Friends and relatives: insight into conformational regulation from orthologues and evolutionary lineages using KIF and KIN.

Noncovalent interaction networks provide a powerful means to represent and analyze protein structure. Such networks can represent both static structures and dynamic conformational ensembles. We have recently developed two tools for analyzing such interaction networks and generating hypotheses for protein engineering. Here, we apply these tools to the conformational regulation of substrate specificity in class A ß-lactamases, particularly the evolutionary development from generalist to specialist catalytic function and how that can be recapitulated or reversed by protein engineering. These tools, KIF and KIN, generate a set of prioritized residues and interactions as targets for experimental protein engineering.

Key interaction networks: Identifying evolutionarily conserved non-covalent interaction networks across protein families.

Protein structure (and thus function) is dictated by non-covalent interaction networks. These can be highly evolutionarily conserved across protein families, the members of which can diverge in sequence and evolutionary history. Here we present KIN, a tool to identify and analyze conserved non-covalent interaction networks across evolutionarily related groups of proteins. KIN is available for download under a GNU General Public License, version 2, from https://www.github.com/kamerlinlab/KIN. KIN can operate on experimentally determined structures, predicted structures, or molecular dynamics trajectories, providing insight into both conserved and missing interactions across evolutionarily related proteins. This provides useful insight both into protein evolution, as well as a tool that can be exploited for protein engineering efforts. As a showcase system, we demonstrate applications of this tool to understanding the evolutionary-relevant conserved interaction networks across the class A ß-lactamases.

Solvent and A-Site Cation Control Preferred Crystallographic Orientation in Bromine-Based Perovskite Thin Films.

Preferred crystallographic orientation in polycrystalline films is desirable for efficient charge carrier transport in metal halide perovskites and semiconductors. However, the mechanisms that determine the preferred orientation of halide perovskites are still not well understood. In this work, we investigate crystallographic orientation in lead bromide perovskites. We show that the solvent of the precursor solution and organic A-site cation strongly affect the preferred orientation of the deposited perovskite thin films. Specifically, we show that the solvent, dimethylsulfoxide, influences the early stages of crystallization and induces preferred orientation in the deposited films by preventing colloidal particle interactions. Additionally, the methylammonium A-site cation induces a higher degree of preferred orientation than the formamidinium counterpart. We use density functional theory to show that the lower surface energy of the (100) plane facets in methylammonium-based perovskites, compared to the (110) planes, is the reason for the higher degree of preferred orientation. In contrast, the surface energy of the (100) and (110) facets is similar for formamidinium-based perovskites, leading to lower degree of preferred orientation. Furthermore, we show that different A-site cations do not significantly affect ion diffusion in bromine-based perovskite solar cells but impact ion density and accumulation, leading to increased hysteresis. Our work highlights the interplay between the solvent and organic A-site cation which determine crystallographic orientation and plays a critical role in the electronic properties and ionic migration of solar cells.

A multi-fragment real-time extension of projected density matrix embedding theory: Non-equilibrium electron dynamics in extended systems.

In this work, we derive a multi-fragment real-time extension of the projected density matrix embedding theory (pDMET) designed to treat non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static pDMET, the real time pDMET partitions the total system into many fragments; the coupling between each fragment and the rest of the system is treated through a compact representation of the environment in terms of a quantum bath. The real-time pDMET involves simultaneously propagating the wavefunctions for each separate fragment-bath embedding system along with an auxiliary mean-field wavefunction of the total system. The equations of motion are derived by (i) projecting the time-dependent Schrödinger equation in the fragment and bath space associated with each separate fragment and by (ii) enforcing the pDMET matching conditions between the global 1-particle reduced density matrix (1-RDM) obtained from the fragment calculations and the mean-field 1-RDM at all points in time. The accuracy of the method is benchmarked through comparisons to time-dependent density-matrix renormalization group and time-dependent Hartree-Fock (TDHF) theory; the methods were applied to a one- and two-dimensional single-impurity Anderson model and multi-impurity Anderson models with ordered and disordered distributions of the impurities. The results demonstrate a large improvement over TDHF and rapid convergence to the exact dynamics with an increase in fragment size. Our results demonstrate that the real-time pDMET is a promising and flexible method that balances accuracy and efficiency to simulate the non-equilibrium electron dynamics in heterogeneous systems of large size.

Changes in Arsenic, Copper, Iron, Manganese, and Zinc Levels Resulting from the Application of Poultry Litter to Agricultural Soils.

Twelve applications of poultry litter were made to a 2.1-ha field located in the Shenandoah Valley of Virginia, United States (USA), between March 1999 and August 2014. The field was planted with bermudagrass (Cynodon dactylon) and used as a pasture on an active farm. Copper, iron, manganese, zinc, and arsenic concentrations in the poultry litter were measured, and the application rates of these metals were calculated. The median application rates were: Cu, 1.32 kg/ha, Fe, 5.57 kg/ha, Mn, 1.80 kg/ha, Zn, 1.39 kg/ha, and As, 0.011 kg/ha. Twelve surface and subsurface soil samples were taken from the treated field in February 2016. Twelve samples were also taken from a comparison site. The comparison site was directly adjacent to the study site, consisted of the same soil type, and had been maintained as an undisturbed forest. Extractable Cu, Fe, Mn, Zn, and As concentrations in the soil samples were determined by atomic absorption spectroscopy, and the results of the chemical analysis were analyzed by ANOVA. Fe and Mn were depleted from the soil in the treated field, while Cu and Zn levels increased over the 12 years of treatment and grazing, and arsenic levels were unchanged in both the surface and subsurface soils between the comparison and the study site. The changes observed for Cu, Fe, Mn, and Zn are within the critical deficiency level and critical toxicity level for these metals, and no arsenic remains in the soil from roxarsone feed supplements, which were added to the poultry feed when the litter was applied to the study site.