Computing the Differences between Asn-X and Gln-X Deamidation and Their Impact on Pharmaceutical and Physiological Proteins: A Theoretical Investigation Using Model Dipeptides.

Protein deamidation is a degradation mechanism that significantly impacts both pharmaceutical and physiological proteins. Deamidation impacts two amino acids, Asn and Gln, where the net neutral residues are converted into their acidic forms. While there are multiple similarities between the reaction mechanisms of the two residues, the impact of Gln deamidation has been noted to be most significant on physiological proteins while Asn deamidation has been linked to both pharmaceutical and physiological proteins. For this purpose, we sought to analyze the thermochemical and kinetic properties of the different reactions of Gln deamidation relative to Asn deamidation. In this study, we mapped the deamidation of Gln-X dipeptides into Glu-X dipeptides using density functional theory (DFT). Full network mapping facilitated the prediction of reaction selectivity between the two primary pathways, as well as between the two products of Gln-X deamidation as a function of solvent dielectric. To achieve this analysis, we studied a total of 77 dipeptide reactions per solvent dielectric (308 total reactions). Modeled at a neutral pH and using quantum chemical and statistical thermodynamic methods, we computed the following values: enthalpy of reaction (ΔHRXN), entropy (ΔSRXN), Gibbs free energy of reaction (ΔGRXN), activation energy (EA), and the Arrhenius preexponential factor (log(A)) for each dipeptide. Additionally, using chemical reaction principles, we generated a database of computed rate coefficients for all possible N-terminus Gln-X deamidation reactions at a neutral pH, predicted the most likely deamidation reaction mechanism for each dipeptide reaction, analyzed our results against our prior study on Asn-X deamidation, and matched our results against qualitative trends previously noted by experimental literature.

Fentanyl Assay Derived from Intermolecular Interaction-Enabled Small Molecule Recognition (iMSR) with Differential Impedance Analysis for Point-of-Care Testing.

Rapid and effective differentiation and quantification of a small molecule drug, such as fentanyl, in bodily fluids are major challenges for diagnosis and personal medication. However, the current toxicology methods used to measure drug concentration and metabolites require laboratory-based testing, which is not an efficient or cost-effective way to treat patients in a timely manner. Here, we show an assay for monitoring fentanyl levels by combining the intermolecular interaction-enabled small molecule recognition (iMSR) with differential impedance analysis of conjugated polymers. The differential interactions with the designed anchor interface were transduced through the perturbance of the electric status of the flexible conducting polymer. This assay showed excellent fentanyl selectivity against common interferences, as well as in variable body fluids through either testing strips or skin patches. Directly using the patient blood, the sensor provided 1%-5% of the average deviation compared to the "gold" standard method LC-MS results in the medically relevant fentanyl range of 20-90 nM. The superior sensing properties, in conjunction with mechanical flexibility and compatibility, enabled point-of-care detection and provided a promising avenue for applications beyond the scope of biomarker detection.

Electronic structure of the ground and excited states of neutral and charged silicon hydrides, SiHx0/+/-, x = 1-4.

The ground and excited electronic states of the titled species are investigated with multi-reference configuration interaction and diffuse basis sets. We found that in addition to the valence orbitals, the inclusion of the 4s, 4p, and especially 3d orbitals (although with minimal population) of silicon in the active space of the reference complete active space self-consistent field wavefunction are necessary for the proper convergence of the calculations. We also demonstrate that the aug-cc-pVTZ basis set provides quite accurate results compared to both larger basis sets and basis set limit results at a lower computational cost. The excited states involve excitations within the 3s and 3p orbitals of silicon (especially for the mono- and di-hydrides), followed by excitations from the Si-H bonding orbitals to either silicon valence or Rydberg (4s, 4p) orbitals. The number of electronic states per energy unit decrease as we add hydrogen atoms, and the first excited state of SiH4 is at 9.0 eV and leads to SiH3 + H. All species have stable ground state structures with all hydrogen atoms bound to silicon, except for SiH4+ and SiH4-. The former dissociates to SiH2+ + H2, while the latter loses an electron or can dissociate forming H2 as well.

Competitive Hydrogen Migration in Silicon Nitride Nanoclusters: Reaction Kinetics Generalized from Supervised Machine Learning.

The rate coefficients for 52 hydrogen shift reactions for silicon nitrides containing up to 6 atoms of silicon and nitrogen have been calculated using the G3//B3LYP composite method and statistical thermodynamics. The overall reaction of substituted acyclic and cyclic silylenes to their respective silene and imine species by a 1,2-hydrogen shift reaction was sorted by three different types of H shift reactions using overall reaction thermodynamics: (1) endothermic H shift between N and Si:, (2) endothermic H shift between Si and Si:, and (3) exothermic H shift between Si and Si:. Endothermic H shift reactions between Si atoms have one dominant activation barrier where the exothermic H shift reaction between Si atoms has two barriers and a stable intermediate. The rate-determining step was determined to be from the intermediate to the substituted silene, and then kinetic parameters for the overall reaction were calculated for the two-step pathway. The single event pre-exponential factors, Ã, and activation energies, Ea, for the three different classes of hydrogen shift reactions of silicon nitrides were computed. The hydrogen shift reaction was explored for acyclic and cyclic monofunctional silicon nitrides, and the type of hydrogen shift reaction gives the most significant influence on the kinetic parameters. Using a supervised machine learning approach, the models for predicting the energy barrier of three different hydrogen shift reactions were generalized and suggested based on selected descriptors.

Isolating key reaction energetics and thermodynamic properties during hardwood model lignin pyrolysis.

Computational studies on the pyrolysis of lignin using electronic structure methods have been largely limited to dimeric or trimeric models. In the current work we have modeled a lignin oligomer consisting of 10 syringyl units linked through 9 ß-O-4' bonds. A lignin model of this size is potentially more representative of the polymer in angiosperms; therefore, we used this representative model to examine the behavior of hardwood lignin during the initial steps of pyrolysis. Using this oligomer, the present work aims to determine if and how the reaction enthalpies of bond cleavage vary with positions within the chain. To accomplish this, we utilized a composite method using molecular mechanics based conformational sampling and quantum mechanically based density functional theory (DFT) calculations. Our key results show marked differences in bond dissociation enthalpies (BDE) with the position. In addition, we calculated standard thermodynamic properties, including enthalpy of formation, heat capacity, entropy, and Gibbs free energy for a wide range of temperatures from 25 K to 1000 K. The prediction of these thermodynamic properties and the reaction enthalpies will benefit further computational studies and cross-validation with pyrolysis experiments. Overall, the results demonstrate the utility of a better understanding of lignin pyrolysis for its effective valorization.

Towards thermoneutral hydrogen evolution reaction using noble metal free molybdenum ditelluride/graphene nanocomposites.

The development of efficient electrocatalysts for hydrogen generation is an essential task to meet future energy demand. In recent years, molybdenum ditelluride (MoTe2) has triggered incredible research interests due to intrinsic nontrivial band gap with promising semi-metallic behaviors. In this work, 2D MoTe2 nanosheets have been synthesized uniformly on graphene substrate through ultra-fast microwave-initiated approach, that shows a superior hydrogen evolution in acidic medium with low overpotential (~150 mV), low activation energy (8.4362 ± 1.5413 kJ mol-1), along with a Tafel slope of 94.5 mV/decade. Interestingly, MoTe2/graphene exhibits the enhanced electrocatalytic stability during the long cycling test, resulting an increase in specific surface area of catalyst materials. Moreover, the results from periodic plane-wave density functional theory (DFT) indicate that, the best active sites are the corner of a Mo-atom and a critical bifunctional site comprised of adjacent Mo and Te edge atoms. Furthermore, the corresponding volcano plot reveals the near thermoneutral catalytic activity of MoTe2/graphene for hydrogen generation.

Data-Driven Investigation of Monosilane and Ammonia Co-Pyrolysis to Silicon-Nitride-Based Ceramic Nanomaterials.

With its high strength, high thermal stability, low density, and high electrical resistance, silicon-nitride-based ceramics have been widely used as gate insulating layers, oxidation masks, and passivation layers. Employing SiN nanomaterials in anode applications also improves rate performances and cycling stability of the lithium-ion batteries. However, a fundamental understanding of the SiN synthetic process remains elusive. SiN gas-phase synthesis can be tailored with a comprehensive understanding of the underlying thermodynamics. In comparison to the characterization data available for solid-state SiN materials, high-level theoretical studies on gas-phase materials possessing Si-N bonds and comprehensive investigation of the SiN chemistry, particularly for nanoclusters, are very uncommon. Thus, we performed a theoretical study of Si and SiN alloy acyclic hydrides and polycyclic clusters to predict electronic structures and thermochemistry using quantum chemical calculation and statistical thermodynamics. Electronic properties by way of highest and lowest occupied molecular orbital energy gap and natural bonding orbitals analysis were calculated to explore the influence of elemental composition and geometry on the stability. Our studies provide characteristic data of SiN species for a data-driven approach to map the design space for discovery of novel silicon-nitride-based ceramic materials for advanced electronic and coating applications.

Tuning Hydrogenated Silicon, Germanium, and SiGe Nanocluster Properties Using Theoretical Calculations and a Machine Learning Approach.

There are limited studies available that predict the properties of hydrogenated silicon-germanium (SiGe) clusters. For this purpose, we conducted a computational study of 46 hydrogenated SiGe clusters (Si xGe yH z, 1 < X + Y ≤ 6) to predict the structural, thermochemical, and electronic properties. The optimized geometries of the Si xGe yH z clusters were investigated using quantum chemical calculations and statistical thermodynamics. The clusters contained 6 to 9 fused Si-Si, Ge-Ge, or Si-Ge bonds, i.e., bonds participating in more than one 3- to 4-membered rings, and different degrees of hydrogenation, i.e., the ratio of hydrogen to Si/Ge atoms varied depending on cluster size and degree of multifunctionality. Our studies have established trends in standard enthalpy of formation, standard entropy, and constant pressure heat capacity as a function of cluster composition and structure. A novel bond additivity correction model for SiGe chemistry was regressed from experimental data on seven acyclic Si/Ge/SiGe species to improve the accuracy of the standard enthalpy of formation predictions. Electronic properties were investigated by analysis of the HOMO-LUMO energy gap to study the effect of elemental composition on the electronic stability of Si xGe yH z clusters. These properties will be discussed in the context of tailored nanomaterials design and generalized using a machine learning approach.

Catalysis by dihydrofolate reductase and other enzymes arises from electrostatic preorganization, not conformational motions.

The proposal that enzymatic catalysis is due to conformational fluctuations has been previously promoted by means of indirect considerations. However, recent works have focused on cases where the relevant motions have components toward distinct conformational regions, whose population could be manipulated by mutations. In particular, a recent work has claimed to provide direct experimental evidence for a dynamical contribution to catalysis in dihydrofolate reductase, where blocking a relevant conformational coordinate was related to the suppression of the motion toward the occluded conformation. The present work utilizes computer simulations to elucidate the true molecular basis for the experimentally observed effect. We start by reproducing the trend in the measured change in catalysis upon mutations (which was assumed to arise as a result of a "dynamical knockout" caused by the mutations). This analysis is performed by calculating the change in the corresponding activation barriers without the need to invoke dynamical effects. We then generate the catalytic landscape of the enzyme and demonstrate that motions in the conformational space do not help drive catalysis. We also discuss the role of flexibility and conformational dynamics in catalysis, once again demonstrating that their role is negligible and that the largest contribution to catalysis arises from electrostatic preorganization. Finally, we point out that the changes in the reaction potential surface modify the reorganization free energy (which includes entropic effects), and such changes in the surface also alter the corresponding motion. However, this motion is never the reason for catalysis, but rather simply a reflection of the shape of the reaction potential surface.

Thermochemical property estimation of hydrogenated silicon clusters.

The thermochemical properties for selected hydrogenated silicon clusters (Si(x)H(y), x = 3-13, y = 0-18) were calculated using quantum chemical calculations and statistical thermodynamics. Standard enthalpy of formation at 298 K and standard entropy and constant pressure heat capacity at various temperatures, i.e., 298-6000 K, were calculated for 162 hydrogenated silicon clusters using G3//B3LYP. The hydrogenated silicon clusters contained ten to twenty fused Si-Si bonds, i.e., bonds participating in more than one three- to six-membered ring. The hydrogenated silicon clusters in this study involved different degrees of hydrogenation, i.e., the ratio of hydrogen to silicon atoms varied widely depending on the size of the cluster and/or degree of multifunctionality. A group additivity database composed of atom-centered groups and ring corrections, as well as bond-centered groups, was created to predict thermochemical properties most accurately. For the training set molecules, the average absolute deviation (AAD) comparing the G3//B3LYP values to the values obtained from the revised group additivity database for standard enthalpy of formation and entropy at 298 K and constant pressure heat capacity at 500, 1000, and 1500 K were 3.2%, 1.9%, 0.40%, 0.43%, and 0.53%, respectively. Sensitivity analysis of the revised group additivity parameter database revealed that the group parameters were able to predict the thermochemical properties of molecules that were not used in the training set within an AAD of 3.8% for standard enthalpy of formation at 298 K.

Converting structural information into an allosteric-energy-based picture for elongation factor Tu activation by the ribosome.

The crucial process of aminoacyl-tRNA delivery to the ribosome is energized by the GTPase reaction of the elongation factor Tu (EF-Tu). Advances in the elucidation of the structure of the EF-Tu/ribosome complex provide the rare opportunity of gaining a detailed understanding of the activation process of this system. Here, we use quantitative simulation approaches and reproduce the energetics of the GTPase reaction of EF-Tu with and without the ribosome and with several key mutants. Our study provides a novel insight into the activation process. It is found that the critical H84 residue is not likely to behave as a general base but rather contributes to an allosteric effect, which includes a major transition state stabilization by the electrostatic effect of the P loop and other regions of the protein. Our findings have general relevance to GTPase activation, including the processes that control signal transduction.

The role of multifunctional kinetics during early-stage silicon hydride pyrolysis: reactivity of Si2H2 isomers with SiH4 and Si2H6.

Kinetic parameters for the dominant pathways during the addition of the four Si(2)H(2) isomers, i.e., trans-HSiSiH, SiSiH(2), Si(H)SiH, and Si(H(2))Si, to monosilane, SiH(4), and disilane, Si(2)H(6), have been calculated using G3//B3LYP, statistical thermodynamics, conventional and variational transition state theory, and internal rotation corrections. The direct addition products of the multifunctional Si(2)H(2) isomers were monofunctional substituted silylenes, hydrogen-bridged species, and silenes. During addition to monosilane and disilane, the SiSiH(2) isomer was found to be most reactive over the temperature range of 800 to 1200 K. Revised parameters for the Evans-Polanyi correlation and a representative pre-exponential factor for multifunctional silicon hydride addition and elimination reaction families under pyrolysis conditions were regressed from the reactions in this study. This revised kinetic correlation was found to capture the activation energies and rate coefficients better than the current literature methods.

Kinetic correlations for H2 addition and elimination reaction mechanisms during silicon hydride pyrolysis.

The mechanism of H(2) addition and elimination reactions in selected silicon hydrides (Si(x)H(y), x = 1-10, y = 4-20) was modeled using quantum chemical calculations, statistical thermodynamics, transition state theory and transition state group additivity. Rate coefficients for 25 H(2) addition reactions were calculated using G3//B3LYP. For nearly every reaction, the overall conversion exhibits two steps. In the addition direction, the reactants first meet to form an adduct which then converts into a saturated silicon hydride via homolytic H-H bond cleavage. Values for the single-event Arrhenius pre-exponential factor, Ã, and the activation energy, E(a), were calculated from the G3//B3LYP rate coefficients, and a group additivity scheme was developed to predict à and E(a). The values predicted by group additivity are more accurate than kinetic correlations currently used in the literature, which rely on representative à values and the Evans-Polanyi correlation. The factors that have the most pronounced effect on à and E(a) were investigated, and stabilization of the divalent silicon atom of the unsaturated silicon hydride with electron-donating substituents was found to influence kinetic parameters considerably. The rate coefficients for H(2) addition reactions were found to correlate reasonably well with the difference in energy between the highest occupied molecular orbital of H(2) (E(HOMO)) and the lowest unoccupied molecular orbital of the reactant silylene (E(LUMO)).

Kinetics of substituted silylene addition and elimination in silicon nanocluster growth captured by group additivity.

Accurate rate coefficients for 40 bimolecular substituted silylene addition reactions for silicon hydrides containing up to nine silicon atoms are calculated using the G3//B3LYP method. The overall reactions exhibit two steps: the reactants first meet to form an adduct, which then converts into a saturated silicon hydride. Values for the single-event Arrhenius pre-exponential factor, A, and the activation energy, E(a), are calculated from the G3//B3LYP rate coefficients corrected for internal rotations, and a group additivity scheme is developed to predict A and E(a). The values predicted by group additivity are more accurate than structure-reactivity relationships currently used in the literature, which rely on representative A values and the Evans-Polanyi correlation. The structural factors that have the most pronounced effect on A and E(a) are considered, and the presence of rings is shown to influence these values strongly.

Exploring 1,2-hydrogen shift in silicon nanoparticles: reaction kinetics from quantum chemical calculations and derivation of transition state group additivity database.

Accurate rate coefficients for 35 1,2-hydrogen shift reactions for hydrides containing up to 10 silicon atoms have been calculated using G3//B3LYP. The overall reactions exhibit two distinct barriers. Overcoming the first barrier results in the formation of a hydrogen-bridged intermediate species from a substituted silylene and is characterized by a low activation energy. Passing over the second barrier converts this stable intermediate into the double-bonded silene. Values for the single event Arrhenius pre-exponential factor, A, and the activation energy, E(a), were calculated from the G3//B3LYP rate coefficients, and a group additivity scheme was developed to predict A and E(a). The values predicted by group additivity are more accurate than structure/reactivity relationships currently used in the literature, which rely on a representative A value and the Evans-Polanyi correlation to predict E(a). The structural factors that have the most pronounced effect on A and E(a) were considered, and the presence of rings was shown to influence these values strongly.