Is Aromatic Nitration Spin Density Driven?

The mechanism of aromatic nitration is critically reviewed with particular emphasis on the paradox of the high positional selectivity of substitution in spite of low substrate selectivity. Early quantum chemical computations in the gas phase have suggested that the retention of positional selectivity at encounter-limited rates could be ascribed to the formation of a radical pair via an electron transfer step occurring before the formation of the Wheland intermediate, but calculations which account for the effects of solvent polarization and the presence of counterion do not support that point of view. Here we report a brief survey of the available experimental and theoretical data, adding a few more computations for better clarifying the role of electron transfer for regioselectivity.

Features of the Electronic Structure of Excited Quadrupolar Molecules in Non-Polar Solvents

Interactions of the electronic subsystem of the quadrupolar fluorophore with intramolecular highfrequency antisymmetric vibrations and solvent polarization are responsible for charge transfer symmetry breaking (SB), which is observed after optical excitation of such molecules in polar solvents. It is known that although these two interactions are mathematically described in similar ways, only the interaction of the fluorophore with solvent orientational polarization can create a state with broken symmetry if this interaction is strong enough. Nevertheless, the interaction of a quadrupolar fluorophore with intramolecular highfrequency antisymmetric vibrations in nonpolar solvents leads to a considerable reconstruction of the electronic subsystem. The analysis of the excited state of quadrupolar molecules in nonpolar solvents performed in this study reveals that such molecules can behave like quantum twostate systems, that is, as a quasispin s = 1/2, having an electric dipole moment instead of a magnetic one. This feature of excited quadrupolar molecules may be of interest to emerging technologies of molecular electronics.

Modeling Interfacial Electron Transfer in the Double Layer: The Interplay Between Electrode Coupling and Electrostatic Driving

This manuscript presents a theoretical model for simulating interfacial electron transfer reactions within the electrical double layer. This model resolves the population density of redox active species and simulated electron transfer at the level of Marcus theory, with a fluctuating solvent polarization coordinate. In this model, the kinetics and thermodynamics of electron transfer depend on the values of the electronic coupling of species (to the electrode) and the electrical potential drop, respectively.

Modeling Interfacial Electron Transfer in the Double Layer: The Interplay Between Electrode Coupling and Electrostatic Driving

This manuscript presents a theoretical model for simulating interfacial electron transfer reactions within the electrical double layer. This model resolves the population density of redox active species and simulated electron transfer at the level of Marcus theory, with a fluctuating solvent polarization coordinate. In this model, the kinetics and thermodynamics of electron transfer depend on the values of the electronic coupling of species (to the electrode) and the electrical potential drop, respectively.

ff19SB: Amino-Acid Specific Protein Backbone Parameters Trained Against Quantum Mechanics Energy Surfaces in Solution

<p>Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled ϕ/ψ parameters using 2D ϕ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, we have performed a total of ~5 milliseconds MD simulations in explicit solvent. Our results show that after amino-acid specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino acid specific Protein Data Bank (PDB) Ramachandran maps better, but also shows significantly improved capability to differentiate amino acid dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. </p>

ff19SB: Amino-Acid Specific Protein Backbone Parameters Trained Against Quantum Mechanics Energy Surfaces in Solution

<p>Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled ϕ/ψ parameters using 2D ϕ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, we have performed a total of ~5 milliseconds MD simulations in explicit solvent. Our results show that after amino-acid specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino acid specific Protein Data Bank (PDB) Ramachandran maps better, but also shows significantly improved capability to differentiate amino acid dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. </p>

Simulating Redox Potentials of Biomolecules: the Case of Cryptochrome 1 from Arabidopsis thaliana

Redox reactions play a key role in various biological processes, including photosynthesis and respiration. Quantitative and predictive computational characterization of redox events is therefore highly desirable for enriching our knowledge on mechanistic features of biological redox-active macromolecules. Here, we present the results of computational studies of the redox potential of flavin adenine dinucleotide (FAD) in cryptochrome 1 from <i>Arabidopsis thaliana</i> (Cry1At). The special attention is paid to fundamental aspects of the theoretical description such as the effects of environment polarization and of the long-range electrostatic interactions on the computed energetic parameters. Environment (protein and the solvent) polarization is shown to be crucial for accurate estimates of the redox potential: hybrid quantum-classical results with and without account for environment polarization differ by 1.4 V. Long-range electrostatic interactions are shown to contribute significantly to the computed redox potential value even at the distances far beyond the protein outer surface. The theoretical estimate (0.07 V) of the midpoint reduction potential of FAD in Cry1At is reported for the first time and is in good agreement with available experimental data.

Simulating Redox Potentials of Biomolecules: the Case of Cryptochrome 1 from Arabidopsis thaliana

Redox reactions play a key role in various biological processes, including photosynthesis and respiration. Quantitative and predictive computational characterization of redox events is therefore highly desirable for enriching our knowledge on mechanistic features of biological redox-active macromolecules. Here, we present the results of computational studies of the redox potential of flavin adenine dinucleotide (FAD) in cryptochrome 1 from <i>Arabidopsis thaliana</i> (Cry1At). The special attention is paid to fundamental aspects of the theoretical description such as the effects of environment polarization and of the long-range electrostatic interactions on the computed energetic parameters. Environment (protein and the solvent) polarization is shown to be crucial for accurate estimates of the redox potential: hybrid quantum-classical results with and without account for environment polarization differ by 1.4 V. Long-range electrostatic interactions are shown to contribute significantly to the computed redox potential value even at the distances far beyond the protein outer surface. The theoretical estimate (0.07 V) of the midpoint reduction potential of FAD in Cry1At is reported for the first time and is in good agreement with available experimental data.

Modeling the electrical double layer to understand the reaction environment in a CO2 electrocatalytic system

Electrical double layer defines the reaction environment by influencing transport of CO2, local pH, electrical field strength and solvent polarization.