AMPing up the search: An in silico approach to identifying Antimicrobial Peptides (AMPs) with potential anti-biofilm activity
Mhade, S.; Panse, S.; Tendulkar, G.; Awate, R.; Kadam, S.; Kaushik, K.
Show abstract
Antibiotic resistance is a public health threat, and the rise of multidrug-resistant bacteria, including those that form protective biofilms, further compounds this challenge. Antimicrobial peptides (AMPs) have been recognized for their anti-infective properties, including their ability to target processes important for biofilm formation. However, given the vast array of natural and synthetic AMPs, determining potential candidates for anti-biofilm testing is a significant challenge. In this study, we present an in silico approach, based on open-source tools, to identify AMPs with potential anti-biofilm activity. This approach is developed using the sortase-pilin machinery, important for adhesion and biofilm formation, of the multidrug-resistant, biofilm-forming pathogen C. striatum as the target. Using homology modeling, we modeled the structure of the C. striatum sortase C protein, resembling the semi-open lid conformation adopted during pilus biogenesis. Next, we developed a structural library of 5544 natural and synthetic AMPs from sequences in the DRAMP database. From this library, AMPs with known anti-Gram positive activity were filtered, and 100 select AMPs were evaluated for their ability to interact with the sortase C protein using in-silico molecular docking. Based on interacting residues and docking scores, we built a preference scale to categorize candidate AMPs in order of priority for future in vitro and in vivo biofilm studies. The considerations and challenges of our approach, and the resources developed, which includes a search-enabled repository of predicted AMP structures and protein-peptide interaction models relevant to biofilm studies (B-AMP), can be leveraged for similar investigations across other biofilm targets and biofilm-forming pathogens.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Cell-surface protein YwfG of Lactococcus lactis binds to α-1,2-linked mannose 95%
- A Dimer between Monomers and Hexamers - Oligomeric Variations in Glucosamine 6-Phosphate Deaminase Family 95%
- Comprehensive Genome Based Analysis of Vibrio parahaemolyticus for Identifying Novel Drug and Vaccine Molecules: Subtractive Proteomics and Vaccinomics Approach 95%
Similar papers in this journal
- Putative staphylococcal enterotoxin possesses two common structural motifs for MHC-II binding 95%
- A Mathematical Genomics Perspective on the Moonlighting Role of Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) 95%
- Proximal relationships of moonlighting Proteins in Escherichia coli: a mathematical genomic perspective 95%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Clues to reaction specificity in PLP-dependent fold type I aminotransferases of monosaccharide biosynthesis 95%
- Identification and Characterization of Outer Membrane Proteins and Membrane Spanning Protein Complexes in Brucella melitensis 95%
- A novel consensus-based computational pipeline for rapid screening of antibody therapeutics for efficacy against SARS-CoV-2 variants of concern including omicron variant 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.