AI-guided few-shot inverse design of HDP-mimicking polymers against drug-resistant bacteria.

Host defense peptide (HDP)-mimicking polymers are promising therapeutic alternatives to antibiotics and have large-scale untapped potential. Artificial intelligence (AI) exhibits promising performance on large-scale chemical-content design, however, existing AI methods face difficulties on scarcity data in each family of HDP-mimicking polymers (<102), much smaller than public polymer datasets (>105), and multi-constraints on properties and structures when exploring high-dimensional polymer space. Herein, we develop a universal AI-guided few-shot inverse design framework by designing multi-modal representations to enrich polymer information for predictions and creating a graph grammar distillation for chemical space restriction to improve the efficiency of multi-constrained polymer generation with reinforcement learning. Exampled with HDP-mimicking ß-amino acid polymers, we successfully simulate predictions of over 105 polymers and identify 83 optimal polymers. Furthermore, we synthesize an optimal polymer DM0.8iPen0.2 and find that this polymer exhibits broad-spectrum and potent antibacterial activity against multiple clinically isolated antibiotic-resistant pathogens, validating the effectiveness of AI-guided design strategy.

An Assay for Immunogenic Detection of Anti-PEG Antibody.

With the increasing use of polyethylene glycol (PEG) based proteins and drug delivery systems, anti-PEG antibodies have commonly been detected among the population, causing the accelerated blood clearance and hypersensitivity reactions, poses potential risks to the clinical efficacy and safety of PEGylated drugs. Therefore, vigilant monitoring of anti-PEG antibodies is crucial for both research and clinical guidance regarding PEGylated drugs. The enzyme-linked immunosorbent assay (ELISA) is a common method for detecting anti-PEG antibodies. However, diverse coating methods, blocking solutions and washing solutions have been employed across different studies, and unsuitable use of Tween 20 as the surfactant even caused biased results. In this study, we established the optimal substrate coating conditions, and investigated the influence of various surfactants and blocking solutions on the detection accuracy. The findings revealed that incorporating 1 % bovine serum albumin into the serum dilution in the absence of surfactants will result the credible outcomes of anti-PEG antibody detection.

A dual-targeting antifungal is effective against multidrug-resistant human fungal pathogens.

Drug-resistant fungal infections pose a significant threat to human health. Dual-targeting compounds, which have multiple targets on a single pathogen, offer an effective approach to combat drug-resistant pathogens, although ensuring potent activity and high selectivity remains a challenge. Here we propose a dual-targeting strategy for designing antifungal compounds. We incorporate DNA-binding naphthalene groups as the hydrophobic moieties into the host defence peptide-mimicking poly(2-oxazoline)s. This resulted in a compound, (Gly0.8Nap0.2)20, which targets both the fungal membrane and DNA. This compound kills clinical strains of multidrug-resistant fungi including Candida spp., Cryptococcus neoformans, Cryptococcus gattii and Aspergillus fumigatus. (Gly0.8Nap0.2)20 shows superior performance compared with amphotericin B by showing not only potent antifungal activities but also high antifungal selectivity. The compound also does not induce antimicrobial resistance. Moreover, (Gly0.8Nap0.2)20 exhibits promising in vivo therapeutic activities against drug-resistant Candida albicans in mouse models of skin abrasion, corneal infection and systemic infection. This study shows that dual-targeting antifungal compounds may be effective in combating drug-resistant fungal pathogens and mitigating fungal resistance.

Reversing Anticancer Drug Resistance by Synergistic Combination of Chemotherapeutics and Membranolytic Antitumor ß-Peptide Polymer.

Multidrug resistance is the main obstacle to cancer chemotherapy. Overexpression of drug efflux pumps causes excessive drug efflux from cancer cells, ultimately leading to drug resistance. Hereby, we raise an effective strategy to overcome multidrug resistance using a synergistic combination of membranolytic antitumor ß-peptide polymer and chemotherapy drugs. This membrane-active ß-peptide polymer promotes the transmembrane transport of chemotherapeutic drugs by increasing membrane permeability and enhances the activity of chemotherapy drugs against multidrug-resistant cancer cells. As a proof-of-concept demonstration, the synergistic combination of ß-peptide polymer and doxorubicin (DOX) is substantially more effective than DOX alone against drug-resistant cancer both in vitro and in vivo. Notably, the synergistic combination maintains a potent anticancer activity after continuous use. Collectively, this combination therapy using membrane lytic ß-peptide polymer appears to be an effective strategy to reverse anticancer drug resistance.