Mechanistic principles of antimicrobial peptides uncovered by charge density-based machine learning
| Title | Mechanistic principles of antimicrobial peptides uncovered by charge density-based machine learning |
| Publication Type | Journal Article |
| Year of Publication | 2026 |
| Authors | Malshikare, H, U. Priyakumar, D, Chatterjee, P, Sengupta, D |
| Journal | Chemical Communications |
| Volume | 62 |
| Issue | 13 |
| Pagination | PMID 9610838 |
| Date Published | FEB |
| Type of Article | Article |
| ISSN | 1359-7345 |
| Abstract | Antimicrobial peptides (AMPs) are emerging as potent alternatives to conventional antibiotics, yet their diverse nature due to divergent mechanisms of action hinders rational design. Here, we present an electrostatics-stratified computational framework that uncovers key physicochemical principles governing AMP activity. Experimentally validated peptides were grouped by average charge per residue (i.e., the charge/length of the peptide) and analyzed through integrated sequence-, structure-, and chemistry-based descriptors. Distinct molecular signatures emerged across electrostatic regimes: low-charge/length peptides rely on amphipathic organization via structural compactness, whereas the intermediate-charge/length peptides exhibit balanced hydrophobicity and electrostatics. The high-charge peptides couple strong cationic attraction with lipophilicity and tryptophan anchoring to mainly disrupt membranes. Interestingly, hydrophobic moment, which is a measure of the amphipathicity, is found to be important in all three classes of AMPs. This study identifies distinguishing features of AMP sub-groups and suggests design guidelines for developing selective and potent next-generation AMPs. |
| DOI | 10.1039/d5cc06374d |
| Type of Journal (Indian or Foreign) | Foreign |
| Impact Factor (IF) | 4.2 |

Add new comment