based on the similarity scores of the sequences that have been incorporated into the Knowledge-base. Furthermore, a Jmol applet is included in the website to help users visualize the 3D structures. Conclusion: The information and functions of the Knowledge-base can offer great help in finding novel antimicrobial drugs, especially towards finding inhibitors for drug-resistant bacteria. The HAMP is freely available at https://bioserver.iiita.ac.in/amp/index.html.