Combating antibiotic resistance: mechanisms, challenges, and innovative approaches in antibacterial drug development

Published: Jan. 26, 2025

Antibiotic resistance is a significant threat to public health and drug development, driven largely by the overuse misuse of antibiotics in medical agricultural settings. As bacteria adapt evade current drugs, managing bacterial infections has become increasingly challenging, leading prolonged illnesses, higher healthcare costs, increased mortality. This review explores critical role fighting mechanisms that enable resist them. Key discussed include carvacrol, dalbavancin, quinolones, fluoroquinolones, zoliflodacin, each with unique actions against pathogens. Bacteria have evolved complex strategies, such as enzyme production neutralize modifying targets, using efflux pumps remove antibiotics, significantly reducing efficacy. Additionally, examines challenges antibiotic including declining discovery rate novel drugs due high costs regulatory complexities. Innovative approaches, structure-based design, combination therapies, new delivery systems, are highlighted for their potential create compounds enhanced action resistant strains. provides valuable insights researchers developers aiming combat advance development robust antibacterial therapies future security.

Language: Английский

From Canonical to Unique: Extension of A Lipophilicity Scale of Amino Acids to Non-Standard Residues

Published: Jan. 31, 2024

The lipophilicity of amino acids plays a pivotal role in determining their physicochemical properties as it gives an estimate solubility, binding propensity, and bioavailability. Herein, we applied the IEFPCM/MST implicit solvation model to compute n-octanol/water partition coefficient lipophilic descriptor for non-standard acids. Thus, extending our previous work on hydrophobicity scale To this end, employed two structural models, named Model 1 2, differentiated solely by C-terminal capping groups using N- or O- methyl substituent, respectively. Our findings revealed substantial similarities between validating values side chains. Differences were observed fewer cases, indicating effect group chain hydrophobicity. This is expected one contains hydrogen bond donor (Model 1) while other uses acceptor 2). Overall, both models exhibit strong correlations with experimental values, showing lower statistical errors. In addition, predictions able correctly predict change due number acetylated lysines peptide pairs determined HPLC, suggesting that can be proteomics studies include post-translational modifications beyond acetylation.

Language: Английский