Nuclear Magnetic Resonance Chemical Shifts Research Articles

Refined Analysis of the Crystal Structure, Thermodynamic Property, and Structural Geometry of Perovskite (CH3NH3)2ZnBr4.

Organic-inorganic hybrid single crystals of (CH3NH3)2ZnBr4 were grown by the aqueous solution technique, and their structure, phase transition temperature, and thermal stability were discussed. The crystals were determined to have a monoclinic structure using X-ray diffraction on single crystals, and a transition temperature of 458 K was confirmed from the differential scanning calorimetry and X-ray diffraction analyses on powders. Moreover, the compound exhibited excellent thermal stabilities up to 550 K. The 1H and 13C nuclear magnetic resonance chemical shifts of CH3 shifted in the positive direction as the temperature increased, while the 1H chemical shift of NH2 exhibited minor variations in N-H···Br hydrogen bonding, which was influenced by minor changes in the bromide ions surrounding Zn in the ZnBr4 anion. The spin-lattice relaxation time, which indicates the energy transfer near 1H and 13C, exhibited similar values, which is because 1H and 13C are bonded to each other in the CH3NH3 cation. This compound exhibits high structural and thermal stabilities and is expected to pave the way for future applications.

Quelling the Geometry Factor Effect in Quantum Chemical Calculations of 13C NMR Chemical Shifts with the Aid of the pecG-n (n = 1, 2) Basis Sets

A root factor for the accuracy of all quantum chemical calculations of nuclear magnetic resonance (NMR) chemical shifts is the quality of the molecular equilibrium geometry used. In turn, this quality depends largely on the basis set employed at the geometry optimization stage. This parameter represents the main subject of the present study, which is a continuation of our recent work, where new pecG-n (n = 1, 2) basis sets for the geometry optimization were introduced. A goal of this study was to compare the performance of our geometry-oriented pecG-n (n = 1, 2) basis sets against the other basis sets in massive calculations of 13C NMR shielding constants/chemical shifts in terms of their efficacy in reducing geometry factor errors. The testing was carried out with both large-sized biologically active natural products and medium-sized compounds with complicated electronic structures. The former were treated using the computation protocol based on the density functional theory (DFT) and considered in the theoretical benchmarking, while the latter were treated using the computational scheme based on the upper-hierarchy coupled cluster (CC) methods and were used in the practical benchmarking involving the comparison with experimental NMR data. Both the theoretical and practical analyses showed that the pecG-1 and pecG-2 basis sets resulted in substantially reduced geometry factor errors in the calculated 13C NMR chemical shifts/shielding constants compared to their commensurate analogs, with the pecG-2 basis set being the best of all the considered basis sets.

Integrative Modeling of Protein-Polypeptide Complexes by Bayesian Model Selection using AlphaFold and NMR Chemical Shift Perturbation Data.

Protein-polypeptide interactions, including those involving intrinsically-disordered peptides and intrinsically-disordered regions of protein binding partners, are crucial for many biological functions. However, experimental structure determination of protein-peptide complexes can be challenging. Computational methods, while promising, generally require experimental data for validation and refinement. Here we present CSP_Rank, an integrated modeling approach to determine the structures of protein-peptide complexes. This method combines AlphaFold2 (AF2) enhanced sampling methods with a Bayesian conformational selection process based on experimental Nuclear Magnetic Resonance (NMR) Chemical Shift Perturbation (CSP) data and AF2 confidence metrics. Using a curated dataset of 108 protein-peptide complexes from the Biological Magnetic Resonance Data Bank (BMRB), we observe that while AF2 typically yields models with excellent consistency with experimental CSP data, applying enhanced sampling followed by data-guided conformational selection routinely results in ensembles of structures with improved agreement with NMR observables. For two systems, we cross-validate the CSP-selected models using independently acquired nuclear Overhauser effect (NOE) NMR data and demonstrate how CSP and NMR can be combined using our Bayesian framework for model selection. CSP_Rank is a novel method for integrative modeling of protein-peptide complexes and has broad implications for studies of protein-peptide interactions and aiding in understanding their biological functions.

Experimental and Computational 77Se NMR Spectroscopic Study on Selenaborane Cluster Compounds.

Calculated and measured 77Se nuclear magnetic resonance (NMR) chemical shift data on a diverse collection of 13 selenaborane cluster compounds, containing a total of 19 selenium centers, reveals a correlation between chemical shifts and the intracluster coordination of selenium atoms within their borane frameworks. A plot of the measured against calculated 77Se NMR chemical shifts shows an approximately linear relationship that can serve as a predictive tool in assessing the chemical shift range in which a selenium vertex from a particular compound might be expected to be found, thereby reducing expensive experimental time. Furthermore, the relative chemical shifts between selenium vertices in clusters containing more than one selenium atom are consistent across the range, thus allowing the assignment of the selenium resonances with a high degree of confidence even in relatively low-level density functional theory calculations. A new macropolyhedral 20-vertex selenaborane Se2B18H20 (A) is also reported.

Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networks.

Carbohydrates, vital components of biological systems, are well-known for their structural diversity. Nuclear Magnetic Resonance (NMR) spectroscopy plays a crucial role in understanding their intricate molecular arrangements and is essential in assessing and verifying the molecular structure of organic molecules. An important part of this process is to predict the NMR chemical shift from the molecular structure. This work introduces a novel approach that leverages E(3) equivariant graph neural networks to predict carbohydrate NMR spectral data. Notably, our model achieves a substantial reduction in mean absolute error, up to threefold, compared to traditional models that rely solely on two-dimensional molecular structure. Even with limited data, the model excels, highlighting its robustness and generalization capabilities. The model is dubbed GeqShift (geometric equivariant shift) and uses equivariant graph self-attention layers to learn about NMR chemical shifts, in particular since stereochemical arrangements in carbohydrate molecules are characteristics of their structures.

Computational and experimental characterisation of a new (R)-camphor-Thiazolidinone derivative: A combined approach for structure optimisation and activity prediction

This study describes the synthesis, characterisation, in-silico exploration, and theoretical investigation of a novel 5-Methyl-2-(((1S,4R)-1,7,7-trimethylbicyclo[2.2.1]heptan-2-ylidene)hydrazono)thiazolidin-4-one 3. The structure of the synthesised derivative was successfully confirmed using high-resolution mass spectrometry (HRMS) and 1H and 13C nuclear magnetic resonance (NMR) spectroscopy. In addition, a concise theoretical study was employed to elucidate the experimentally observed stability of the compound. On the computational level, this investigation utilised DFT, molecular docking, and molecular dynamics simulations for the (R)-camphor-thiazolidinone derivative. The optimised structure of compound 3 was predicted with the DFT/B3LYP method with the 6–311++G(d,p) basis set. The theoretical vibrational modes were assigned and found to be consistent with the observed FT-IR spectrum. The simulated NMR values exhibited good agreement with the experimental NMR chemical shifts, with the deviations of 0.5113 and 3.816 ppm for the 1H and 13C, respectively. The UV–vis spectra indicated the n → π* and π → π* transitions in compound 3, with confirmation of intermolecular charge transfer (ICT) from the FMOs and NBO analyses. The MEP surface, Mulliken, and NPA analyses confirm the presence of reactive sites within compound 3. NCI-RDG studies revealed the presence of van der Waals (vdW) interactions and the absence of hydrogen bonding within the studied molecule. The molecular docking analysis indicates that compound 3 exhibits a strong inhibitory effect on the targeted protein 6HQO, which, in turn, is associated with breast cancer. The molecular dynamics analysis validates the accuracy of the docking results.

Can Graph Machines Accurately Estimate 13C NMR Chemical Shifts of Benzenic Compounds?

In the organic laboratory, the 13C nuclear magnetic resonance (NMR) spectrum of a newly synthesized compound remains an essential step in elucidating its structure. For the chemist, the interpretation of such a spectrum, which is a set of chemical-shift values, is made easier if he/she has a tool capable of predicting with sufficient accuracy the carbon-shift values from the structure he/she intends to prepare. As there are few open-source methods for accurately estimating this property, we applied our graph-machine approach to build models capable of predicting the chemical shifts of carbons. For this study, we focused on benzene compounds, building an optimized model derived from training a database of 10,577 chemical shifts originating from 2026 structures that contain up to ten types of non-carbon atoms, namely H, O, N, S, P, Si, and halogens. It provides a training root-mean-squared relative error (RMSRE) of 0.5%, i.e., a root-mean-squared error (RMSE) of 0.6 ppm, and a mean absolute error (MAE) of 0.4 ppm for estimating the chemical shifts of the 10k carbons. The predictive capability of the graph-machine model is also compared with that of three commercial packages on a dataset of 171 original benzenic structures (1012 chemical shifts). The graph-machine model proves to be very efficient in predicting chemical shifts, with an RMSE of 0.9 ppm, and compares favorably with the RMSEs of 3.4, 1.8, and 1.9 ppm computed with the ChemDraw v. 23.1.1.3, ACD v. 11.01, and MestReNova v. 15.0.1-35756 packages respectively. Finally, a Docker-based tool is proposed to predict the carbon chemical shifts of benzenic compounds solely from their SMILES codes.

On the geometry dependence of the nuclear magnetic resonance chemical shift of mercury in thiolate complexes: A relativistic density functional theory study.

Thiolate containing mercury(II) complexes of the general formula [Hg(SR) ] have been of great interest since the toxicity of mercury was recognized. 199Hg nuclear magnetic resonance spectroscopy (NMR) is a powerful tool for characterization of mercury complexes. In this work, the Hg shielding constants in a series of [Hg(SR) ] complexes are therefore investigated computationally with particular emphasis on their geometry dependence. Geometry optimizations and NMR chemical shift calculations are performed at the density functional theory (DFT) level with both the zeroth-order regular approximation (ZORA) and four-component relativistic methods. The four exchange-correlation (XC) functionals PBE0, PBE, B3LYP, and BLYP are used in combination with either Dyall's Gaussian-type (GTO) or Slater-type orbitals (STOs) basis sets. Comparing ZORA and four-component calculations, one observes that the calculated shielding constants for a given molecular geometry have a constant difference of 1070 ppm. This confirms that ZORA is an acceptable relativistic method to compute NMR chemical shifts. The combinations of four-component/PBE0/v3z and ZORA/PBE0/QZ4P are applied to explore the geometry dependence of the isotropic shielding. For a given coordination number, the distance between mercury and sulfur is the key factor affecting the shielding constant, while changes in bond and dihedral angles and even different side groups have relatively little impact.

(2S,4S)-5-Fluoroleucine, (2S,4R)-5-Fluoroleucine, and 5,5'-Difluoroleucine in Escherichia coli PpiB: Protein Production, 19F NMR, and Ligand Sensing Enhanced by the γ-Gauche Effect.

Global substitution of leucine for analogues containing CH2F instead of methyl groups delivers proteins with multiple sites for monitoring by 19F nuclear magnetic resonance (NMR) spectroscopy. The 19 kDa Escherichia coli peptidyl-prolyl cis-trans isomerase B (PpiB) was prepared with uniform high-level substitution of leucine by (2S,4S)-5-fluoroleucine, (2S,4R)-5-fluoroleucine, or 5,5'-difluoroleucine. The stability of the samples toward thermal denaturation was little altered compared to the wild-type protein. 19F nuclear magnetic resonance (NMR) spectra showed large chemical shift dispersions between 6 and 17 ppm. The 19F chemical shifts correlate with the three-bond 1H-19F couplings (3JHF), providing the first experimental verification of the γ-gauche effect predicted by [Feeney, J. J. Am. Chem. Soc. 1996, 118, 8700-8706] and establishing the effect as the predominant determinant of the 19F chemical shifts of CH2F groups. Individual CH2F groups can be confined to single rotameric states by the protein environment, but most CH2F groups exchange between different rotamers at a rate that is fast on the NMR chemical shift scale. Interactions between fluorine atoms in 5,5'-difluoroleucine bias the CH2F rotamers in agreement with results obtained previously for 1,3-difluoropropane. The sensitivity of the 19F chemical shift to the rotameric state of the CH2F groups potentially renders them particularly sensitive for detecting allosteric effects.

Mechanism of Methylene Blue Inducing the Disulfide Bond Formation of Tubulin-Associated Unit Proteins.

Methylene blue (MB) has recently completed a Phase-3 clinical trial as leuco-methylthioninium (LMT) bis(hydromethanesulfonate) for treating Alzheimer's disease. Herein, we investigated the mechanism underlying the MB inhibition of tubulin-associated unit (tau) aggregation by focusing on tau monomers. We found that MB causes disulfide bond formation, resulting in strong nuclear magnetic resonance chemical shift perturbations in a large area of tau proteins. The oxidized form of MB, namely methylthioninium (MT+), specifically catalyzed the oxidation of cysteine residues in tau proteins to form disulfide bonds directly using O2. This process is independent of the MT+-to-LMT redox cycle. Moreover, MT+ preferentially oxidized C291 and C322 in the lysine-rich R2 and R3 domains. Under in vivo brain physoxia conditions, LMT may convert to MT+, possibly interfering with tau fibrillation via disulfide bond formation.

Optoelectronic Response to the Fluor Ion Bond on 4-(4,4,5,5-Tetramethyl-1,3,2-dioxoborolan-2-yl)benzaldehyde.

Boronate esters are a class of compounds containing a boron atom bonded to two oxygen atoms in an ester group, often being used as precursors in the synthesis of other materials. The characterization of the structure and properties of esters is usually carried out by UV-visible, infrared, and nuclear magnetic resonance (NMR) spectroscopic techniques. With the aim to better understand our experimental data, in this article, the density functional theory (DFT) is used to analyze the UV-visible and infrared spectra, as well as the isotropic shielding and chemical shifts of the hydrogen atoms 1H, carbon 13C and boron 11B in the compound 4-(4,4,5,5-tetramethyl-1,3,2-dioxoborolan-2-yl)benzaldehyde. Furthermore, this study considers the change in its electronic and spectroscopic properties of this particular ester, when its boron atom is coordinated with a fluoride anion. The calculations were carried out using the LSDA and B3LYP functionals in Gaussian-16, and PBE in CASTEP. The results show that the B3LYP functional gives the best approximation to the experimental data. The formation of a coordinated covalent B-F bond highlights the remarkable sensitivity of the NMR chemical shifts of carbon, oxygen, and boron atoms and their surroundings. Furthermore, this bond also highlights the changes in the electron transitions bands n → π* and π → π* during the absorption and emission of a photon in the UV-vis, and in the stretching bands of the C=C bonds, and bending of BO2 in the infrared spectrum. This study not only contributes to the understanding of the properties of boronate esters but also provides important information on the interactions and responses optoelectronic of the compound when is bonded to a fluorine atom.

Serratiomycins D1-D3, Antibacterial Cyclic Peptides from a Serratia sp. and Structure Revision of Serratiomycin.

Serratiomycin (1) is an antibacterial cyclic depsipeptide, first discovered from a Eubacterium culture in 1998. This compound was initially reported to contain l-Leu, l-Ser, l-allo-Thr, d-Phe, d-Ile, and hydroxydecanoic acid. In the present study, 1 and three new derivatives, serratiomycin D1-D3 (2-4), were isolated from a Serratia sp. strain isolated from the exoskeleton of a long-horned beetle. The planar structures of 1-4 were elucidated by using mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Comparison of the NMR chemical shifts and the physicochemical data of 1 to those of previously reported serratiomycin indeed identified 1 as serratiomycin. The absolute configurations of the amino units in compounds 1-4 were determined by the advanced Marfey's method, 2,3,4,6-tetra-O-acetyl-β-d-glucopyranosyl isothiocyanate derivatization, and liquid chromatography-mass spectrometric (LC-MS) analysis. Additionally, methanolysis and the modified Mosher's method were used to determine the absolute configuration of (3R)-hydroxydecanoic acid in 1. Consequently, the revised structure of 1 was found to possess d-Leu, l-Ser, l-Thr, d-Phe, l-allo-Ile, and d-hydroxydecanoic acid. In comparison with the previously published structure of serratiomycin, l-Leu, l-allo-Thr, and d-Ile in serratiomycin were revised to d-Leu, l-Thr, and l-allo-Ile. The new members of the serratiomycin family, compounds 2 and 3, showed considerably higher antibacterial activities against Staphylococcus aureus and Salmonella enterica than compound 1.

Different profiles of soil phosphorous compounds depending on tree species and availability of soil phosphorus in a tropical rainforest in French Guiana

BackgroundThe availability of soil phosphorus (P) often limits the productivities of wet tropical lowland forests. Little is known, however, about the metabolomic profile of different chemical P compounds with potentially different uses and about the cycling of P and their variability across space under different tree species in highly diverse tropical rainforests.ResultsWe hypothesised that the different strategies of the competing tree species to retranslocate, mineralise, mobilise, and take up P from the soil would promote distinct soil 31P profiles. We tested this hypothesis by performing a metabolomic analysis of the soils in two rainforests in French Guiana using 31P nuclear magnetic resonance (NMR). We analysed 31P NMR chemical shifts in soil solutions of model P compounds, including inorganic phosphates, orthophosphate mono- and diesters, phosphonates, and organic polyphosphates. The identity of the tree species (growing above the soil samples) explained > 53% of the total variance of the 31P NMR metabolomic profiles of the soils, suggesting species-specific ecological niches and/or species-specific interactions with the soil microbiome and soil trophic web structure and functionality determining the use and production of P compounds. Differences at regional and topographic levels also explained some part of the the total variance of the 31P NMR profiles, although less than the influence of the tree species. Multivariate analyses of soil 31P NMR metabolomics data indicated higher soil concentrations of P biomolecules involved in the active use of P (nucleic acids and molecules involved with energy and anabolism) in soils with lower concentrations of total soil P and higher concentrations of P-storing biomolecules in soils with higher concentrations of total P.ConclusionsThe results strongly suggest “niches” of soil P profiles associated with physical gradients, mostly topographic position, and with the specific distribution of species along this gradient, which is associated with species-specific strategies of soil P mineralisation, mobilisation, use, and uptake.

Nuclear Magnetic Resonance Chemical Shift as a Probe for Single‐Molecule Charge Transport

AbstractExisting modelling tools, developed to aid the design of efficient molecular wires and to better understand their charge‐transport behaviour and mechanism, have limitations in accuracy and computational cost. Further research is required to develop faster and more precise methods that can yield information on how charge transport properties are impacted by changes in the chemical structure of a molecular wire. In this study, we report a clear semilogarithmic correlation between charge transport efficiency and nuclear magnetic resonance chemical shifts in multiple series of molecular wires, also accounting for the presence of chemical substituents. The NMR data was used to inform a simple tight‐binding model that accurately captures the experimental single‐molecule conductance values, especially useful in this case as more sophisticated density functional theory calculations fail due to inherent limitations. Our study demonstrates the potential of NMR spectroscopy as a valuable tool for characterising, rationalising, and gaining additional insights on the charge transport properties of single‐molecule junctions.

Nuclear Magnetic Resonance Chemical Shift as a Probe for Single-Molecule Charge Transport.

Existing modelling tools, developed to aid the design of efficient molecular wires and to better understand their charge-transport behaviour and mechanism, have limitations in accuracy and computational cost. Further research is required to develop faster and more precise methods that can yield information on how charge transport properties are impacted by changes in the chemical structure of a molecular wire. In this study, we report a clear semilogarithmic correlation between charge transport efficiency and nuclear magnetic resonance chemical shifts in multiple series of molecular wires, also accounting for the presence of chemical substituents. The NMR data was used to inform a simple tight-binding model that accurately captures the experimental single-molecule conductance values, especially useful in this case as more sophisticated density functional theory calculations fail due to inherent limitations. Our study demonstrates the potential of NMR spectroscopy as a valuable tool for characterising, rationalising, and gaining additional insights on the charge transport properties of single-molecule junctions.

Intermolecular interaction of azide, cyano and alkyne-N-phenethylacetamide dimers: Experimental and quantum chemical approach

In this study, we present the synthesis and structure characterization by single-crystal X-ray Diffraction (SC-XRD), Ultraviolet Spectroscopy (UV), Fourier Transform Infrared Spectroscopy (FTIR), Nuclear Magnetic Resonance (NMR) and High-resolution Mass Spectrometry (HRMS) of 2-azido-N-phenethylacetamide (4) and 2-cyano-N-phenethylacetamide (6). Further, Density Functional Theory (DFT) was employed to get a better insight regarding the properties exhibited by the compounds. The computational chemistry has been used to explain and investigate the bimolecular nucleophilic substitution (SN2) and concerted acyl substitution mechanisms for the synthesis of compounds 4 and 6, respectively. Additionally, intrinsic reaction coordinate (IRC) calculations confirm the transition state for these reactions. The X-ray diffraction analysis showed that the compounds 4 and 6 crystallized as monoclinic systems, in space group P21/c and P21/n, respectively. The Hirshfeld Surface Analysis revealed that the main contributions in the crystal packing have H···H, H···N/N···H, H···C/C···H and H···O/O···H interactions. The frontier molecular orbital energies were calculated and the HOMO-LUMO energy gap of 4 and 6 were 10.011 and 10.278 eV, respectively. Theoretical values of electronic transitions, vibrational frequencies and NMR chemical shifts were calculated and compared with experimental results, they all showed good results.

Stereochemical and Computational NMR Survey of 1,2,3-Triazoles: in Search of the Original Tauto-Conformers.

The conformational analysis of nine functionalized 1,2,3-triazoles was carried out by the correlation of calculated and experimental high-level nuclear magnetic resonance (NMR) chemical shifts. In solution, the studied triazoles are in exchange dynamic equilibrium caused by their prototropic tautomerism of the NH-proton. The experimentally unresolved NMR signals were assigned for most of the compounds. A more thorough survey was conducted for 4-t-butyl-1,2,3-triazole-5-carbaldehyde oxime. The analysis performed within the framework of the DP4+ formalism completely confirmed the hypothesis of the predominance of the 2H-tautomer. Thus, the methodology for estimating stereochemical structures in the absence of some experimental data allowed the most stable conformations for dynamic systems with different tautomeric ratios to be reliably identified.

Systematic QM/MM Study for Predicting 31P NMR Chemical Shifts of Adenosine Nucleotides in Solution and Stages of ATP Hydrolysis in a Protein Environment.

NMR (nuclear magnetic resonance) spectroscopy allows for important atomistic insights into the structure and dynamics of biological macromolecules; however, reliable assignments of experimental spectra are often difficult. Herein, quantum mechanical/molecular mechanical (QM/MM) calculations can provide crucial support. A major problem for the simulations is that experimental NMR signals are time-averaged over much longer time scales, and since computed chemical shifts are highly sensitive to local changes in the electronic and structural environment, sufficiently large averages over representative structural ensembles are essential. This entails high computational demands for reliable simulations. For NMR measurements in biological systems, a nucleus of major interest is 31P since it is both highly present (e.g., in nucleic acids) and easily observable. The focus of our present study is to develop a robust and computationally cost-efficient framework for simulating 31P NMR chemical shifts of nucleotides. We apply this scheme to study the different stages of the ATP hydrolysis reaction catalyzed by p97. Our methodology is based on MM molecular dynamics (MM-MD) sampling, followed by QM/MM structure optimizations and NMR calculations. Overall, our study is one of the most comprehensive QM-based 31P studies in a protein environment and the first to provide computed NMR chemical shifts for multiple nucleotide states in a protein environment. This study sheds light on a process that is challenging to probe experimentally and aims to bridge the gap between measured and calculated NMR spectroscopic properties.

Benchmark Study on the Calculation of 207Pb NMR Chemical Shifts.

A benchmark set for the computation of 207Pb nuclear magnetic resonance (NMR) chemical shifts is presented. The PbS50 set includes conformer ensembles of 50 lead-containing molecular compounds and their experimentally measured 207Pb NMR chemical shifts. Various bonding motifs at the Pb center with up to seven bonding partners are included. Six different solvents were used in the measurements. The respective shifts lie in the range between +10745 and -5030 ppm. Several calculation settings are assessed by evaluating computed 207Pb NMR shifts for the use with different density functional approximations (DFAs), relativistic approaches, treatment of the conformational space, and levels for geometry optimization. Relativistic effects were included explicitly with the zeroth order regular approximation (ZORA), for which only the spin-orbit variant was able to yield reliable results. In total, seven GGAs and three hybrid DFAs were tested. Hybrid DFAs significantly outperform GGAs. The most accurate DFAs are mPW1PW with a mean absolute deviation (MAD) of 429 ppm and PBE0 with an MAD of 446 ppm. Conformational influences are small as most compounds are rigid, but more flexible structures still benefit from Boltzmann averaging. Including explicit relativistic treatments such as SO-ZORA in the geometry optimization does not show any significant improvement over the use of effective core potentials (ECPs).

Effects of Xylanase A double mutation on substrate specificity and structural dynamics

While protein activity is traditionally studied with a major focus on the active site, the activity of enzymes has been hypothesized to be linked to the flexibility of adjacent regions, warranting more exploration into how the dynamics in these regions affects catalytic turnover. One such enzyme is Xylanase A (XylA), which cleaves hemicellulose xylan polymers by hydrolysis at internal β-1,4-xylosidic linkages. It contains a “thumb” region whose flexibility has been suggested to affect the activity. The double mutation D11F/R122D was previously found to affect activity and potentially bias the thumb region to a more open conformation. We find that the D11F/R122D double mutation shows substrate-dependent effects, increasing activity on the non-native substrate ONPX2 but decreasing activity on its native xylan substrate. To characterize how the double mutant causes these kinetics changes, nuclear magnetic resonance (NMR) and molecular dynamics (MD) simulations were used to probe structural and flexibility changes. NMR chemical shift perturbations revealed structural changes in the double mutant relative to the wild-type, specifically in the thumb and fingers regions. Increased slow-timescale dynamics in the fingers region was observed as intermediate-exchange line broadening. Lipari-Szabo order parameters show negligible changes in flexibility in the thumb region in the presence of the double mutation. To help understand if there is increased energetic accessibility to the open state upon mutation, alchemical free energy simulations were employed that indicated thumb opening is more favorable in the double mutant. These studies aid in further characterizing how flexibility in adjacent regions affects the function of XylA.