The present approach provides a basis for understanding the origin of the KR2 CD spectrum and is useful for analyzing the mechanism of chromophore-chromophore interactions in biological systems.Kinetics of photoinduced intramolecular charge separation (CS) and the ensuing ultrafast charge recombination (CR) in electron-donor-acceptor dyads are studied numerically, taking into account the excitation of charge-transfer active intramolecular vibrations and multiple relaxation time scales of the surrounding polar solvent. Both energetic and dynamic properties of intramolecular and solvent reorganization are considered, and their influence on the CS/CR kinetics and quantum yield of ultrafast CS is explored. Particular attention is paid to the energy efficiency of CS, as one of the most important parameters indicating the promise of using a molecular compound as a basis for emerging optoelectronic devices. The CS quantum yield and the energy efficiency of CS are shown to depend differently on the key model parameters. Necessary conditions for the highly efficient CS are evaluated using analytic formulae for the electron transfer rates and derived from numerical simulation data. The reasons why low-exergonic CS taking place in the Marcus normal region can be much slower than CR in the deep inverted region are discussed.In this paper, the fifth of our series focused on the dielectric spectrum symmetrical broadening of water, we consider the solutions of methemoglobin (MetHb) in pure water and in phosphate-buffered saline (PBS). The universal character of the Cole-Cole dielectric response, which reflects the interaction of water dipoles with solute molecules, was described in Paper I [E. Levy et al., J. Chem. Phys. 136, 114502 (2012)]. It enables the interpretation of the dielectric data of MetHb solutions in a unified manner using the previously developed 3D trajectory method driven by the protein concentration. It was shown that protein hydration is determined by the interaction of water dipoles with the charges and dipoles located on the rough surfaces of the protein macromolecules. In the case of the buffered solution, the transition from a dipole-charged to a dipole-dipole interaction with the protein concentration is observed see Paper III [A. Puzenko et al., J. Chem. Phys. 137, 194502 (2012)]. A new approach is proposed for evaluating the amount of hydration water molecules bounded to the macromolecule that takes into account the number of positive and negative charges on the protein's surface. In the case of the MetHb solution in PBS, the hydration of the solvent ions and their interaction with charges on the protein's surface are also taken into consideration. The difference in hydration between the two solutions of MetHb is discussed.Recent studies of the weakly bound anisole⋯CH4 complex found a dual mode of binding, featuring both C/H⋯π and C/H⋯O noncovalent interactions. In this work, we examine the dissociation energies of related aniline⋯(CH4)n (n = 1, 2) van der Waals clusters, where both C/H⋯π and C/H⋯N interactions are possible. Using a combination of theory and experiments that include mass-selected two-color resonant two-photon ionization spectroscopy, two-color appearance potential (2CAP) measurements, and velocity-mapped ion imaging (VMI), we derive the dissociation energies of both complexes in the ground (S0), excited (S1), and cation radical (D0) states. As the amide group is non-planar in the ground state, the optimized ground state geometry of the aniline⋯CH4 11 complex shows two isomers, each with the methane positioned above the aniline ring. The observed redshift of the electronic origin from the aniline monomer is consistent with TDDFT calculations for the more stable isomer, where the methane sits on the same face as isole-methane 12 complex, which shows an enhanced dissociation energy for the loss of one methane in comparison with the 11 complex, here, we find that the energy required to remove one methane from the ground state aniline-methane 12 complex is smaller than that of the 11 complex, consistent with theoretical expectations.We study the post-translational escape of nascent proteins at the ribosomal exit tunnel with the consideration of a real shape atomistic tunnel based on the Protein Data Bank structure of the large ribosome subunit of archeon Haloarcula marismortui. Molecular dynamics simulations employing the Go-like model for the proteins show that at intermediate and high temperatures, including a presumable physiological temperature, the protein escape process at the atomistic tunnel is quantitatively similar to that at a cylinder tunnel of length L = 72 Å and diameter d = 16 Å. At low temperatures, the atomistic tunnel, however, yields an increased probability of protein trapping inside the tunnel, while the cylinder tunnel does not cause the trapping. All-β proteins tend to escape faster than all-α proteins, but this difference is blurred on increasing the protein's chain length. A 29-residue zinc-finger domain is shown to be severely trapped inside the tunnel.  https://www.selleckchem.com/products/Sunitinib-Malate-(Sutent).html  Most of the single-domain proteins considered, however, can escape efficiently at the physiological temperature with the escape time distribution following the diffusion model proposed in our previous works. An extrapolation of the simulation data to a realistic value of the friction coefficient for amino acids indicates that the escape times of globular proteins are at the sub-millisecond scale. It is argued that this time scale is short enough for the smooth functioning of the ribosome by not allowing nascent proteins to jam the ribosome tunnel.Intermolecular interactions are critical to many chemical phenomena, but their accurate computation using ab initio methods is often limited by computational cost. The recent emergence of machine learning (ML) potentials may be a promising alternative. Useful ML models should not only estimate accurate interaction energies but also predict smooth and asymptotically correct potential energy surfaces. However, existing ML models are not guaranteed to obey these constraints. Indeed, systemic deficiencies are apparent in the predictions of our previous hydrogen-bond model as well as the popular ANI-1X model, which we attribute to the use of an atomic energy partition. As a solution, we propose an alternative atomic-pairwise framework specifically for intermolecular ML potentials, and we introduce AP-Net-a neural network model for interaction energies. The AP-Net model is developed using this physically motivated atomic-pairwise paradigm and also exploits the interpretability of symmetry adapted perturbation theory (SAPT).