Nature of partial sigma bond.

This study investigates the formation of partial sigma (σ) covalent bonds in experimentally synthesizable biradicals formed from hydrogenated and fluorinated C8, C20, and C60 cage structures, by assessing their stability, geometry, and bonding character in singlet and triplet states using restricted B3LYP-D3/6-31+G(d,p) theory, natural bond orbital (NBO) analysis, and complete active space self-consistent field (CASSCF) method. The results show that these partial σCC bonds have Wiberg bond orders of 0.38 to 0.48 and bond lengths ranging from 2.62 Å to 5.93 Å. Cage size influences the characteristics of the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), with electrons favoring more antibonding orbitals in smaller cages where electrons reside more on the exterior of the cage and favoring bonding orbitals in larger ones where electrons are more in the interior. Fluorination enhances electron density on bonding orbitals. The analysis further clarified that the differentiation between antibonding and bonding features of HOMOs and LUMOs extends beyond merely electron transfer from s- to p-atomic orbitals, also noting possible interactions of the same symmetry repel. The study also introduces hyperconjugation from α-position CH bonds as a factor in stabilizing partial σ-bond formation. The results also caution against the use of broken symmetry methodology in unrestricted SCF wavefunctions for biradicals, such as those in this study as it may cause large spin contamination and thus errors in the calculated electronic properties results.

Atom-Based Machine Learning Model for Quantitative Property-Structure Relationship of Electronic Properties of Fusenes and Substituted Fusenes.

This study presents the development of machine-learning-based quantitative structure-property relationship (QSPR) models for predicting electron affinity, ionization potential, and band gap of fusenes from different chemical classes. Three variants of the atom-based Weisfeiler-Lehman (WL) graph kernel method and the machine learning model Gaussian process regressor (GPR) were used. The data pool comprises polycyclic aromatic hydrocarbons (PAHs), thienoacenes, cyano-substituted PAHs, and nitro-substituted PAHs computed with density functional theory (DFT) at the B3LYP-D3/6-31+G(d) level of theory. The results demonstrate that the GPR/WL kernel methods can accurately predict the electronic properties of PAHs and their derivatives with root-mean-square deviations of 0.15 eV. Additionally, we also demonstrate the effectiveness of the active learning protocol for the GPR/WL kernel methods pipeline, particularly for data sets with greater diversity. The interpretation of the model for contributions of individual atoms to the predicted electronic properties provides reasons for the success of our previous degree of π-orbital overlap model.

Computational Design of a Lantern Organic Framework.

This study employed a computational quantum chemistry approach to design lantern organic framework (LOF) materials. Using the density functional theory method with the B3LYP-D3/6-31+G(d) level theory, novel lantern molecules ranging from two to eight bridges made of sp3 and sp carbon atoms to connect circulene bases that have phosphorous or silicon as anchor atoms were made. It was found that five-sp3-carbon and four-sp-carbon bridges are optimal candidates for constructing the lantern framework in the vertical direction. Although circulenes can be stacked vertically, their resulting HOMO-LUMO gaps remain relatively unchanged, indicating their potential applications as porous materials and for host-guest chemistry. The electrostatic potential surface maps reveal that LOF materials are relatively electrostatically neutral overall.

Machine Learning-Based Quantitative Structure-Property Relationships for the Electronic Properties of Cyano Polycyclic Aromatic Hydrocarbons.

In this study, quantitative structure-property relationships (QSPR) based on a machine learning (ML) methodology and the truncated degree of π-orbital overlap (DPO) to predict the electronic properties, namely, the bandgaps, electron affinities, and ionization potentials of the cyano polycyclic aromatic hydrocarbon (CN-PAH) chemical class were developed. The level of theory B3LYP/6-31+G(d) of density functional theory (DFT) was used to calculate a total of 926 data points for the development of the QSPR model. To include the substituents effects, a new descriptor was added to the DPO model. Consequently, the new ML-DPO model yields excellent linear correlations to predict the desired electronic properties with high accuracy to within 0.2 eV for all multi-CN-substituted PAHs and 0.1 eV for the mono-CN-substituted PAH subclass.

Gagones A-F: Six prenylated chalcones from the heartwood of Mansonia gagei.

Six undescribed prenylated chalcones gagones A-F were isolated from the acetone fraction of Mansonia gagei heartwood. Their structures were unambiguously established based on spectroscopic analysis (HRESIMS, 1D and 2D NMR), as well as comparison to literature data. Their absolute configurations were elucidated using DP4 and electronic circular dichroism calculations. Isolated compounds were evaluated for their inhibitory activity against α-glucosidase and DPPH assay. All of the tested compounds exhibited better activity than that of acarbose (IC50 93.6 ± 0.5 µM). Among them, gagone D exhibited the highest α-glucosidase inhibitory with the IC50 value of 3.6 ± 0.4 µM. For antioxidant activity, gagones A-C, and E showed more active than that of ascorbic acid (IC50 30.2 ± 0.5 µM) with the IC50 values of 13.2 ± 0.7, 20.1 ± 0.4, 19.3 ± 0.5 and 12.8 ± 0.2 µM, respectively.

Computational Study on the Nature of Bonding between Silver Ions and Nitrogen Ligands.

In this paper, the nature of silver ion-nitrogen atom bonding in the complexation with ammonia, azomethine, pyridine, and hydrogen cyanide from one to four coordinations is studied at the B97-1 level of density functional theory. The results indicate that the two-coordinated complex of the silver ion with different nitrogen ligands representing sp, sp2, and sp3 orbital hybridizations is the most stable form having the shortest Ag+-N bond distance, highest vibrational frequencies, largest bond order, and favorable Gibbs free energy of formation. Natural bond orbital analyses further show that σ-donation from the nitrogen lone pair to the silver empty 5s orbital is dominant in the dative metal-ligand bonding character with N-sp3 having the largest contribution among the different N atomic orbital hybridizations. Natural energy decomposition analyses further show that the two-coordinated complexes have enhanced electrostatic interaction and charge transfer energies over other coordination types leading them to be more stable. For this reason, the two-coordinated complexes would be a better representation for studying bonding and interaction in silver ion complexes.

Application of Machine Learning in Developing Quantitative Structure-Property Relationship for Electronic Properties of Polyaromatic Compounds.

The degree of π orbital overlap (DPO) model has been demonstrated to be an excellent quantitative structure-property relationship (QSPR) that can map two-dimensional structural information of polycyclic aromatic hydrocarbons (PAHs) and thienoacenes to their electronic properties, namely, band gaps, electron affinities, and ionization potentials. However, the model suffers from significant limitations that narrow its applications due to inefficient manual procedures in parameter optimization and descriptor formulation. In this work, we developed a machine learning (ML)-based method for efficiently optimizing DPO parameters and proposed a truncated DPO descriptor, which is simple enough that can be automatically extracted from simplified molecular-input line-entry system strings of PAHs and thienoacenes. Compared with the result from our previous studies, the ML-based methodology can optimize DPO parameters with four times fewer data, while it can achieve the same level of accuracy in predictions of the mentioned electronic properties to within 0.1 eV. The truncated DPO model also has similar accuracy to the full DPO model. Consequently, the ML-based DPO approach coupled with the truncated DPO model enables new possibilities for developing automatic pipelines for high-throughput screening and investigating new QSPR for new chemical classes.

A Computational Study of the Electronic Properties of Heterocirculenes: Oxiflowers and Sulflowers.

This study investigated the relationship of electronic properties with some structural parameters of two circulene classes: Sulflowers and Oxiflowers. It is found that correlations between the HOMO-LUMO gap and some electronic properties of these circulenes are opposite to those of linear conjugated structures. Moreover, a new hybrid molecule, called an Oxisulflower, is proposed to be a potential structure for synthesizing as Sulflower. Also, a brand-new descriptor, namely, the "degree of non-planarity", is evaluated with excellent correlations with the HOMO-LUMO gap of molecules in Oxiflower and Sulflower classes. The correlations have also shown that the steric characteristic of a structure can be controlled to modulate its band gap for studying the prediction science of the electronic properties in developing organic semiconductors.

Quantum Mechanical-Based Quantitative Structure-Property Relationships for Electronic Properties of Two Large Classes of Organic Semiconductor Materials: Polycyclic Aromatic Hydrocarbons and Thienoacenes.

In this study, the degree of the π-orbital overlap (DPO) model proposed earlier for polycyclic aromatic hydrocarbons (PAH) was employed to develop quantitative structure-property relationships (QSPRs) for band gaps, ionization potentials, and electron affinities of thienoacenes. DPO is based on two-dimensional topological draw of aromatic molecules. The B3LYP/6-31+G(d) level of density functional theory (DFT) was used to provide chemical data for developing QSPRs. We found that the DPO model is able to capture the correct physics of electronic properties of aromatic molecules so that with only six nonzero topological parameters (four for PAH and additional two for thienoacenes), the DPO model yields the linear dependence of electronic properties of both the PAH and thienoacenes classes by a single set of QSPRs with the accuracy to within 0.1 eV of the DFT results. The results suggest that within the DPO framework, all aromatic molecules can share the same set of QSPRs.

Impact of a chemotherapy workload and productivity dashboard on pharmacy technician turnover.

PURPOSE: To describe the methods used in the development of an intravenous chemotherapy workload and productivity dashboard and its impact on symptoms of burnout and technician turnover. SUMMARY: In February 2017, chemotherapy sterile preparation pharmacy technicians reported symptoms of burnout as a result of perceived increase in workload. In response, an i.v. chemotherapy workload and productivity dashboard was developed at an academic medical center to validate workload in comparison to the reported job stress of pharmacy technicians. The dashboard provided pharmacy leadership objective data to validate staff concerns and leveraged lean principles to level-load the work prior to requesting additional full-time equivalents (FTEs) to senior leadership. The rate of turnover of i.v. chemotherapy technicians was assessed before (December 2016-June 2017) and after (July 2017-January 2018) dashboard implementation and approval of an additional i.v. chemotherapy technician FTE. The addition of the new FTE resulted in a decrease in productivity from an average of 106% (range 67%-151%) to 84% (range 65%-110%). The interventions allowed for the ability to leverage a staffing-to-demand model, resulting in the observed improvement in technician symptoms of burnout and a notable decrease in the overall turnover rate of i.v. chemotherapy technicians. CONCLUSION: The i.v. chemotherapy workload and productivity dashboard confirmed frontline staff perception and provided data to support the addition of labor resource and an opportunity to leverage a staffing-to-demand model to decrease symptoms of burnout and technician turnover.

Quantitative Structure-Property Relationships for the Electronic Properties of Polycyclic Aromatic Hydrocarbons.

This study presents a development in quantitative structure-property relationships (QSPRs) for research in organic semiconductor materials by introducing a new structural descriptor called "degree of π-orbital overlap" based on two-dimensional structure information of aromatic molecules. Application of this method to predict the electronic properties of polycyclic aromatic hydrocarbon (PAH) molecules, which are known to be the core component of many organic semiconductor materials, is presented. Results demonstrated that QSPRs based on the new descriptor can predict rather accurate band gaps, ionization potentials and electron affinities for a large number of PAHs compared to those explicitly calculated by density functional theory method. This research opens new possibilities for developing QSPRs for other organic semiconductor classes in future.

Molecular interactions of human Exo1 with DNA.

Human Exo1 is a member of the RAD2 nuclease family with roles in replication, repair and recombination. Despite sharing significant amino acid sequence homology, the RAD2 proteins exhibit disparate nuclease properties and biological functions. In order to identify elements that dictate substrate selectivity within the RAD2 family, we sought to identify residues key to Exo1 nuclease activity and to characterize the molecular details of the human Exo1-DNA interaction. Site-specific mutagenesis studies demonstrate that amino acids D78, D173 and D225 are critical for Exo1 nuclease function. In addition, we show that the chemical nature of the 5'-terminus has a major impact on Exo1 nuclease efficiency, with a 5'-phosphate group stimulating degradation 10-fold and a 5'-biotin inhibiting degradation 10-fold (relative to a 5'-hydroxyl moiety). An abasic lesion located within a substrate DNA strand impedes Exo1 nucleolytic degradation, and a 5'-terminal abasic residue reduces nuclease efficiency 2-fold. Hydroxyl radical footprinting indicates that Exo1 binds predominantly along the minor groove of flap DNA, downstream of the junction. As will be discussed, our results favor the notion that the single-stranded DNA structure is pinched by the helical arch of the protein and not threaded through this key recognition loop. Furthermore, our studies indicate that significant, presumably biologically relevant, differences exist between the active site dynamics of Exo1 and Fen1.

Determinants in nuclease specificity of Ape1 and Ape2, human homologues of Escherichia coli exonuclease III.

Abasic sites and non-conventional 3'-ends, e.g. 3'-oxidized fragments (including 3'-phosphate groups) and 3'-mismatched nucleotides, arise at significant frequency in the genome due to spontaneous decay, oxidation or replication errors. To avert the potentially mutagenic or cytotoxic effects of these chromosome modifications/intermediates, organisms are equipped with apurinic/apyrimidinic (AP) endonucleases and 3'-nucleases that initiate repair. Ape1, which shares homology with Escherichia coli exonuclease III (ExoIII), is the major abasic endonuclease in mammals and an important, yet selective, contributor to 3'-end processing. Mammals also possess a second protein (Ape2) with sequence homology to ExoIII, but this protein exhibits comparatively weak AP site-specific and 3'-nuclease activities. Prompted by homology modeling studies, we found that substitutions in the hydrophobic pocket of Ape1 (comprised of F266, W280 and L282) reduce abasic incision potency about fourfold to 450,000-fold, while introduction of an ExoIII-like pocket into Ape2 enhances its AP endonuclease function. We demonstrate that mutations at F266 and W280 of Ape1 increase 3' to 5' DNA exonuclease activity. These results, coupled with prior comparative sequence analysis, indicate that this active-site hydrophobic pocket influences the substrate specificity of a diverse set of sequence-related proteins possessing the conserved four-layered alpha/beta-fold. Lastly, we report that wild-type Ape1 excises 3'-mismatched nucleotides at a rate up to 374-fold higher than correctly base-paired nucleotides, depending greatly on the structure and sequence of the DNA substrate, suggesting a novel, selective role for the human protein in 3'-mismatch repair.