ChemRxiv
Not a member yet
27047 research outputs found
Sort by
Native mass spectrometry reveals binding interactions of SARS-CoV-2 PLpro with inhibitors and ISG15
No full textHere we used native mass spectrometry (native MS) to probe a SARS-CoV protease, PLpro, which plays critical roles in coronavirus disease by affecting viral protein production and antagonizing host antiviral responses. Ultraviolet photodissociation (UVPD) and variable temperature electrospray ionization (vT ESI) were used to localize binding sites of PLpro inhibitors and revealed the stabilizing effects of inhibitors on protein tertiary structure. We compared PLpro from SARS-CoV-1 and SARS-CoV-2 in terms of inhibitor and ISG15 interactions to discern possible differences in protease function. A PLpro mutant lacking a single cysteine was used to localize inhibitor binding, and thermodynamic measurements revealed that inhibitor PR-619 stabilized the folded PLpro structure. These results will inform further development of PLpro as a therapeutic target against SARS-CoV-2 and other emerging coronaviruses
A microfluidic system for cultivation of cyanobacteria with precise light intensity and CO2 control: Enabling growth data acquisition at single-cell resolution.
No full textQuantification of cell growth is central to any study of photoautotrophic microorganisms. However, cellular self-shading and limited CO2 control in conventional photobioreactors lead to heterogeneous conditions that obscure distinct correlations between the environment and cellular physiology. Here we present a microfluidic cultivation platform that enables precise analysis of cyanobacterial growth with spatio-temporal resolution. Since cyanobacteria are cultivated in monolayers, cellular self-shading does not occur, allowing homogeneous illumination and precise knowledge of the photonflux density at single-cell resolution. A single chip contains multiple channels, each connected to several hundred growth chambers. In combination with an externally applied light gradient, this setup enables high-throughput multi-parameter analysis in short time. In addition, the multilayered microfluidic design allows continuous perfusion of defined gas mixtures. Transversal CO2 diffusion across the intermediate polydimethylsiloxane membrane results in homogeneous CO2 supply, with a unique exchange-surface to cultivation-volume ratio. Three cyanobacterial model strains were examined under various, static and dynamic environmental conditions. Phase-contrast and chlorophyllfluorescence images were recorded by automated time-lapse microscopy. Deep-learning trained cell segmentation was used to efficiently analyse large image stacks, thereby generating statistically reliable data. Cell division was highly synchronized, and growth was robust under continuous illumination but stopped rapidly upon initiating dark phases. CO2-limitation, often a limiting factor in photobioreactors, was only observed when the device was operated under reduced CO2 between 50 and 0 ppm. Here we provide comprehensive and precise data on cyanobacterial growth at single-cell resolution, accessible for further growth studies and modeling
Praseodymium in the Formal +5 Oxidation State
No full textThe pentavalent oxidation state of praseodymium – a long-sought connection between lanthanide, early-transition, and actinide metal redox chemistries – has only been identified in gas-phase or matrix isolation environments. We report the low-temperature characterization of a molecular praseodymium complex in the formal +5 oxidation state, [Pr5+(NP(tBu3)4][X–] (where tBu = tert-butyl and X– = tetrakis(pentafluorophenyl)borate or hexafluorophosphate). Single-crystal X-ray diffraction, solution-state spectroscopic, solution magnetometric, density functional theory, and multireference wavefunction-based methods indicate a highly multiconfigurational, singlet ground state. An inverted ligand field drives this unique electronic structure, which establishes a critical link in understanding the bonding of high-valent metal complexes across the periodic table
A combined experimental and computational exploration of heteroleptic cis-Pd2L2L’2 coordination cages through geometric complementarity
No full textHeteroleptic (mixed-ligand) coordination cages are of interest as host systems with more structurally and functionally complex cavities than homoleptic architectures. The design of heteroleptic cages, however, is far from trivial. In this work, we experimentally probed the self-assembly of Pd(II) ions with binary ligand combinations in a combinatorial fashion to search for new cis-Pd2L2L’2 heteroleptic cages. A hierarchy of computational analyses was then applied to these systems with the aim of elucidating key factors for rationalising self-assembly outcomes. Simple and inexpensive geometric analyses were shown to be effective in identifying complementary ligand pairs. Preliminary results demonstrated the viability of relatively rapid semi-empirical calculations for predicting the topology of thermodynamically favoured assemblies with rigid ligands, whilst more flexible systems proved challenging. Stemming from this, key challenges were identified for future work developing effective computational forecasting tools for self-assembled metallo-supramolecular systems
Electric fields imbue enzyme reactivity by aligning active site fragment orbitals
No full textIt is broadly recognized that intramolecular electric fields, produced by the protein scaffold and acting on the active site, facilitate enzymatic catalysis. This field effect can be described by several theoretical models, each of which is intuitive to varying degrees. In this contribution, we show that a fundamental effect of electric fields is to generate electrostatic potentials that facilitate the energetic alignment of reactant frontier orbitals. We apply this model to demystify the impact of electric fields on high-valent iron–oxo heme proteins: catalases, peroxidases, and peroxygenases/monooxygenases. Specifically, we show that this model easily accounts for the observed field-induced changes to the spin distribution within peroxidase active sites and explains the transition between epoxidation and hydroxylation pathways seen in Cytochrome P450 active site models. Thus, for the intuitive interpretation of the chemical effect of the field, the strategy involves analyzing the response of the orbitals of active site fragments, and their energetic alignment. We note that the energy difference between fragment orbitals involved in charge redistribution acts as a measure for the chemical hardness/softness of the reactive complex. This measure, and its sensitivity to electric fields, offers a single parameter model from which to quantitatively assess the effects of electric fields on reactivity and selectivity. Thus, the model provides an additional perspective to describe electrostatic preorganization and offers ways for its manipulation
SubTuner: a Physics-Guided Computational Tool for Modifying Enzymatic Substrate Preference and Its Application to Anion Methyltransferases
No full textEngineering enzymes to catalyze non-native substrates is critical for chemical synthesis and drug development. Although general-purpose computational tools exist, a significant challenge is to create a tool specialized in shifting an enzyme’s activity toward a specified non-native substrate. We developed SubTuner, a physics-guided computational tool that automates enzyme engineering for catalyzing desired non-native substrates. To test the performance of SubTuner, we designed three tasks – all aiming to identify beneficial anion methyltransferase mutants for synthesis of non-native S-adenosyl-L-methionine analogs: first in the conversion of ethyl iodide from a pool of 190 AtHOL1 single-point mutants for an initial test of accuracy and speed; second of ethyl iodide and n-propyl iodide from a pool of 600 acl-MT multi-point mutants for a test of generalizability; and eventually of bulkier substrates (n-propyl iodide, isopropyl iodide, and allyl iodide) combined with experimental characterization for a test of a priori predictivity. All the tests demonstrate SubTuner’s ability to accelerating the discovery of function-enhancing mutants for non-native substrates. Moreover, utilizing molecular simulation data derived from SubTuner, we elucidated how beneficial mutations promote catalysis. SubTuner, with its solid physical hypothesis, quantitative accuracy, and mechanism-informing ability, holds a significant potential to aid enzyme engineering for substrate scope expansion
Dimensional Analysis of Diffusive Association Rate Equations
No full textDiffusive adsorption/association is a fundamental step in almost all chemical reactions in diluted solutions, such as organic synthesis, polymerization, self-assembly, biomolecular interactions, electrode dynamics, catalysis, chromatography, air and water environmental dynamics, and social and market dynamics. However, predicting the rate of such a reaction is challenging using the equations established over 100 years ago. From dimensional analysis, we can guess a series of equations including historical ones and new ones that have the correct final unit, the number of molecules associated per second, which is constructed from concentration, diffusion coefficient, and size of the molecules only. These equations are roughly divided into two groups, continuous models and discrete models. The continuous models integrate Fick’s concentration gradient in the solution near the target to calculate the association rate, and are the historical solutions reported. The discrete models integrate the probability density function of each probe that is discretely distributed in the solution. I have introduced a key concept of the nearest neighbor diffusion time to stabilize these time-dependent solutions. These models are applied to analyze a set of experimental results for comparison to achieve consistency and clarify assumptions among models
PathInHydro, a set of machine learning models to identify unbinding pathways of gas molecules in [NiFe] hydrogenases
No full textMachine learning (ML) is a powerful tool for the automated data analysis of molecular dynamics (MD) simulations. Recent studies showed that ML models can be used to identify protein-ligand unbinding pathways and understand the underlying mechanism. To expedite the examination of MD simulations, we constructed PathInHydro, a set of supervised ML models capable of automatically assigning unbinding pathways for the dissociation of gas molecules from the [NiFe] hydrogenases, using the unbinding trajectories of CO from Desulfovibrio fructosovorans [NiFe] hydrogenase as a training set. [NiFe] hydrogenases are receiving increasing attention in biotechnology due to their high efficiency in the generation of H2, which is considered by many to be the fuel of the future. However, some of these enzymes are sensitive to O2 and CO. Many efforts have been made to rectify this problem and generate air-stable enzymes by introducing mutations that selectively regulate the access of specific gas molecules to the catalytic site. Herein, we showcase the performance of PathInHydro for the identification of unbinding paths in different test sets, including various gas molecules and a different [NiFe] hydrogenase, which demonstrates its feasibility for the trajectory analysis of a diversity of gas molecules along enzymes with mutations and sequence differences. PathInHydro allows the user to skip time-consuming manual analysis and visual inspection, facilitating data analysis for MD simulations of ligand unbinding from [NiFe] hydrogenases. The codes and data sets are available online: https://github.com/FarzinSohraby/PathInHydro
2D Interfacial Crystallization Stabilized by Short-Chain Aliphatic Interfaces
No full textWe report the formation of interface sealing crystalline sheets based on amino acid and peptoid-monomer amphiphiles. This process, interfacial crystallization (IFC), is demonstrated using a range of halide salts of amidated peptoid monomers and amino acid amide bases with varied aliphatic sidechains. In our investigation, we identified that sufficient dynamic freedom of attached sidechains is a crucial design principle underpinning the viability of IFC for a given molecule. In addition, our results indicated that a combination of ionic coordination, hydrogen bonding and dispersion interactions all contribute significantly to the formation of these structures, and they are consistent with a hypothesis of interfacial ion migration playing a critical role in structure formation. A comprehensive range of techniques, including AFM, FT-IR, TOF-SIMs, X-ray crystallography, salt exchange experiments, quantum mechanical (QM) calculations and molecular dy-namics (MD) simulation studies were used to characterize this phenomenon. The formation of these hierarchical nanostructures, and the simplicity of the chemistry involved, suggests that IFC may have applications in formation of 2D supramolecular materials and barriers
Bimetallic Synergy in Ru−Pt Alloy Catalyst for Polyethylene Hydrogenolysis
No full textHydrogenolysis of low-density polyethylene (LDPE) under low pressure of H2 has been accomplished with a Ru−Pt bimetallic alloy catalyst. Using Ru5Pt1/CeO2 (atomic ratio of Ru to Pt is 5:1) as a catalyst, LDPE was efficiently converted (99% conversion) to gas and liquid hydrocarbons under 5 bar of H2 at 200 °C. This is contrastive to the 55% conversion with Ru/CeO2 and <1% conversion with Pt/CeO2 under the same reaction conditions. Mechanistic studies suggested that the higher activity of Ru5Pt1/CeO2 can be attributed to the synergistic effect of Ru (cleavage of C−C bond) and Pt (acceleration of Ru−alkyl hydrogenation step) on the catalyst surface