Our picture of reactions on electronically excited states has evolved considerably in recent years, due to advances in our understanding of points of degeneracy between different electronic states, termed "conical intersections" (CIs). CIs serve as funnels for population transfer between different electronic states, and play a central role in ultrafast photochemistry. Because most practical photochemistry occurs in solution and protein environments, it is important to understand the role complex environments play in directing excited-state dynamics generally, as well as specific environmental effects on CI geometries and energies. In order to model such effects, we employ the full multiple spawning (FMS) method for multistate quantum dynamics, together with hybrid quantum mechanical/molecular mechanical (QM/MM) potential energy surfaces using both semiempirical and ab initio QM methods. In this article, we present an overview of these methods, and a comparison of the excited-state dynamics of several biological chromophores in solvent and protein environments. Aqueous solvation increases the rate of quenching to the ground state for both the photoactive yellow protein (PYP) and green fluorescent protein (GFP) chromophores, apparently by energetic stabilization of their respective CIs. In contrast, solvation in methanol retards the quenching process of the retinal protonated Schiff base (RPSB), the rhodopsin chromophore. Protein environments serve to direct the excited-state dynamics, leading to higher quantum yields and enhanced reaction selectivity.

This paper presents an overview of recent experiments and theoretical developments aimed at using vibrational spectroscopy to understand the structure and dynamics of nitrile-labeled biomolecules. Nitrile groups are excellent vibrational probes of proteins and DNA because they absorb in a region of the spectrum that is relatively free of absorption due to the biomolecule, and they have high extinction coefficients. The vibrational frequency of nitrile groups is also extraordinarily sensitive to its local environment, and thus C[triple bond, length as m-dash]N bonds have been employed in both linear and 2-D infrared (IR) spectroscopy experiments and also as vibrational Stark probes of electric fields in proteins. The interpretation and design of these experiments would be enhanced by accurate calculations of IR spectra from molecular dynamics simulations. Recently, theoretical developments towards computing the vibrational spectrum of nitrile groups in the condensed-phase have been highly successful. A strong synergy between experiment and theory will further promote the use of vibrational spectroscopy of nitrile-labeled biomolecules to address fundamental questions of structure and dynamics that are elusive to other techniques.

The C[TRIPLE BOND]N bond is a powerful probe of protein structure and dynamics because it absorbs in a region of the infrared spectrum apart from the other vibrations that occur naturally in proteins, and because its infrared absorption line shape is sensitive to specific characteristics of the local environment. Since the polarity experienced by the probe can differ dramatically within the protein, infrared spectroscopy of a C[TRIPLE BOND]N site-specifically labeled residue can be used to infer its local environment within the protein. It has been shown experimentally that the spectrum of acetonitrile in water is different in terms of peak position and width compared to acetonitrile in tetrahydrofuran (THF). An optimized quantum mechanics/molecular mechanics method for calculating accurate vibrational frequencies in condensed-phase was parametrized for acetonitrile in water. The transferability of the methodology to a different solvent was tested by computing the infrared line shapes of acetonitrile in both water and THF and comparing to experiment. The infrared absorption line shapes agree well with experiment in each case, and the trends observed experimentally are recovered. The accuracy of the methodology for two solvents of differing polarity indicates that this technique is suitable to study CN probes in proteins.

There are many well-known differences in the physical and chemical properties of ozone (O3) and sulfur dioxide (SO2). O3 has longer and weaker bonds than O2, whereas SO2 has shorter and stronger bonds than SO. The O-O2 bond is dramatically weaker than the O-SO bond, and the singlet-triplet gap in SO2 is more than double that in O3. In addition, O3 is a very reactive species, while SO2 is far less so. These disparities have been attributed to variations in the amount of diradical character in the two molecules. In this work, we use generalized valence bond (GVB) theory to characterize the electronic structure of ozone and sulfur dioxide, showing O3 does indeed possess significant diradical character, whereas SO2 is effectively a closed shell molecule. The GVB results provide critical insights into the genesis of the observed difference in these two isoelectronic species. SO2 possesses a recoupled pair bond dyad in the a"(π) system, resulting in SO double bonds. The π system of O3, on the other hand, has a lone pair on the central oxygen atom plus a pair of electrons in orbitals on the terminal oxygen atoms that give rise to a relatively weak π interaction.

A new discretization for the polarizable continuum model within the domain decomposition paradigm

One emerging approach for the fabrication of complex architectures on the nanoscale is to utilize particles customized to intrinsically self-assemble into a desired structure. Inverse methods of statistical mechanics have proven particularly effective for the discovery of interparticle interactions suitable for this aim. Here we evaluate the generality and robustness of a recently introduced inverse design strategy [Lindquist et al., J. Chem. Phys. 145, 111101 (2016)] by applying this simulated-based, machine learning method to optimize for interparticle interactions that self-assemble particles into a variety of complex microstructures: cluster fluids, porous mesophases, and crystalline lattices. Using the method, we discover isotropic pair interactions that lead to self-assembly of each of the desired morphologies, including several types of potentials that were not previously understood to be capable of stabilizing such systems. One such pair potential led to assembly of the highly asymmetric truncated trihexagonal lattice and another produced a fluid containing spherical voids, or pores, of designed size via purely repulsive interactions. Through these examples, we demonstrate several advantages inherent to this particular design approach including the use of a parametrized functional form for the optimized interparticle interactions, the ability to constrain the range of said parameters, and compatibility of the inverse design strategy with a variety of simulation protocols (e.g., positional restraints).

Controlled micro- to meso-scale porosity is a common materials design goal with possible applications ranging from molecular gas adsorption to particle size selective permeability or solubility. Here, we use inverse methods of statistical mechanics to design an isotropic pair interaction that, in the absence of an external field, assembles particles into an inhomogeneous fluid matrix surrounding pores of prescribed size ordered in a lattice morphology. The pore size can be tuned via modification of temperature or particle concentration. Moreover, modulating density reveals a rich series of microphase-separated morphologies including pore- or particle-based lattices, pore- or particle-based columns, and bicontinuous or lamellar structures. Sensitivity of pore assembly to the form of the designed interaction potential is explored.

The nitrile (Ctriple bondN) group is a powerful probe of structure and dynamics because its vibrational frequency is extraordinarily sensitive to the electrostatic and chemical characteristics of its local environment. For example, site-specific nitrile labels are useful indicators of protein structure because their infrared (IR) absorption spectra can clearly distinguish between solvent-exposed residues and residues buried in the hydrophobic core of a protein. In this work, three variants of the optimized quantum mechanics/molecular mechanics (OQM/MM) technique for computing Ctriple bondN vibrational frequencies were developed and assessed for acetonitrile in water. For the most robust variant, the transferability of the OQM/MM methodology to different solutes and solvents was evaluated by simulating the IR absorption spectra of para-tolunitrile in water and tetrahydrofuran and comparing to experiment and density functional theory (DFT) calculations. The OQM/MM frequencies compared favorably to DFT for para-tolunitrile/water, and the calculated IR absorption spectra are in qualitative agreement with experiment. This suggests that a single parametrization of the OQM/MM technique is reasonable for the calculation of nitrile line shapes when the probe is attached to different chemical moieties and when the label experiences local environments of different polarity.