Explore the vast range of titles available.

Monkeypox is an emerging epidemic of concern. The disease is caused by the monkeypox virus and an increasing global incidence with a 2022 outbreak that has spread to Europe amid the COVID-19 pandemic. The new outbreak is associated with novel, previously undiscovered mutations and variants. Currently, the US Food and Drug Administration (FDA) approved poxvirus treatment involves the use of tecovirimat. However, there is otherwise limited pharmacopoeia and research interest in monkeypox. In this study, virtual screening and molecular dynamics were employed to explore the potential repurposing of multiple drugs previously approved by the FDA or other jurisdictions for other applications. Several drugs are predicted to tightly bind to viral proteins, which are crucial in viral replication, including molecules which show high potential for binding the monkeypox D13L capsid protein, whose inhibition has previously been demonstrated to suppress viral replication.

The mechanism of the antibiotic molecule A22 is yet to be clearly understood. In a previous study, we carried out molecular dynamics simulations of a monomer of the bacterial actin-like MreB in complex with different nucleotides and A22, and suggested that A22 impedes the release of Pi from the active site of MreB after the hydrolysis of ATP, resulting in filament instability. On the basis of the suggestion that Pi release occurs on a similar timescale to polymerization and that polymerization can occur in the absence of nucleotides, we sought in this study to investigate a hypothesis that A22 impedes the conformational change in MreB that is required for polymerization through molecular dynamics simulations of the MreB protofilament in the apo, ATP+, and ATP-A22+ states. We suggest that A22 inhibits MreB in part by antagonizing the ATP-induced structural changes required for polymerization. Our data give further insight into the polymerization/depolymerization dynamics of MreB and the mechanism of A22.

It has long been observed that trimethylamine N-oxide (TMAO) and urea demonstrate dramatically different properties in a protein folding process. Even with the enormous theoretical and experimental research work on these two osmolytes, various aspects of their underlying mechanisms still remain largely elusive. In this paper, we propose to use the weighted persistent homology to systematically study the osmolytes molecular aggregation and their hydrogen-bonding network from a local topological perspective. We consider two weighted models, i.e., localized persistent homology (LPH) and interactive persistent homology (IPH). Boltzmann persistent entropy (BPE) is proposed to quantitatively characterize the topological features from LPH and IPH, together with persistent Betti number (PBN). More specifically, from the localized persistent homology models, we have found that TMAO and urea have very different local topology. TMAO is found to exhibit a local network structure. With the concentration increase, the circle elements in these networks show a clear increase in their total numbers and a decrease in their relative sizes. In contrast, urea shows two types of local topological patterns, i.e., local clusters around 6 Å and a few global circle elements at around 12 Å. From the interactive persistent homology models, it has been found that our persistent radial distribution function (PRDF) from the global-scale IPH has same physical properties as the traditional radial distribution function. Moreover, PRDFs from the local-scale IPH can also be generated and used to characterize the local interaction information. Other than the clear difference of the first peak value of PRDFs at filtration size 4 Å, TMAO and urea also shows very different behaviors at the second peak region from filtration size 5 Å to 10 Å. These differences are also reflected in the PBNs and BPEs of the local-scale IPH. These localized topological information has never been revealed before. Since graphs can be transferred into simplicial complexes by the clique complex, our weighted persistent homology models can be used in the analysis of various networks and graphs from any molecular structures and aggregation systems.

The 3D structure of RNA critically influences its functionality, and understanding this structure is vital for deciphering RNA biology. Experimental methods for determining RNA structures are labour-intensive, expensive, and time-consuming. Computational approaches have emerged as valuable tools, leveraging physics-based-principles and machine learning to predict RNA structures rapidly. Despite advancements, the accuracy of computational methods remains modest, especially when compared to protein structure prediction. Deep learning methods, while successful in protein structure prediction, have shown some promise for RNA structure prediction as well, but face unique challenges. This study systematically benchmarks state-of-the-art deep learning methods for RNA structure prediction across diverse datasets. Our aim is to identify factors influencing performance variation, such as RNA family diversity, sequence length, RNA type, multiple sequence alignment (MSA) quality, and deep learning model architecture. We show that generally ML-based methods perform much better than non-ML methods on most RNA targets, although the performance difference isn’t substantial when working with unseen novel or synthetic RNAs. The quality of the MSA and secondary structure prediction both play an important role and most methods aren’t able to predict non-Watson-Crick pairs in the RNAs. Overall among the automated 3D RNA structure prediction methods, DeepFoldRNA has the best prediction results followed by DRFold as the second best method. Finally, we also suggest possible mitigations to improve the quality of the prediction for future method development.

Antimicrobial peptides (AMPs), also referred to as host defense peptides, are promising molecules in the development of the next generation of antibiotics against drug-resistant bacterial pathogens. Thanatin comprises a family of naturally occurring cationic AMPs derived from several species of insects. The first thanatin, 21 residues long, was identified from the spined soldier bug, and more thanatin peptides have been discovered in recent studies. The 16-residue thanatin from Anasa tristis, or Ana-thanatin, represents the shortest sequence in the family. However, the antimicrobial activity and mechanistic process underpinning bacterial cell killing have yet to be reported for Ana-thanatin peptide. In this work, we examined the antibacterial activity, structures, and target interactions of Ana-thanatin. Our results demonstrated that Ana-thanatin exerts potent antibiotic activity against strains of Gram-negative and Gram-positive bacteria. Biophysical studies demonstrated that Ana-thanatin interacts with LPS outer membrane and can permeabilize the OM barrier in the process. Atomic-resolution structures of the peptide in free solution and in complex with lipopolysaccharide (LPS) micelle were solved by NMR, determining canonical β-sheet structures. Notably, in complex with LPS, the β-sheet structure of the peptide was better defined in terms of the packing of amino acid residues. Further, MD simulations demonstrated rapid binding of the Ana-thanatin peptide with the LPS molecules within the lipid bilayers. These studies have revealed structural features which could be responsible for LPS-OM disruption of the Gram-negative bacteria. In addition, NMR heteronuclear single quantum coherence (HSQC) studies have demonstrated that Ana-thanatin can strongly interact with the LPS transport periplasmic protein LptAm, potentially inhibiting OM biogenesis. Taken together, we surmise that the Ana-thanatin peptide could serve as a template for the further development of novel antibiotics.

Previously we revealed that the extra domain of SARS 3CLpro mediated the catalysis via different mechanisms. While the R298A mutation completely abolished the dimerization, thus resulting in the inactive catalytic machinery, N214A inactivated the enzyme by altering its dynamics without significantly perturbing its structure. Here we studied another mutant with S284-T285-I286 replaced by Ala (STI/A) with a 3.6-fold activity increase and slightly enhanced dimerization. We determined its crystal structure, which still adopts the dimeric structure almost identical to that of the wild-type (WT), except for slightly tighter packing between two extra-domains. We then conducted 100-ns molecular dynamics (MD) simulations for both STI/A and WT, the longest reported so far for 3CLpro. In the simulations, two STI/A extra domains become further tightly packed, leading to a significant volume reduction of the nano-channel formed by residues from both catalytic and extra domains. The enhanced packing appears to slightly increase the dynamic stability of the N-finger and the first helix residues, which subsequently triggers the redistribution of dynamics over residues directly contacting them. This ultimately enhances the dynamical stability of the residues constituting the catalytic dyad and substrate-binding pockets. Further correlation analysis reveals that a global network of the correlated motions exists in the protease, whose components include all residues identified so far to be critical for the dimerization and catalysis. Most strikingly, the N214A mutation globally decouples this network while the STI/A mutation alters the correlation pattern. Together with previous results, the present study establishes that besides the classic structural allostery, the dynamic allostery also operates in the SARS 3CLpro, which is surprisingly able to relay the perturbations on the extra domain onto the catalytic machinery to manifest opposite catalytic effects. Our results thus imply a promising avenue to design specific inhibitors for 3CL proteases by disrupting their dynamic correlation network.

How the intra-Golgi secretory transport works remains a mystery. The cisternal progression and the stable compartment models have been proposed and are under debate. Classic cisternal progression model posits that both the intra-Golgi transport and Golgi exit of secretory cargos should occur at a constant velocity dictated by the cisternal progression; furthermore, COPI-mediated intra-Golgi retrograde transport is essential for maintaining the Golgi organization. Leveraging our recently developed Golgi imaging tools in nocodazole-induced Golgi ministacks, we found that the intra-Golgi transport velocity of a secretory cargo decreases during their transition from the cis to the trans -side of the Golgi, and different cargos exhibit distinct velocities even within the same cisternae. We observed a vast variation in the Golgi residence times of different cargos. Remarkably, truncation of the luminal domain causes the Golgi residence time of Tac — a standard transmembrane secretory cargo without intra-Golgi recycling signals — to extend from 16 min to a notable 3.4 hr. Additionally, when COPI-mediated intra-Golgi retrograde transport was inhibited by brefeldin A, we found that nocodazole-induced Golgi can remain stacked for over 30–60 min. Therefore, our findings challenge the classical cisternal progression model and suggest the stable compartment nature of the Golgi.

The treatment of bacterial infections is hindered by the presence of biofilms and metabolically inactive persisters. Here, we report the synthesis of an enantiomeric block co-beta-peptide, poly(amido-D-glucose)- block -poly(beta-L-lysine), with high yield and purity by one-shot one-pot anionic-ring opening (co)polymerization. The co-beta-peptide is bactericidal against methicillin-resistant Staphylococcus aureus (MRSA), including replicating, biofilm and persister bacterial cells, and also disperses biofilm biomass. It is active towards community-acquired and hospital-associated MRSA strains which are resistant to multiple drugs including vancomycin and daptomycin. Its antibacterial activity is superior to that of vancomycin in MRSA mouse and human ex vivo skin infection models, with no acute in vivo toxicity in repeated dosing in mice at above therapeutic levels. The copolymer displays bacteria-activated surfactant-like properties, resulting from contact with the bacterial envelope. Our results indicate that this class of non-toxic molecule, effective against different bacterial sub-populations, has promising potential for the treatment of S. aureus infections. The authors report the synthesis of an enantiomeric block co-beta-peptide that kills methicillin-resistant Staphylococcus aureus , including biofilm and persister bacterial cells, and disperses biofilms. The copolymer displays antibacterial activity in human ex vivo and mouse in vivo infection models without toxicity.

Cholesterol-enhanced pore formation is one evolutionary means cholesterol-free bacterial cells utilize to specifically target cholesterol-rich eukaryotic cells, thus escaping the toxicity these membrane-lytic pores might have brought onto themselves. Here, we present a class of artificial cholesterol-dependent nanopores, manifesting nanopore formation sensitivity, up-regulated by cholesterol of up to 50 mol% (relative to the lipid molecules). The high modularity in the amphiphilic molecular backbone enables a facile tuning of pore size and consequently channel activity. Possessing a nano-sized cavity of ~ 1.6 nm in diameter, our most active channel Ch-C1 can transport nanometer-sized molecules as large as 5(6)-carboxyfluorescein and display potent anticancer activity (IC 50  = 3.8 µM) toward human hepatocellular carcinomas, with high selectivity index values of 12.5 and >130 against normal human liver and kidney cells, respectively. Bacterial cells utilize cholesterol-enhanced pore formation to specifically target eukaryotic cells. Here, the authors present a class of bio-inspired, cholesterol-enhanced nanopores which display anticancer activities in vitro.

Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor can bind to different conformations of the binding site favorably was put forth, and related strategies to defeat this challenge were devised; reducing false positives when receptor plasticity is considered. The receptor in the study is the influenza A nucleoprotein, whose oligomerization is a requirement for RNA binding. The structural flexibility of influenza A nucleoprotein was explored by molecular dynamics simulations. The resultant distinctive structures and the crystal structure were used as receptor models in docking exercises in which two binding sites, the tail-loop binding pocket and the RNA binding site, were targeted with the Otava PrimScreen1 diversity-molecule library using the GOLD software. The intersection ligands that were listed in the top-ranked molecules from all receptor models were selected. Such selection strategy successfully distinguished high-affinity and low-affinity control molecules added to the molecule library. This work provides an applicable approach for reducing false positives and selecting true ligands from molecule libraries.