Evaluation of the reactivity, selectivity and lifetime of hydrotalcite-based catalysts using isopropanol as probe molecule

Hydrotalcite catalysts derived from NiAl and NiAlMg mixed oxides were successfully prepared by coprecipitation at a constant pH of 11. Physicochemical methods were investigated to determine their structural and textural properties. Using isopropanol as a probe molecule, the acid–base properties of the catalysts were investigated, and the evaluation of reactivity, selectivity and lifetime was established.

Revealing the unknown aspects of initial steps of prenylated flavin mononucleotide biosynthesis – the role of Lys129 in PaUbiX

Background Prenylated flavin mononucleotide (prFMN) is a recently discovered, heavily modified flavin compound. It is the only known cofactor that enables enzymatic 1,3-dipolar cycloaddition reactions. It is produced by enzymes from UbiX family, from flavin mononucleotide and either dimethylallyl mono- or diphosphate. prFMN biosynthesis is currently reported to be initiated by a protonation of the substrate by Glu140. Methods Computational chemistry methods are applied herein - mostly different flavors of molecular dynamics MD, such as Constant pH MD, hybrid Quantum-Mechanical / Molecular Mechanical MD, and classical MD. Results Glu140 competes for a single proton with Lys129 but it is the latter that adopted a protonated state throughout most of the simulation time. Lys129 plays a key role in the positioning of the DMAP’s phosphate group within the PaUbiX active site. DMAP’s breakdown into a phosphate and a prenyl group can be decoupled from the protona-tion of the DMAP’s phosphate group. Conclusions The role of Lys129 in functioning of PaUbiX is reported for the first time. The severity of interactions between Glu140, Lys129, and DMAP’s phosphate group enables an unusual decoupling of phosphate’s protonation from DMAP’s breakdown. Those findings are most likely conserved throughout the UbiX family to the structural re-semblence of active sites of those proteins. Significance Mechanistic insights into a crucial biochemical process, biosynthesis of prFMN, are provided. This study, alt-hough purely computational, extends and perfectly complements the knowledge obtained in classical laboratory experiments.

Ion Transport, Selectivity, and Electronic Polarization in Fluoride Channels

Fluoride channels (Fluc) export toxic F- from the cytoplasm. Crystallography and mutagenesis have identified several conserved residues crucial for fluoride transport, but the transport mechanism at the molecular level has remained elusive. Herein we have applied constant-pH molecular dynamics and free energy sampling methods to investigate fluoride transfer through a Fluc protein from Escherichia coli. We find that fluoride is facile to transfer in its charged form, i.e., F-, by traversing through a non-bonded network. The extraordinary F- selectivity is gained by the hydrogen-bonding capability of the central binding site and the Coulombic filter at the channel entrance. The F- transfer rate calculated using an electronically polarizable force field is significantly more accurate compared to the experimental value than that calculated using a more standard additive force field, suggesting an essential role for electronic polarization in the F- - Fluc interactions.

The Protection of Building Materials of Historical Monuments with Nanoparticle Suspensions

Marble and limestone have been extensively used as building materials in historical monuments. Environmental, physical, chemical and biological factors contribute to stone deterioration. The rehabilitation of stone damage and the delay of further deterioration is of utmost importance. Inorganic nanoparticles having chemical and crystallographic affinity with building materials is very important for the formation of protective coatings or overlayers. In the present work, we have tested the possibility of treating calcitic materials with suspensions of amorphous calcium carbonate (am-CaCO3, ACC) and amorphous silica (AmSiO2). Pentelic marble (PM) was selected as the test material to validate the efficiency of the nanoparticle suspension treatment towards dissolution in undersaturated solutions and slightly acidic pH (6.50). Suspensions of ACC and AnSiO2 nanoparticles were prepared by spontaneous precipitation from supersaturated solutions and by tetraethyl orthosilicate (TEOS) hydrolysis, respectively. The suspensions were quite stable (nine days for ACC and months for AmSiO2). ACC and Am SiO2 particles were deposited on the surface of powdered PM. The rates of dissolution of PM were measured in solutions undersaturated with respect to calcite at a constant pH of 6.50. For specimens treated with ACC and AmSiO2 suspensions, the measured dissolution rates were significantly lower. The extent of the rate of dissolution reduction was higher for AmSiO2 particles on PM. Moreover, application of the nanoparticles on the substrate during their precipitation was most efficient method.

Optimization of Conditions For Increasing of Saffron Cell Biomass And Crocin Production In Stirred Bioreactor

Bioreactors provide suitable conditions for the growth of cells and production of secondary metabolites by regulating physical and chemical factors. In this study, first, sucrose, 2-(N-morpholino) ethanesulfonic acid (MES) as a buffering agent and medium pH was optimized in the Erlenmeyer flask. This aim was then pursued in a stirred bioreactor through aeration and pH medium adjustment. Results of the first step showed that Schenk and Hildebrandt (SH) basal medium with naphthalene acetic acid (2 mg.l-1) and 6-benzylaminopurine (1 mg.l-1) supplemented with 2.5 mM of MES and gradually increment of sucrose from 3 to 6% caused to catch the highest cell biomass and crocin production. The spectrophotometry measurement showed that the highest crocin content of the cells was 0.8 mg/g after five weeks. The results of the second part revealed that in the stirred bioreactor, constant pH (5.8) during the growth period is a limited factor for the cell growth and crocin production. Although aeration initially found to be an inhibited factor for the production of crocin, results showed that, if the evaporated volume of water caused by aeration is constituted, it can be an effective factor to increase cell growth rate around 2 folds. In addition, total crocin content of the cells, based on the HPLC could be raised up to 2 mg/g. Based on this study, it can be concluded that MES and gradual increment of sucrose could increasing the cell growth and crocin production. Aeration in bioreactor can increase cell biomass, if the medium volume will be kept constant.

pKAI: a fast and interpretable deep learning approach for accurate electrostatics-driven pKa predictions

The pKa values of ionizable residues influence protein folding, stability and biological function. The pKa in bulk water is known for all residues, however, in a protein environment, it can significantly be affected by confinement and electrostatics. Existing computational methods to estimate pKa shifts rely on theoretical approximations and lengthy computations. Furthermore, the amount of experimentally determined pKa values is still very limited, hindering the development of faster machine learning-based methods. In this work, we use a data set of 6 million pKa shifts — determined by PypKa, a continuum electrostatics method — to train deep learning models that are shown to rival the physics-based predictor. On ~750 experimentally determined data points, our model displays the best accuracy and it is the only one that breaks the 1 pK unit RMSE barrier of this considerably difficult test set. Although trained using a very simplified view of the surroundings of the titratable group (namely, atom types and distances to other titratable groups within a given radius), the models are shown to assign proper electrostatic charges to chemical groups, to keep the known correlation between solvent exposure and pKa shift magnitude, and to grasp the importance of close interactions, including hydrogen bonds. Inference times allow speedups of more than 1000 times faster than physics-based methods, especially for large proteins. By combining speed, accuracy and a reasonable understanding of the theoretical basis for pKa shifts, our models provide a game-changing solution for fast estimations of macroscopic pKa from ensembles of microscopic (pKhalf) values as well as for many downstream applications such as molecular docking and constant-pH molecular dynamics simulations.

Protein pKa prediction with machine learning

Protein pKa prediction is essential for the investigation of pH-associated relationship between protein structure and function. In this work, we introduce a deep learning based protein pKa predictor DeepKa, which is trained and validated with the pKa values derived from continuous constant pH molecular dynamics (CpHMD) simulations of 279 soluble proteins. Here the CpHMD implemented in the Amber molecular dynamics package has been employed (Huang, Harris, and Shen J. Chem. Inf. Model. 2018, 58, 1372-1383). Notably, to avoid discontinuities at the boundary, grid charges are proposed to represent protein electrostatics. We show that the prediction accuracy by DeepKa is close to that by CpHMD benchmarking simulations, validating DeepKa as an efficient protein pKa predictor. In addition, the training and validation sets created in this study can be applied to the development of machine learning based protein pKa predictors in future. Finally, the grid charge representation is general and applicable to other topics, such as the protein-ligand binding affinity prediction.

Unravelling Constant pH Molecular Dynamics in Oligopeptides with Explicit Solvation Model

An accurate description of the protonation state of amino acids is essential to correctly simulate the conformational space and the mechanisms of action of proteins or other biochemical systems. The pH and the electrochemical environments are decisive factors to define the effective pKa of amino acids and, therefore, the protonation state. However, they are poorly considered in Molecular Dynamics (MD) simulations. To deal with this problem, constant pH Molecular Dynamics (cpHMD) methods have been developed in recent decades, demonstrating a great ability to consider the effective pKa of amino acids within complex structures. Nonetheless, there are very few studies that assess the effect of these approaches in the conformational sampling. In a previous work of our research group, we detected strengths and weaknesses of the discrete cpHMD method implemented in AMBER when simulating capped tripeptides in implicit solvent. Now, we progressed this assessment by including explicit solvation in these peptides. To analyze more in depth the scope of the reported limitations, we also carried out simulations of oligopeptides with distinct positions of the titratable amino acids. Our study showed that the explicit solvation model does not improve the previously noted weaknesses and, furthermore, the separation of the titratable amino acids in oligopeptides can minimize them, thus providing guidelines to improve the conformational sampling in the cpHMD simulations.

Adsorption of Lysozyme Into a Charged Confining Pore

Several applications arise from the confinement of proteins on surfaces since their stability and biological activity are enhanced. It is also known that the way a protein adsorbs on the surface is important for its biological function since its active sites should not be obstructed. In this study, the adsorption properties of hen egg-white Lysozyme, HEWL, into a negatively charged silica pore is examined employing a coarse-grained model and constant-pH Monte Carlo simulations. The role of electrostatic interactions is taken into account when including the Debye-Hueckel potentials into the Ca structure-based model. We evaluate the effects of pH, salt concentration, and pore radius on the protein preferential orientation and spatial distribution of its residues regarding the pore surface. By mapping the residues that stay closer to the pore surface, we find the increase of pH leads to orientational changes of the adsorbed protein when the solution pH gets closer to the HEWL isoelectric point. At these conditions, the pKa shift of these important residues caused by the adsorption into the charged confining surface results in a HEWL charge distribution that stabilizes the adsorption in the observed protein orientation. We compare our observations to the results of pKa shift for HEWL available in the literature and to some experimental data.

Kinetics and Mechanism of Catalyzed Oxidation of L-Cysteine by Salen Schiff Base Complexes of Co(III), Fe (III) and Cr(III)

Kinetics of oxidation of L-cysteine by new series of substituted ONNO-donor salen-type Schiff base complexes of general formula [MIII(L)Cl] (M = Co, Fe, Cr; L = Schiff base ligand) have been studied in aqueous solutions. Measurements were run at constant temperature (25º C), constant ionic strength (0.20 M), and constant pH (7.0) under pseudo-first order conditions, in which the concentration of cysteine is around two orders of magnitude greater than that of metal complex. The observed rate constant was determined by following the change in absorbance of reaction mixture at a predetermined wavelength with time. Results show that the rate of oxidation depends on the type of metal center, with Co(III) complexes were found to have the highest rates due to higher reduction potential of Co(III). The oxidation rate was also found to depend on steric factor and the electron withdrawing / releasing ability of the ligand bound to the metal ion.