A5009200588- Antimicrobial Peptides and Activities
- vaccines and immunoinformatics approaches
- Diabetes Treatment and Management
- Dendrimers and Hyperbranched Polymers
- Neuropeptides and Animal Physiology
- Pancreatic function and diabetes
- Metabolism, Diabetes, and Cancer
- RNA Interference and Gene Delivery
- Antimicrobial agents and applications
- Chemical Synthesis and Analysis
- Receptor Mechanisms and Signaling
- Biochemical and Structural Characterization
- Machine Learning in Bioinformatics
- Computational Drug Discovery Methods
- Advanced biosensing and bioanalysis techniques
- Pharmacological Receptor Mechanisms and Effects
- RNA and protein synthesis mechanisms
- Nanoparticle-Based Drug Delivery
- Pharmacology and Obesity Treatment
- Lipid Membrane Structure and Behavior
- Peptidase Inhibition and Analysis
- Antibiotic Resistance in Bacteria
- Click Chemistry and Applications
- Polydiacetylene-based materials and applications
- Mass Spectrometry Techniques and Applications
University of Bern
2020-2024
China Pharmaceutical University
2015-2020
State Key Laboratory of Natural Medicine
2015-2016
Machine learning models trained with experimental data for antimicrobial activity and hemolysis are shown to produce new non-hemolytic peptides active against multidrug-resistant bacteria.
We report herein a new chemical platform for coupling chitosan derivatives to antimicrobial peptide dendrimers (AMPDs) with different degrees of ramification and molecular weights via thiol-maleimide reactions. Previous studies showed that simple incorporation AMPDs polymeric hydrogels resulted in loss antibacterial activity augmented cytotoxicity mammalian cells. have shown enabled the two compounds act synergistically. was preserved when incorporating AMPD conjugates into various...
There is an urgent need to develop new antibiotics against multidrug-resistant bacteria. Many antimicrobial peptides (AMPs) are active such bacteria and often act by destabilizing membranes, a mechanism that can also be used permeabilize other antibiotics, resulting in synergistic effects. We recently showed G3KL, AMP with multibranched dendritic topology of the peptide chain, permeabilizes inner outer membranes Gram-negative including strains, leading efficient bacterial killing. Here, we...
A previously unknown pH-effect on the antimicrobial activity of peptide dendrimers and polymyxin B against <italic>Klebsiella pneumoniae</italic> MRSA is reported.
Membrane-disruptive amphiphilic antimicrobial peptides behave as intrinsically disordered proteins by being unordered in water and becoming α-helical contact with biological membranes. We recently discovered that synthesizing the peptide dendrimer L-T25 ((KL)8(KKL)4(KLL)2KKLL) using racemic amino acids to form stereorandomized sr-T25, an analytically pure mixture of all possible diastereoisomers L-T25, preserved antibacterial activity but abolished hemolysis cytotoxicity, pointing...
We recently showed that solid-phase peptide synthesis using racemic amino acids yields stereorandomized peptides comprising all possible diastereomers as homogeneous, single-mass products can be purified by HPLC and stereorandomization modulates activity, toxicity, stability of membrane-disruptive cyclic linear antimicrobial (AMPs) dendrimers. Here, we tested if might compatible with target binding the example proline-rich AMP oncocin, which inhibits bacterial ribosome. Stereorandomization...
Abstract There is an urgent need to develop new antibacterial agents against multidrug resistant bacteria. Herein we report our investigation of antimicrobial peptide dendrimers (AMPDs) active Gram‐negative bacteria, whose sequences were designed using a genetic algorithm optimizing molecular similarity the previously reported AMPD T7 with sequence (KL) 8 ( K KL) 4 KLL) 2 KKL. Our computational approach selected analogues unlikely emerge from systematic study, including X66 non‐conservative...
Machine learning (ML) consists in the recognition of patterns from training data and offers opportunity to exploit large structure-activity database sets for drug design. In area peptide drugs, ML is mostly being tested design antimicrobial peptides (AMPs), a class biomolecules potentially useful fight multidrug resistant bacteria. models have successfully identified membrane disruptive amphiphilic AMPs, however without addressing associated toxicity human red blood cells. Here we trained...
<p>Machine learning (ML) consists in the recognition of patterns from training data and offers opportunity to exploit large structure-activity database sets for drug design. In area peptide drugs, ML is mostly being tested design antimicrobial peptides (AMPs), a class biomolecules potentially useful fight multidrug resistant bacteria. models have successfully identified membrane disruptive amphiphilic AMPs, however without addressing associated toxicity human red blood cells. Here we...
The presence of ionizable groups in antimicrobial peptides (AMPs) often induces a pH-dependent activity. Herein we report that removing eight low p K amino termini peptide dendrimer (AMPD) G3KL provides XC1 with broader pH-activity range. Furthermore, raising the pH to 8.0 reveals strong activities against Klebsiella pneumoniae and methicillin resistant Staphylococcus aureus (MRSA) which these AMPDs are inactive at 7.4. We observe similar effect polymyxin B on MRSA. Binding experiments...