Tryptophan to Tryptophan Hole Hopping in an Azurin Construct.

Electron transfer (ET) between neutral and cationic tryptophan residues in the azurin construct [ReI(H126)(CO)3(dmp)](W124)(W122)CuI (dmp = 4,7-Me2-1,10-phenanthroline) was investigated by Born-Oppenheimer quantum-mechanics/molecular mechanics/molecular dynamics (QM/MM/MD) simulations. We focused on W124•+ ← W122 ET, which is the middle step of the photochemical hole-hopping process *ReII(CO)3(dmp•-) ← W124 ← W122 ← CuI, where sequential hopping amounts to nearly 10,000-fold acceleration over single-step tunneling (ACS Cent. Sci. 2019, 5, 192-200). In accordance with experiments, UKS-DFT QM/MM/MD simulations identified forward and reverse steps of W124•+ ↔ W122 ET equilibrium, as well as back ET ReI(CO)3(dmp•-) → W124•+ that restores *ReII(CO)3(dmp•-). Strong electronic coupling between the two indoles (≥40 meV in the crossing region) makes the productive W124•+ ← W122 ET adiabatic. Energies of the two redox states are driven to degeneracy by fluctuations of the electrostatic potential at the two indoles, mainly caused by water solvation, with contributions from the protein dynamics in the W122 vicinity. ET probability depends on the orientation of Re(CO)3(dmp) relative to W124 and its rotation diminishes the hopping yield. Comparison with hole hopping in natural systems reveals structural and dynamics factors that are important for designing efficient hole-hopping processes

Light-Induced Nanosecond Relaxation Dynamics of Rhenium-Labeled Pseudomonas aeruginosa Azurins.

Time-resolved phosphorescence spectra of Re(CO)3(dmp)+ and Re(CO)3(phen)+ chromophores (dmp = 4,7-dimethyl-1,10-phenanthroline, phen = 1,10-phenanthroline) bound to surface histidines (H83, H124, and H126) of Pseudomonas aeruginosa azurin mutants exhibit dynamic band maxima shifts to lower wavenumbers following 3-exponential kinetics with 1-5 and 20-100 ns major phases and a 1.1-2.5 μs minor (5-16%) phase. Observation of slow relaxation components was made possible by using an organometallic Re chromophore as a probe whose long phosphorescence lifetime extends the observation window up to ∼3 μs. Integrated emission-band areas also decay with 2- or 3-exponential kinetics; the faster decay phase(s) is relaxation-related, whereas the slowest one [360-680 ns (dmp); 90-140 ns (phen)] arises mainly from population decay. As a result of shifting bands, the emission intensity decay kinetics depend on the detection wavelength. Detailed kinetics analyses and comparisons with band-shift dynamics are needed to disentangle relaxation and population decay kinetics if they occur on comparable timescales. The dynamic phosphorescence Stokes shift in Re-azurins is caused by relaxation motions of the solvent, the protein, and solvated amino acid side chains at the Re binding site in response to chromophore electronic excitation. Comparing relaxation and decay kinetics of Re(dmp)124K122Cu II and Re(dmp)124W122Cu II suggests that electron transfer (ET) and relaxation motions in the W122 mutant are coupled. It follows that nanosecond and faster photo-induced ET steps in azurins (and likely other redox proteins) occur from unrelaxed systems; importantly, these reactions can be driven (or hindered) by structural and solvational dynamics

Simple eigenvalue-self-consistent Δ ¯ G W 0 .

We show that a rigid scissors-like GW self-consistency approach, labeled here Δ ¯ G W 0 , can be trivially implemented at zero additional cost for large scale one-shot G 0 W 0 calculations. The method significantly improves one-shot G 0 W 0 and for large systems is very accurate. Δ ¯ G W 0 is similar in spirit to evGW 0 where the self-consistency is only applied on the eigenvalues entering Green's function, while both W and the eigenvectors of Green's function are held fixed. Δ ¯ G W 0 further assumes that the shift of the eigenvalues is rigid scissors-like so that all occupied states are shifted by the same amount and analogously for all the unoccupied states. We show that this results in a trivial modification of the time-dependent G 0 W 0 self-energy, enabling an a posteriori self-consistency cycle. The method is applicable for our recent stochastic-GW approach, thereby enabling self-consistent calculations for giant systems with thousands of electrons. The accuracy of Δ ¯ G W 0 increases with the system size. For molecules, it is up to 0.4-0.5 eV away from coupled-cluster single double triple (CCSD(T)), but for tetracene and hexacene, it matches the ionization energies from both CCSD(T) and evGW 0 to better than 0.05 eV. For solids, as exemplified here by periodic supercells of semiconductors and insulators with 6192 valence electrons, the method matches evGW 0 quite well and both methods are in good agreement with the experiment

The Plastid Genome of Eutreptiella Provides a Window into the Process of Secondary Endosymbiosis of Plastid in Euglenids

Euglenids are a group of protists that comprises species with diverse feeding modes. One distinct and diversified clade of euglenids is photoautotrophic, and its members bear green secondary plastids. In this paper we present the plastid genome of the euglenid Eutreptiella, which we assembled from 454 sequencing of Eutreptiella gDNA. Comparison of this genome and the only other available plastid genomes of photosynthetic euglenid, Euglena gracilis, revealed that they contain a virtually identical set of 57 protein coding genes, 24 genes fewer than the genome of Pyramimonas parkeae, the closest extant algal relative of the euglenid plastid. Searching within the transcriptomes of Euglena and Eutreptiella showed that 6 of the missing genes were transferred to the nucleus of the euglenid host while 18 have been probably lost completely. Euglena and Eutreptiella represent the deepest bifurcation in the photosynthetic clade, and therefore all these gene transfers and losses must have happened before the last common ancestor of all known photosynthetic euglenids. After the split of Euglena and Eutreptiella only one additional gene loss took place. The conservation of gene content in the two lineages of euglenids is in contrast to the variability of gene order and intron counts, which diversified dramatically. Our results show that the early secondary plastid of euglenids was much more susceptible to gene losses and endosymbiotic gene transfers than the established plastid, which is surprisingly resistant to changes in gene content

DNA Damage during G2 Phase Does Not Affect Cell Cycle Progression of the Green Alga Scenedesmus quadricauda

DNA damage is a threat to genomic integrity in all living organisms. Plants and green algae are particularly susceptible to DNA damage especially that caused by UV light, due to their light dependency for photosynthesis. For survival of a plant, and other eukaryotic cells, it is essential for an organism to continuously check the integrity of its genetic material and, when damaged, to repair it immediately. Cells therefore utilize a DNA damage response pathway that is responsible for sensing, reacting to and repairing damaged DNA. We have studied the effect of 5-fluorodeoxyuridine, zeocin, caffeine and combinations of these on the cell cycle of the green alga Scenedesmus quadricauda. The cells delayed S phase and underwent a permanent G2 phase block if DNA metabolism was affected prior to S phase; the G2 phase block imposed by zeocin was partially abolished by caffeine. No cell cycle block was observed if the treatment with zeocin occurred in G2 phase and the cells divided normally. CDKA and CDKB kinases regulate mitosis in S. quadricauda; their kinase activities were inhibited by Wee1. CDKA, CDKB protein levels were stabilized in the presence of zeocin. In contrast, the protein level of Wee1 was unaffected by DNA perturbing treatments. Wee1 therefore does not appear to be involved in the DNA damage response in S. quadricauda. Our results imply a specific reaction to DNA damage in S. quadricauda, with no cell cycle arrest, after experiencing DNA damage during G2 phase

Database-driven High-Throughput Calculations and Machine Learning Models for Materials Design

This paper reviews past and ongoing efforts in using high-throughput ab-inito calculations in combination with machine learning models for materials design. The primary focus is on bulk materials, i.e., materials with fixed, ordered, crystal structures, although the methods naturally extend into more complicated configurations. Efficient and robust computational methods, computational power, and reliable methods for automated database-driven high-throughput computation are combined to produce high-quality data sets. This data can be used to train machine learning models for predicting the stability of bulk materials and their properties. The underlying computational methods and the tools for automated calculations are discussed in some detail. Various machine learning models and, in particular, descriptors for general use in materials design are also covered.Comment: 19 pages, 2 figure