Marshallpatterson1163

Coronaviruses may produce severe acute respiratory syndrome (SARS). As a matter of fact, a new SARS-type virus, SARS-CoV-2, is responsible for the global pandemic in 2020 with unprecedented sanitary and economic consequences for most countries. In the present contribution we study, by all-atom equilibrium and enhanced sampling molecular dynamics simulations, the interaction between the SARS Unique Domain and RNA guanine quadruplexes, a process involved in eluding the defensive response of the host thus favoring viral infection of human cells. Our results evidence two stable binding modes involving an interaction site spanning either the protein dimer interface or only one monomer. The free energy profile unequivocally points to the dimer mode as the thermodynamically favored one. The effect of these binding modes in stabilizing the protein dimer was also assessed, being related to its biological role in assisting the SARS viruses to bypass the host protective response. check details This work also constitutes a first step in the possible rational design of efficient therapeutic agents aiming at perturbing the interaction between SARS Unique Domain and guanine quadruplexes, hence enhancing the host defenses against the virus.High-throughput computational screening typically employs methods (i.e., density functional theory or DFT) that can fail to describe challenging molecules, such as those with strongly correlated electronic structure. In such cases, multireference (MR) correlated wavefunction theory (WFT) would be the appropriate choice but remains more challenging to carry out and automate than single-reference (SR) WFT or DFT. Numerous diagnostics have been proposed for identifying when MR character is likely to have an effect on the predictive power of SR calculations, but conflicting conclusions about diagnostic performance have been reached on small data sets. We compute 15 MR diagnostics, ranging from affordable DFT-based to more costly MR-WFT-based diagnostics, on a set of 3165 equilibrium and distorted small organic molecules containing up to six heavy atoms. Conflicting MR character assignments and low pairwise linear correlations among diagnostics are also observed over this set. We evaluate the ability of existing diagnostics to predict the percent recovery of the correlation energy, %Ecorr. None of the DFT-based diagnostics are nearly as predictive of %Ecorr as the best WFT-based diagnostics. To overcome the limitation of this cost-accuracy trade-off, we develop machine learning (ML, i.e., kernel ridge regression) models to predict WFT-based diagnostics from a combination of DFT-based diagnostics and a new, size-independent 3D geometric representation. The ML-predicted diagnostics correlate as well with MR effects as their computed (i.e., with WFT) values, significantly improving over the DFT-based diagnostics on which the models were trained. These ML models thus provide a promising approach to improve upon DFT-based diagnostic accuracy while remaining suitably low cost for high-throughput screening.We propose a computationally lean, two-stage approach that reliably predicts self-assembly behavior of complex charged molecules on metallic surfaces under electrochemical conditions. Stage one uses ab initio simulations to provide reference data for the energies (evaluated for archetypical configurations) to fit the parameters of a conceptually much simpler and computationally less expensive force field of the molecules classical, spherical particles, representing the respective atomic entities; a flat and perfectly conducting wall represents the metallic surface. Stage two feeds the energies that emerge from this force field into highly efficient and reliable optimization techniques to identify via energy minimization the ordered ground-state configurations of the molecules. We demonstrate the power of our approach by successfully reproducing, on a semiquantitative level, the intricate supramolecular ordering observed experimentally for PQP+ and ClO4- molecules at an Au(111)-electrolyte interface, including the formation of open-porous, self-host-guest, and stratified bilayer phases as a function of the electric field at the solid-liquid interface. We also discuss the role of the perchlorate ions in the self-assembly process, whose positions could not be identified in the related experimental investigations.The development of highly active and durable catalysts for electrochemical reduction of CO2 (ERC) to CH4 in aqueous media is an efficient and environmentally friendly solution to address global problems in energy and sustainability. In this work, an electrocatalyst consisting of single Zn atoms supported on microporous N-doped carbon was designed to enable multielectron transfer for catalyzing ERC to CH4 in 1 M KHCO3 solution. This catalyst exhibits a high Faradaic efficiency (FE) of 85%, a partial current density of -31.8 mA cm-2 at a potential of -1.8 V versus saturated calomel electrode, and remarkable stability, with neither an obvious current drop nor large FE fluctuation observed during 35 h of ERC, indicating a far superior performance than that of dominant Cu-based catalysts for ERC to CH4. Theoretical calculations reveal that single Zn atoms largely block CO generation and instead facilitate the production of CH4.Relaxometric analyses and in particular the use of fast-field cycling techniques have become routine in the study of paramagnetic metal complexes. The field dependence of the solvent proton relaxation properties (nuclear magnetic relaxation dispersion, NMRD) can provide unparalleled insights into the chemistry of these complexes. However, analyzing NMRD data is a multiparametric problem, and some sets of variables are mutually compensatory. Specifically, when fitting NMRD profiles, the metal-proton distance and the rotational correlation time constant have a push-pull relationship in which a change to one causes a predictable compensation in the other. A relaxometric analysis of four isomeric chelates highlights the pitfalls that await when fitting the NMRD profiles of chelates for which dissociative water exchange is extremely rapid. In the absence of independently verified values for one of these parameters, NMRD profiles can be fitted to multiple parameter sets. This means that NMRD fitting can inadvertently be used to buttress a preconceived notion of how the complex should behave when a different parameter set may more accurately describe the actual behavior. These findings explain why the effect of very rapid dissociative exchange on the hydration state of Gd3+ has remained obscured until only recently.Herein we present a Bi-catalyzed cross-coupling of arylboronic acids with perfluoroalkyl sulfonate salts based on a Bi(III)/Bi(V) redox cycle. An electron-deficient sulfone ligand proved to be key for the successful implementation of this protocol, which allows the unusual construction of C(sp2)-O bonds using commercially available NaOTf and KONf as coupling partners. Preliminary mechanistic studies as well as theoretical investigations reveal the intermediacy of a highly electrophilic Bi(V) species, which rapidly eliminates phenyl triflate.The development of a π-conjugated polymer with hydrogen-bonding moieties has aroused great attention because of the improved molecular stacking and the hydrogen-bonding network. In this study, PDPPTVT (diketopyrrolopyrrole-thiophenevinylenethiophene) and PDPPSe (diketopyrrolopyrrole-selenophene) alkylated with a carbosilane (SiC8) side chain and poly(acryl amide) (PAM)-incorporated alkyl side chain were prepared, and their structure-performance and structure-stretchability correlation were evaluated. By incorporating the DPPTVT backbone and 0, 5, 10, or 20% PAM-incorporated alkyl side chain, the μh value could reach 2.0, 0.97, 0.74, and 0.42 cm2 V-1 s-1, respectively (P1 to P4). The polymer with the PDPPSe backbone and 5% PAM-incorporated alkyl side-chain (P5) exhibited the maximum μh value of 0.96 cm2 V-1 s-1. By extending the PAM moiety from the backbone with alkyl spacers, the solid-state packing and edge-on orientation can be properly maintained. Surprisingly, the PAM-incorporated alkyl side-chain can propromising approach to promote the intrinsic stretchability of the π-conjugated polymers.Ultraviolet photodissociation (UVPD) experiments of protonated tryptamine ([Tryp+H]+) have been implemented by a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer combined with a wavelength-tunable optical parametric oscillator (OPO) laser. UVPD mass spectra under different laser wavelengths have been obtained, in which the dependence of the yield of fragment ions on the laser wavelength was observed. The UVPD spectrum of [Tryp+H]+ has been obtained in the range of 210-310 nm. Besides the previously reported two competitive channels of H loss and NH3 loss, two important channels of losing CH2NH and CH2NH2 units were observed and further studied by UV-UV tandem mass spectrometry and theoretical calculations. Interestingly, results show that the pair of competitive channels of CH2NH loss and CH2NH2 loss are both from the McLafferty-type rearrangement caused by ππ* electronic excited states. After the excitation, the two different dissociation pathways produce two different ion-neutral complexes, respectively. The wavelength-dependent dissociation and the existing competitive channels shown in this study reflect the diversity of UVPD processes of such organic molecules.Constructing yolk-shell-structured non-noble-metal composites is very important for improving their activity and stability in catalytic performance. Herein, we report a facile strategy for the synthesis of ternary Cu@SiO2@C yolk-shell composites by converting the resorcinol-formaldehyde (RF) resin-coated Cu2O@SiO2 with a core-shell structure via a thermal treatment under a N2 atmosphere. Notably, the annealing temperature and silica interlayer play vital roles in modulating their structures and catalytic performance. Moreover, this strategy may pave a new way to constructing non-noble-metal-based composites with yolk-shell structures.Amyloid β-peptide oligomer (AβO) is widely acknowledged as the promising biomarker for the diagnosis of Alzheimer's disease (AD). In this work, we designed a three-dimensional (3D) DNA walker nanoprobe for AβO detection and real-time imaging in living cells and in vivo. The presence of AβO triggered the DNAzyme walking strand to cleave the fluorophore (TAMRA)-labeled substrate strand modified on the gold nanoparticle (AuNP) surface and release TAMRA-labeled DNA fragment, resulting in the recovery of fluorescent signal. The entire process was autonomous and continuous, without external fuel strands or protease, and finally produced plenty of TAMRA fluorescence, achieving signal amplification effect. The nanoprobe enabled the quantitative detection of AβO in vitro, and the limit of detection was 22.3 pM. Given the good biocompatibility of 3D DNA walker nanoprobe, we extended this enzyme-free signal amplification method to real-time imaging of AβO. Under the microscope, nanoprobe accurately located and visualized the distribution of AβO in living cells. Moreover, in vivo imaging results showed that our nanoprobe could be used to effectively distinguish the AD mice from the wild-type mice. This nanoprobe with the advantages of great sensitivity, high specificity, and convenience, provides an outstanding prospect for AD's early diagnosis development.