Confinement and Polarity Effects on the Peptide Packing Density on Mesoporous Silica Nanoparticles.

The adsorption of cationic peptide JM21 onto different mesoporous silica nanoparticles (MSNs) from an aqueous solution was studied as a function of pH. In agreement with the literature, the highest loading degrees could be achieved at pH close to the isoelectric point of the peptide where the peptide-peptide repulsion is minimum. However, mesopore size, mesopore geometry, and surface polarity all had an influence on the peptide adsorption in terms of both affinity and maximum loading at a given pH. This adsorption behavior could largely be explained by a combination of pH-dependent electrostatic interactions and confinement effects. It is demonstrated that hydrophobic interactions enhance the degree of peptide adsorption under pH conditions where the electrostatic attraction was absent in the case of mesoporous organosilica nanoparticles (MONs). The lower surface concentration of silanol groups for MON led to a lower level of peptide adsorption under optimum pH conditions compared to all-silica particles. Finally, the study confirmed the protective role of MSNs in preserving the biological activity of JM#21 against enzymatic degradation, even for large-pore MSNs, emphasizing their potential as nanocarriers for therapeutic peptides. By integrating experimental findings with theoretical modeling, this research elucidates the complex interplay of factors that influence peptide-silica interactions, providing vital insights for optimizing peptide loading and stabilization in biomedical applications.

Natural cystatin C fragments inhibit GPR15-mediated HIV and SIV infection without interfering with GPR15L signaling.

GPR15 is a G protein-coupled receptor (GPCR) proposed to play a role in mucosal immunity that also serves as a major entry cofactor for HIV-2 and simian immunodeficiency virus (SIV). To discover novel endogenous GPR15 ligands, we screened a hemofiltrate (HF)-derived peptide library for inhibitors of GPR15-mediated SIV infection. Our approach identified a C-terminal fragment of cystatin C (CysC95-146) that specifically inhibits GPR15-dependent HIV-1, HIV-2, and SIV infection. In contrast, GPR15L, the chemokine ligand of GPR15, failed to inhibit virus infection. We found that cystatin C fragments preventing GPR15-mediated viral entry do not interfere with GPR15L signaling and are generated by proteases activated at sites of inflammation. The antiretroviral activity of CysC95-146 was confirmed in primary CD4+ T cells and is conserved in simian hosts of SIV infection. Thus, we identified a potent endogenous inhibitor of GPR15-mediated HIV and SIV infection that does not interfere with the physiological function of this GPCR.

An Atomistic View of Platinum Cluster Growth on Pristine and Defective Graphene Supports.

Density functional theory (DFT) is used to systematically investigate the electronic structure of platinum clusters grown on different graphene substrates. Platinum clusters with 1 to 10 atoms and graphene vacancy defect supports with 0 to 5 missing C atoms are investigated. Calculations show that Pt clusters bind more strongly as the vacancy size increases. For a given defect size, increasing the cluster size leads to more endothermic energy of formation, suggesting a templating effect that limits cluster growth. The opposite trend is observed for defect-free graphene where the formation energy becomes more exothermic with increasing cluster size. Calculations show that oxidation of the defect weakens binding of the Pt cluster, hence it is suggested that oxygen-free graphene supports are critical for successful attachment of Pt to carbon-based substrates. However, once the combined material is formed, oxygen adsorption is more favorable on the cluster than on the support, indicating resistance to oxidative support degradation. Finally, while highly-symmetric defects are found to encourage formation of symmetric Pt clusters, calculations also reveal that cluster stability in this size range mostly depends on the number of and ratio between PtC, PtPt, and PtO bonds; the actual cluster geometry seems secondary.

Omicron: What Makes the Latest SARS-CoV-2 Variant of Concern So Concerning?

Emerging strains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19) pandemic, that show increased transmission fitness and/or immune evasion are classified as "variants of concern" (VOCs). Recently, a SARS-CoV-2 variant first identified in November 2021 in South Africa has been recognized as a fifth VOC, termed "Omicron." What makes this VOC so alarming is the high number of changes, especially in the viral Spike protein, and accumulating evidence for increased transmission efficiency and escape from neutralizing antibodies. In an amazingly short time, the Omicron VOC has outcompeted the previously dominating Delta VOC. However, it seems that the Omicron VOC is overall less pathogenic than other SARS-CoV-2 VOCs. Here, we provide an overview of the mutations in the Omicron genome and the resulting changes in viral proteins compared to other SARS-CoV-2 strains and discuss their potential functional consequences.

Potential-Dependent Pt(111)/Water Interface: Tackling the Challenge of a Consistent Treatment of Electrochemical Interfaces.

The interface between an electrode and an electrolyte is where electrochemical processes take place for countless technologically important applications. Despite its high relevance and intense efforts to elucidate it, a description of the interfacial structure and, in particular, the dynamics of the electric double layer at the atomic level is still lacking. Here we present reactive force-field molecular dynamics simulations of electrified Pt(111)/water interfaces, shedding light on the orientation of water molecules in the vicinity of the Pt(111) surface, taking into account the influence of potential, adsorbates, and ions simultaneously. We obtain a shift in the preferred orientation of water in the surface oxidation potential region, which breaks with the previously proclaimed strict correlation to the free charge density. Moreover, the characterization is complemented by course of the entropy and the intermolecular ordering in the interfacial region complements the characterization. Our work contributes to the ongoing process of understanding electric double layers and, in particular, the structure of the electrified Pt(111)/water interface, and aims to provide insights into the electrochemical processes occurring there.

In silico characterization of nanoparticles.

Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often require different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations.

Conformational States of the CXCR4 Inhibitor Peptide EPI-X4-A Theoretical Analysis.

EPI-X4, an endogenous peptide inhibitor, has exhibited potential as a blocker of CXCR4-a G protein-coupled receptor. This unique inhibitor demonstrates the ability to impede HIV-1 infection and halt CXCR4-dependent processes such as tumor cell migration and invagination. Despite its promising effects, a comprehensive understanding of the interaction between EPI-X4 and CXCR4 under natural conditions remains elusive due to experimental limitations. To bridge this knowledge gap, a simulation approach was undertaken. Approximately 150,000 secondary structures of EPI-X4 were subjected to simulations to identify thermodynamically stable candidates. This simulation process harnessed a self-developed reactive force field operating within the ReaxFF framework. The application of the Two-Phase Thermodynamic methodology to ReaxFF facilitated the derivation of crucial thermodynamic attributes of the EPI-X4 conformers. To deepen insights, an ab initio density functional theory calculation method was employed to assess the electrostatic potentials of the most relevant (i.e., stable) EPI-X4 structures. This analytical endeavor aimed to enhance comprehension of the inhibitor's structural characteristics. As a result of these investigations, predictions were made regarding how EPI-X4 interacts with CXCR4. Two pivotal requirements emerged. Firstly, the spatial conformation of EPI-X4 must align effectively with the CXCR4 receptor protein. Secondly, the functional groups present on the surface of the inhibitor's structure must complement the corresponding features of CXCR4 to induce attraction between the two entities. These predictive outcomes were based on a meticulous analysis of the conformers, conducted in a gaseous environment. Ultimately, this rigorous exploration yielded a suitable EPI-X4 structure that fulfills the spatial and functional prerequisites for interacting with CXCR4, thus potentially shedding light on new avenues for therapeutic development.

Simulations of the Oxidation and Degradation of Platinum Electrocatalysts.

Improved understanding of the fundamental processes leading to degradation of platinum nanoparticle electrocatalysts is essential to the continued advancement of their catalytic activity and stability. To this end, the oxidation of platinum nanoparticles is simulated using a ReaxFF reactive force field within a grand-canonical Monte Carlo scheme. 2-4 nm cuboctahedral particles serve as model systems, for which electrochemical potential-dependent phase diagrams are constructed from the thermodynamically most stable oxide structures, including solvation and thermochemical contributions. Calculations in this study suggest that surface oxide structures should become thermodynamically stable at voltages around 0.80-0.85 V versus standard hydrogen electrode, which corresponds to typical fuel cell operating conditions. The potential presence of a surface oxide during catalysis is usually not accounted for in theoretical studies of Pt electrocatalysts. Beyond 1.1 V, fragmentation of the catalyst particles into [Pt6 O8 ]4- clusters is observed. Density functional theory calculations confirm that [Pt6 O8 ]4- is indeed stable and hydrophilic. These results suggest that the formation of [Pt6 O8 ]4- may play an important role in platinum catalyst degradation as well as the electromotoric transport of Pt2+/4+ ions in fuel cells.

A Porphyrin Complex as a Self-Conditioned Electrode Material for High-Performance Energy Storage.

The novel functionalized porphyrin [5,15-bis(ethynyl)-10,20-diphenylporphinato]copper(II) (CuDEPP) was used as electrodes for rechargeable energy-storage systems with an extraordinary combination of storage capacity, rate capability, and cycling stability. The ability of CuDEPP to serve as an electron donor or acceptor supports various energy-storage applications. Combined with a lithium negative electrode, the CuDEPP electrode exhibited a long cycle life of several thousand cycles and fast charge-discharge rates up to 53 C and a specific energy density of 345 Wh kg-1 at a specific power density of 29 kW kg-1 . Coupled with a graphite cathode, the CuDEPP anode delivered a specific power density of 14 kW kg-1 . Whereas the capacity is in the range of that of ordinary lithium-ion batteries, the CuDEPP electrode has a power density in the range of that of supercapacitors, thus opening a pathway toward new organic electrodes with excellent rate capability and cyclic stability.

Hybrid nanoparticles by step-growth Sonogashira coupling in disperse systems.

Organic/inorganic hybrid nanoparticles were prepared by a Sonogashira miniemulsion polymerization of dibromo aryl and diethynyl aryl monomers and modified titanium dioxide and cadmium selenide nanocrystals, respectively. The poly(arylene ethynylene) microstructure and polymerization rates, as reflected by monomer reactivity, decisively impact whether inorganic guest particles can be trapped to afford a uniform distribution within a newly formed polymer particle or phase separate. This issue was found to be more critical for the TiO2 rods studied here. To this end, the compatibility of the organic and inorganic portions could be improved substantially by the incorporation of functional groups that bind the inorganic surface to the polymer via an appropriate termonomer. This concept, in combination with rapid particle formation via a postpolymerization dispersion of a premade poly(arylene ethynylene)/TiO2 composite as an alternative technique, yielded composite particles with a high loading of the inorganic nanoparticles.

Conjugated polymer composite nanoparticles by rapid mixing.

Composite nanoparticles from poly[(9,9-di-n-octylfluoren-2,7-diyl)-alt-(benzo[2,1,3]thiadiazol-4,8-diyl)] (F8BT) and poly(9,9-di-n-hexylfluoren-2,7-diyl) (PF) with embedded inorganic nanoparticles (TiO2 , CdSe, and CdSe/CdS) are prepared through kinetic trapping by rapid turbulent mixing in a multi-inlet vortex mixer without the need for polymer functionalization. High contents of inorganic materials up to 50-60 wt% are realized for all composites. The influence of flow ratios, sodium dodecyl sulfate (SDS) concentration, and absolute flow rates on the particle size and morphology is studied. High water-to-THF ratios and high total flow rates around 2 m s(-1) yield particle sizes below 50 nm. By adjusting these parameters, controlled particle sizes between 30 to several hundred nanometers are obtained. Composite particles from CdSe/CdS and F8BT or PF show a strong quenching of the polymer emission and near exclusive emission from the inorganic nanocrystal, which indicates an efficient energy transfer with fluorescence quantum yields of 23% for the F8BT/CdSe/CdS composites and 21% for the PF/CdSe/CdS composites. The dispersions are colloidally stable for several months.

Causes and Consequences of Coronavirus Spike Protein Variability.

Coronaviruses are a large family of enveloped RNA viruses found in numerous animal species. They are well known for their ability to cross species barriers and have been transmitted from bats or intermediate hosts to humans on several occasions. Four of the seven human coronaviruses (hCoVs) are responsible for approximately 20% of common colds (hCoV-229E, -NL63, -OC43, -HKU1). Two others (SARS-CoV-1 and MERS-CoV) cause severe and frequently lethal respiratory syndromes but have only spread to very limited extents in the human population. In contrast the most recent human hCoV, SARS-CoV-2, while exhibiting intermediate pathogenicity, has a profound impact on public health due to its enormous spread. In this review, we discuss which initial features of the SARS-CoV-2 Spike protein and subsequent adaptations to the new human host may have helped this pathogen to cause the COVID-19 pandemic. Our focus is on host forces driving changes in the Spike protein and their consequences for virus infectivity, pathogenicity, immune evasion and resistance to preventive or therapeutic agents. In addition, we briefly address the significance and perspectives of broad-spectrum therapeutics and vaccines.

Determinants of species-specific utilization of ACE2 by human and animal coronaviruses.

Utilization of human ACE2 allowed several bat coronaviruses (CoVs), including the causative agent of COVID-19, to infect humans directly or via intermediate hosts. However, the determinants of species-specific differences in ACE2 usage and the frequency of the ability of animal CoVs to use human ACE2 are poorly understood. Here we applied VSV pseudoviruses to analyze the ability of Spike proteins from 26 human or animal CoVs to use ACE2 receptors across nine reservoir, potential intermediate and human hosts. We show that SARS-CoV-2 Omicron variants evolved towards more efficient ACE2 usage but mutation of R493Q in BA.4/5 and XBB Spike proteins disrupts utilization of ACE2 from Greater horseshoe bats. Variations in ACE2 residues 31, 41 and 354 govern species-specific differences in usage by coronaviral Spike proteins. Mutation of T403R allows the RaTG13 bat CoV Spike to efficiently use all ACE2 orthologs for viral entry. Sera from COVID-19 vaccinated individuals neutralize the Spike proteins of various bat Sarbecoviruses. Our results define determinants of ACE2 receptor usage of diverse CoVs and suggest that COVID-19 vaccination may protect against future zoonoses of bat coronaviruses.

Determinants of Spike infectivity, processing, and neutralization in SARS-CoV-2 Omicron subvariants BA.1 and BA.2.

SARS-CoV-2 Omicron rapidly outcompeted other variants and currently dominates the COVID-19 pandemic. Its enhanced transmission and immune evasion are thought to be driven by numerous mutations in the Omicron Spike protein. Here, we systematically introduced BA.1 and/or BA.2 Omicron Spike mutations into the ancestral Spike protein and examined the impacts on Spike function, processing, and susceptibility to neutralization. Individual mutations of S371F/L, S375F, and T376A in the ACE2-receptor-binding domain as well as Q954H and N969K in the hinge region 1 impaired infectivity, while changes to G339D, D614G, N764K, and L981F moderately enhanced it. Most mutations in the N-terminal region and receptor-binding domain reduced the sensitivity of the Spike protein to neutralization by sera from individuals vaccinated with the BNT162b2 vaccine and by therapeutic antibodies. Our results represent a systematic functional analysis of Omicron Spike adaptations that have allowed this SARS-CoV-2 variant to dominate the current pandemic.

An increase in surface hydrophobicity mediates chaperone activity in N-chlorinated RidA.

Under physiological conditions, Escherichia coli RidA is an enamine/imine deaminase, which promotes the release of ammonia from reactive enamine/imine intermediates. However, when modified by hypochlorous acid (HOCl), it turns into a potent chaperone-like holdase that can effectively protect E. coli's proteome during oxidative stress. However, it is unknown, which residues need to be chlorinated for activation. Here, we employ a combination of LC-MS/MS analysis, a chemo-proteomic approach, and a mutagenesis study to identify residues responsible for RidA's chaperone-like function. Through LC-MS/MS of digested RidAHOCl, we obtained direct evidence of the chlorination of one arginine residue. To overcome the instability of the N-chloramine modification, we established a chemoproteomic approach using 5-(dimethylamino) naphthalene-1-sulfinic acid (DANSO2H) as a probe to label N-chlorinated lysines. Using this probe, we were able to detect the N-chlorination of six additional lysine residues. Moreover, using a mutagenesis study to genetically probe the role of single arginine and lysine residues, we found that the removal of arginines R105 and/or R128 led to a substantial reduction of RidAHOCl's chaperone activity. These results, together with structural analysis, confirm that the chaperone activity of RidA is concomitant with the loss of positive charges on the protein surface, leading to an increased overall protein hydrophobicity. Molecular modelling of RidAHOCl and the rational design of a RidA variant that shows chaperone activity even in the absence of HOCl further supports our hypothesis. Our data provide a molecular mechanism for HOCl-mediated chaperone activity found in RidA and a growing number of other HOCl-activated chaperones.

Did Dog Domestication Contribute to Language Evolution?

Different factors seemingly account for the emergence of present-day languages in our species. Human self-domestication has been recently invoked as one important force favoring language complexity mostly via a cultural mechanism. Because our self-domestication ultimately resulted from selection for less aggressive behavior and increased prosocial behavior, any evolutionary or cultural change impacting on aggression levels is expected to have fostered this process. Here, we hypothesize about a parallel domestication of humans and dogs, and more specifically, about a positive effect of our interaction with dogs on human self-domestication, and ultimately, on aspects of language evolution, through the mechanisms involved in the control of aggression. We review evidence of diverse sort (ethological mostly, but also archeological, genetic, and physiological) supporting such an effect and propose some ways of testing our hypothesis.

Spike residue 403 affects binding of coronavirus spikes to human ACE2.

The bat sarbecovirus RaTG13 is a close relative of SARS-CoV-2, the cause of the COVID-19 pandemic. However, this bat virus was most likely unable to directly infect humans since its Spike (S) protein does not interact efficiently with the human ACE2 receptor. Here, we show that a single T403R mutation increases binding of RaTG13 S to human ACE2 and allows VSV pseudoparticle infection of human lung cells and intestinal organoids. Conversely, mutation of R403T in the SARS-CoV-2 S reduces pseudoparticle infection and viral replication. The T403R RaTG13 S is neutralized by sera from individuals vaccinated against COVID-19 indicating that vaccination might protect against future zoonoses. Our data suggest that a positively charged amino acid at position 403 in the S protein is critical for efficient utilization of human ACE2 by S proteins of bat coronaviruses. This finding could help to better predict the zoonotic potential of animal coronaviruses.

Physiological pathways to rapid prosocial evolution.

Dogs (Canis lupus familiaris) descend from wolves (Canis lupus) sharing the same ecological niche of cooperative hunters, as humans. Initially, humans and wolves were competitors starting interspecific communication in order to avoid risk of injury. The evolutionary continuity of mammalian brains enabled interspecific prosocial contacts between both of them, which reduced stress, and enabled behavioral cultures leading to genetic isolation of those wolves. Dogs are the first domesticated animal living together with humans for about 25,000 years. Domestication means decreased aggression and flight distance toward humans, thus changes in the stress axis are crucial. The hypothesis of Active Social Domestication considers genetic selection as a necessary prediction but not a sufficient explanation of dog domestication. In addition, dog domestication is suggested to be an epigenetic disclosure. Due to changed stress activity, epigenetic mechanisms affect cerebral receptor activity and regulate transposon expressions, thus shaping brain function and behavior. Interspecific prosocial contacts initiated via serotonin release an enzymatic cascade enhancing, epigeneti-cally, the glucocorticoid negative feedback loop. Reduced chronic stress improved social learning capability and inhibitory control. Over time, those wolves could integrate themselves into human social structures, thus becoming dogs. In analogy, human mental skills, such as creating art and culture, might have also improved during the Upper Paleolithic.

Grand Canonical ReaxFF Molecular Dynamics Simulations for Catalytic Reactions.

In order to study the time-dependent behavior of catalytic systems during operation, we have developed a grand canonical molecular dynamics approach based on the ReaxFF reactive force-field framework. After describing the details of the implementation, the capabilities of this method are demonstrated by studying the gas-phase water formation from oxygen and hydrogen on platinum catalysts during the steady state where we discuss the effects of the surface structure as well as the importance of kinetics. The approach presented here can be extended to other dynamic (catalytic) systems, providing a framework for exploring catalytic and electrocatalytic processes, in particular, allowing studies on the effects of reaction conditions on a system's behavior, characteristics, and stability.

Towards quantitative treatment of electron pair distribution function.

The pair distribution function (PDF) is a versatile tool to describe the structure of disordered and amorphous materials. Electron PDF (ePDF) uses the advantage of strong scattering of electrons, thus allowing small volumes to be probed and providing unique information on structure variations at the nano-scale. The spectrum of ePDF applications is rather broad: from ceramic to metallic glasses and mineralogical to organic samples. The quantitative interpretation of ePDF relies on knowledge of how structural and instrumental effects contribute to the experimental data. Here, a broad overview is given on the development of ePDF as a structure analysis method and its applications to diverse materials. Then the physical meaning of the PDF is explained and its use is demonstrated with several examples. Special features of electron scattering regarding the PDF calculations are discussed. A quantitative approach to ePDF data treatment is demonstrated using different refinement software programs for a nanocrystalline anatase sample. Finally, a list of available software packages for ePDF calculation is provided.