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Tight junctions are cell-cell adhesion complexes that act as gatekeepers of the paracellular space. Formed by several transmembrane proteins, the claudin family performs the primary gate-keeping function. The claudin proteins form charge and size-selective diffusion barriers to maintain homeostasis across endothelial and epithelial tissue. Of the 27 known claudins in mammals, some are known to seal the paracellular space, while others provide selective permeability. The differences in permeability arise due to the varying expression levels of claudins in each tissue. The tight junctions are observed as strands in freeze-fracture electron monographs; however, at the molecular level, tight junction strands form when multiple claudin proteins assemble laterally (cis assembly) within a cell and head-on (trans assembly) with claudins of the adjacent cell in a zipper-like architecture, closing the gap between the neighboring cells. The disruption of tight junctions caused by changing claudin expression levels or mutations can lead to diseases. Therefore, knowledge of the molecular architecture of the tight junctions and how that is tied to tissue-specific function is critical for fighting diseases. Here, we review the current understanding of the tight junctions accrued over the last three decades from experimental and computational biophysics perspectives. 

Biology exploits biomacromolecular phase separation to form condensates, known as membraneless organelles. Despite significant advancements in deciphering sequence determinants for phase separation, modulating these features in vivo remains challenging. A promising approach inspired by biology is to use post-translational modifications (PTMs)—to modulate the amino acid physicochemistry instead of altering protein sequences—to control the formation and characteristics of condensates. However, despite the identification of more than 300 types of PTMs, the detailed understanding of how they influence the formation and material properties of protein condensates remains incomplete. In this study, we investigated how modification with myristoyl lipid alters the formation and characteristics of the resilin-like polypeptide (RLP) condensates, a prototypical disordered protein with upper critical solution temperature (UCST) phase behaviour. Using turbidimetry, dynamic light scattering, confocal and electron microscopy, we demonstrated that lipidation—in synergy with the sequence of the lipidation site—significantly influences RLPs' thermodynamic propensity for phase separation and their condensate properties. Molecular simulations suggested these effects result from an expanded hydrophobic region created by the interaction between the lipid and lipidation site rather than changes in peptide rigidity. These findings emphasize the role of “sequence context” in modifying the properties of PTMs, suggesting that variations in lipidation sequences could be strategically used to fine-tune the effect of these motifs. Our study advances understanding of lipidation's impact on UCST phase behaviour, relevant to proteins critical in biological processes and diseases, and opens avenues for designing lipidated resilins for biomedical applications like heat-mediated drug elution. 

We have been studying the complexation between cationic antimicrobials and polyanionic microgels to create self-defensive surfaces that responsively resist bacterial colonization. An essential property is the stable sequestration of the loaded (complexed) antimicrobial within the microgel under physiological ionic strength. Here we assess the complexation strength between poly(acrylic acid) [PAA] microgels and a series of cationic peptoids that display supramolecular structures ranging from an oligomeric monomer to a tetramer. We follow changes in loaded microgel diameter with increasing [Na+] as a measure of the counterion doping level. Consistent with prior findings on colistin/PAA complexation, we find that a monomeric peptoid is fully released at ionic strengths well below physiological conditions despite its +5 charge. In contrast, progressively higher degrees of peptoid supramolecular structure display progressively greater resistance to salting out, which we attribute to the greater entropic stability associated with the complexation of multimeric peptoid bundles. 

Bacterial colonization of biotic and abiotic surfaces and antibiotic resistance are grand challenges with paramount societal impacts. However, in the face of increasing bacterial resistance to all known antibiotics, efforts to discover new classes of antibiotics have languished, creating an urgent need to accelerate the antibiotic discovery pipeline. A major deterrent in the discovering of new antibiotics is the limited permeability of molecules across the bacterial envelope. Notably, the Gram-negative bacteria have nutrient specific protein channels (or porins) that restrict the permeability of non-essential molecules, including antibiotics. Here, we have developed the Computational Antibiotic Screening Platform (CLASP) for screening of potential drug molecules through the porins. The CLASP takes advantage of coarse grain (CG) resolution, advanced sampling techniques, and a parallel computing environment to maximize its performance. The CLASP yields comprehensive thermodynamic and kinetic output data of a potential drug molecule within a few hours of wall-clock time. Its output includes the potential of mean force profile, energy barrier, the rate constant, and contact analysis of the molecule with the pore-lining residues, and the orientational analysis of the molecule in the porin channel. In our first CLASP application, we report the transport properties of six carbapenem antibiotics—biapenem, doripenem, ertapenem, imipenem, meropenem, and panipenem—through OccD3, a major channel for carbapenem uptake in Pseudomonas aeruginosa . The CLASP is designed to screen small molecule libraries with a fast turnaround time to yield structure–property relationships to discover antibiotics with high permeability. The CLASP will be freely distributed to enable accelerated antibiotic drug discovery. 

In the Big Data era, a change of paradigm in the use of molecular dynamics is required. Trajectories should be stored under FAIR (findable, accessible, interoperable and reusable) requirements to favor its reuse by the community under an open science paradigm. 

Integral membrane proteins represent a large and diverse portion of the proteome and are often recalcitrant to purification, impeding studies essential for understanding protein structure and function. By combining co-evolutionary constraints and computational modeling with biochemical validation through site-directed mutagenesis and enzyme activity assays, we demonstrate here a synergistic approach to structurally model purification-resistant topologically complex integral membrane proteins. We report the first structural model of a eukaryotic membrane-bound O-acyltransferase (MBOAT), ghrelin O-acyltransferase (GOAT), which modifies the metabolism-regulating hormone ghrelin. Our structure, generated in the absence of any experimental structural data, revealed an unanticipated strategy for transmembrane protein acylation with catalysis occurring in an internal channel connecting the endoplasmic reticulum lumen and cytoplasm. This finding validated the power of our approach to generate predictive structural models for other experimentally challenging integral membrane proteins. Our results illuminate novel aspects of membrane protein function and represent key steps for advancing structure-guided inhibitor design to target therapeutically important but experimentally intractable membrane proteins.