Xukai Jiang

Multidrug-resistant (MDR) Gram-negative bacteria pose a critical global health threat, while polymyxins remain a last-line therapy. However, their clinical use is limited by nephrotoxicity. Human oligopeptide transporter 2 (hPepT2) is a membrane transporter mediating the reabsorption of polymyxins in renal cells and contributes to their nephrotoxicity, but the molecular basis of their interaction remains unclear. Here, we investigated the structure-interaction relationship (SIR) of polymyxins with hPepT2 by integrating computational, chemical, and cell biology approaches. Bioinformatic modeling predicted an outward-facing hPepT2 structure and a potential transport pathway, with polymyxins interacting at the lateral opening, particularly E214, D215, D317, D342, and E622. Transporter mutagenesis and molecular analyses confirmed that D215 is critical for polymyxin binding, while other residues influence transporter turnover and/or expression. We subsequently synthesized polymyxin analogs with modifications at Dab1, Dab3, Dab5, and Dab9 of polymyxins, which reduced interactions with hPepT2. Notably, alanine substitution at Dab3 reduced nephrotoxicity in mice while retaining antibacterial activity. Overall, this proof-of-concept study demonstrates that the hPepT2-polymyxin SIR model provides a viable strategy for developing novel, safer lipopeptide antibiotics.

Hyaluronate lyases have been widely used to degrade hyaluronic acid (HA) and prepare HA oligosaccharides. To date, no hyaluronate lyase has been reported in glycoside hydrolase family 56 (GH56). Herein, SpskHL from Sporothrix schenckii 1099-18 was first identified as a GH56 endolytic hyaluronate lyase, and then its four homologues were discovered. These five microbial GH56 enzymes cleaved HA, yielding unsaturated HA oligosaccharides with ΔHA2 as the end product, forming a new GH56 subfamily of endolytic hyaluronate lyase. Through alanine-scanning mutagenesis of 15 residues in the catalytic cleft of SpskHL and combining three positive mutations, triple-site mutant SpskHLM3 (Y120A/N125A/H189A) increased activity by 126%. Grafting of the triple-site mutation onto four other hyaluronate lyases increased their activities by 74%–155%. Molecular dynamics simulations suggested that all five triple-site mutants had an expanded catalytic cleft, a larger cavity near the catalytic residue E, and a shorter catalytic OE2-O4 distance, which might contribute to their enhanced activities.

One of the major causes for hospital acquired infections is multidrug-resistant Pseudomonas aeruginosa strains. Polymyxins are a group of lipopeptide antibiotics used as a last-line resort for treatment of Gram-negative infections. Polymyxins initially target Lipid A’s of lipopolysaccharides in the bacterial outer membrane via both electrostatic and hydrophobic interactions. Resistance to polymyxins in P. aeruginosa includes modification of Lipid A’s to attenuate the interactions with polymyxins but to date our understanding of underlying mechanisms is still limited. This study was conducted to investigate the molecular mechanisms of Polymyxin B1 interacting with outer membranes of P. aeruginosa strains including wild-type strain PAK (Polymyxin B1 MIC = 1 mg/L) control and treated and PAKpmrB6 strain (MIC = 8 mg/L) control and treated. Molecular models of PAK as well as PAKpmrB6 membranes were established, and each of those four membrane compositions were simulated as eight independent simulation systems, excluding and including six Polymyxin B1 molecules. The created membrane systems were evaluated running Molecular Dynamic (MD) Simulations for up to 1150 ns each. MD simulations showed that different membrane compositions and Polymyxin B1 interaction affect the general membrane behaviour. In addition, Polymyxin B1 interacts with mutant PAKpmrB6 membranes more slowly and penetrates them less deeply compared to non-mutant membranes. In summary, MD simulations of different membrane compositions provide insights at the membrane level that are consistent with the observed difference in Polymyxin B1 susceptibility between the PAK and PAKpmrB6 strains.

Background Multidrug-resistant (MDR) Gram-negative bacteria have presented a critical global health crisis and polymyxins remain a last-line therapy. However, their clinical use has been largely limited by nephrotoxicity. Human oligopeptide transporter 2 (hPepT2) is a membrane transporter mediating the reabsorption of polymyxins in renal cells, contributing to their nephrotoxicity. However, it remains unclear how polymyxins interact with hPepT2. Methods We investigated the structure-interaction relationship (SIR) of polymyxins with hPepT2 by integrating computational, chemical, and cell biology approaches. Bioinformatic modelling predicted the essential residues of hPepT2 for the binding to polymyxins. Transporter mutagenesis and molecular analysis were employed to examine the role of each residue in the interaction between hPepT2 and polymyxins. Subsequently, we synthesised a series of new analogues with alterations to the moieties of the polymyxin scaffold that are critical for binding with hPepT2, and assessed their antibacterial activity and nephrotoxicity. Results Our bioinformatic modelling proposed an outward-facing structure of hPepT2 with a possible transport pathway, in which polymyxins bind to the lateral opening site of hPepT2, particularly E214, D215, D317, D342, and E622. Molecular assays for transporter function and expression confirmed that D215 of hPepT2 is critical for polymyxin binding, while several other residues significantly impact transporter turnover rate and/or protein expression. Our experimental validations showed that the lipopeptides with alterations to the Dab1, Dab3, Dab5, and Dab9 residues of polymyxins demonstrated decreased interactions with hPepT2. Among these analogues, alanine substitution at Dab3 showed reduced nephrotoxicity in mice while retaining antibacterial activity. Conclusions Overall, this proof-of-concept study demonstrated that our SIR model of polymyxins with hPepT2 provides a viable approach for the discovery of novel, safer lipopeptide antibiotics.

Antimicrobial peptides (AMPs) are promising antibiotic alternatives, but current AI-based discovery often relies on sequence labels and lacks explicit modeling of peptide–membrane interactions. We developed Membrane-MaSIF, an MD-derived membrane surface matching model designed to capture peptide–membrane compatibility beyond sequence-level AMP labels. Using LL-37–perturbed Acinetobacter baumannii outer membranes, Membrane-MaSIF represents binding, insertion, and pore-like perturbation states as computable surface fingerprints encoding local geometry and physicochemical features. We further integrated Membrane-MaSIF with PepGraph-Diffusion for de novo AMP candidate generation and applied it to an external SPLUNC1 α4-derived A4 analogue library for known-scaffold prioritization. Experimental validation of selected candidates, including peptide 71 and high-scoring A4 analogues, supported the utility of membrane surface matching for enriching membrane-active antibacterial peptides. This framework provides a mechanism-aware strategy for Gram-negative AMP discovery and optimization.

Closely related G protein-coupled receptor (GPCR) subtypes often share highly conserved orthosteric pockets, making subtype-selective ligand development challenging. Here, we developed a five-agent workflow to systematically identify divergent protein-membrane-interface sites across class A GPCRs and exploit them for selective allosteric ligand discovery. By combining dMaSIF-derived surface fingerprints with Ballesteros-Weinstein (BW) position alignment, we compared structurally equivalent membrane-facing regions and identified the three most divergent hotspots for each of 163 receptor pairs. These regions showed substantial spatial overlap with experimentally characterized allosteric sites. Paired target-off-target screening of one million lead-like compounds, followed by detail-mode redocking and multi-seed consistency filtering, yielded 352 receptor-pair-specific candidates corresponding to 344 unique compounds across 104 receptor pairs. These candidates, together with their divergent sites and predicted selectivity profiles, were integrated into a searchable database. Our findings establish a scalable strategy for translating GPCR membrane-interface divergence into precise allosteric sites and testable subtype-selective ligand candidates.

Multidrug-resistant Gram-negative pathogens pose a major global medical challenge due to the lack of new antibiotics. Outer membrane vesicles (OMVs) in Gram-negative bacteria significantly contribute to their resistance to antimicrobial peptides (AMPs), particularly the lipopeptide polymyxins. However, how the structural organization of the OMV membranes influences AMP binding remains poorly understood. Here, we employed large-scale coarse-grained molecular dynamics simulations and enhanced sampling techniques to explore the structural dynamics of the OMV models and their interactions with polymyxins and other AMPs. Our results demonstrated that the separation of lipopolysaccharides (LPS) and phospholipids (PLs) occurred within the outer leaflet of the OMV models, forming LPS-rich regions, PL-rich regions, and LPS–PL interfaces. Interestingly, small geometric defects appeared at LPS–PL interfaces due to a mismatched orientation between LPS and PL molecules. These defects enhanced polymyxin binding to OMV models with folded conformations, in which their hydrophobic parts inserted into the PL-rich regions while the positively charged residues bound to the exposed phosphate groups of lipid A. Free energy calculations confirmed that polymyxins penetrated OMV models more effectively at LPS–PL interfaces than at LPS-rich regions. Importantly, this biased location at the LPS–PL interfaces was found across six other types of AMPs, including Melittin, LL-37, Magainin 2, Tachyplesin 1, Protegrin 1, and Capitellacin. Our findings suggest that the LPS–PL separation in the OMV models creates distinct microenvironments that favor AMP binding, particularly at LPS–PL interfaces. These mechanistic insights will inspire the design of novel AMPs that can evade the protective effect of the aforementioned OMVs.

Cellular membranes serve as selective barriers, and membrane permeability is crucial for drug pharmacokinetics. While in vitro and in vivo methods exist, predicting and designing membrane permeability remains challenging. We developed a thermodynamics-based deep learning framework to analyze the structure-permeability relationship, based on the concept that interactions between membrane lipids and small molecules influence permeability. We determined the membrane penetration thermodynamics of 8,239 compounds using coarse-grained molecular dynamics simulations and created interpretable graph neural network models to predict and design drug membrane permeability. As a proof-of-concept, we designed a novel nasal-administered melatonin analog, MT-A2, optimized for permeability. Compared with melatonin, MT-A2 showed superior nasal absorption, prolonged brain retention, and enhanced sleep efficacy. Our results provide a promising approach for predicting and designing membrane permeability, aiding in the development of drugs with better pharmacokinetics.

Background: Multidrug-resistant (MDR) Gram-negative bacteria have triggered a critical global health crisis. Polymyxin lipopeptide antibiotics are used as a last-line therapy against these problematic pathogens, but their clinical use is largely limited by severe nephrotoxicity. Human oligopeptide transporter 2 (hPepT2) is a membrane transporter mediating the reabsorption of polymyxins in renal proximal tubular cells, substantially contributing to their nephrotoxicity. However, it remains unclear how polymyxins interact with hPepT2. Methods: In this study, we investigated the structure-interaction relationship (SIR) of polymyxins with hPepT2 by integrating computational, chemical and cell biology approaches. Bioinformatic modelling predicted the residues essential for the binding of polymyxins with hPepT2. Transporter mutagenesis and molecular analysis were employed to explore the role of each residue in the interaction of hPepT2 and polymyxins. Moreover, we synthesised a series of polymyxin-like analogues with altering the moieties that are critical for binding with hPepT2. The antibacterial activity and nephrotoxicity of these analogues were subsequently assessed. Results: Our bioinformatic modelling proposed an outward-facing structure of hPepT2 with a possible transport pathway that polymyxins bind to the lateral opening site of hPepT2 (e.g. E214, D215, D317, D342, E622). Molecular assays for transporter function and expression confirmed that D215 residue of hPepT2 is critical for polymyxin binding, while several other residues significantly impact on transporter turnover rate and/or protein expression. Our experimental validations showed that the lipopeptide analogues with altering the Dab1, Dab3, Dab5 and Dab9 moieties of polymyxins demonstrated decreased interactions with hPepT2. Among these synthetic analogues, alanine substitution at Dab3 showed reduced nephrotoxicity in mice while reserved antibacterial activity against a range of bacterial strains. Conclusions: Overall, this proof-of-concept study demonstrated that the computationally predicted and experimentally validated polymyxin-hPepT2 SIR model provides a viable approach for the discovery of novel, safer lipopeptide antibiotics.