Electron density of a benzoylated tetrafructopyranose

The electron density distribution (EDD) of a tetrasaccharide composed of four benzoylated fructopyranosyl units was obtained by refinement with scattering factors from the invariom library. X-ray diffraction data was downloaded from the Cambridge Structural Database (CSD). Bond topological and atomic properties were obtained by application of Bader’s QTAIM formalism. From a large number of 105 C–C bonds in the molecule average bond orders for 33 single and 72 aromatic bonds were calculated yielding values of 1.33 and 1.61. Molecular Hirshfeld and electrostatic potential (ESP) surfaces show that only weak non-covalent interactions exist. The phenyl rings of the benzoyl fragments in the outer regions of the molecule generate a positive ESP shell with repulsive properties between adjacent molecules. Weak surface interactions result in a rather unusual low density around 1.3 g cm−3, which is understandable when compared to other carbohydrates where strong O–H⋯O hydrogen bonds allow a 20% more dense packing with densities >1.5 g cm−3 as determined by single crystal X-ray diffraction.

Bare singulars and singularity in Turkish

This paper explores the semantics of bare singulars in Turkish, which are unmarked for number in form, as in English, but can behave like both singular and plural terms, unlike in English. While they behave like singular terms as case-marked arguments, they are interpreted number neutrally in non-case-marked argument positions, the existential copular construction, and the predicate position. Previous accounts (Bliss, in Calgary Papers in Linguistics 25:1–65, 2004; Bale et al. in Semantics and Linguistic Theory (SALT) 20:1–15, 2010; Görgülü, in: Semantics of nouns and the specification of number in Turkish, Ph.d. thesis, Simon Fraser University, 2012) propose that Turkish bare singulars denote number neutral sets and that morphologically plural marked nouns denote sets of pluralities only. This approach leads to a symmetric correlation of morphological and semantic (un)markedness. However, in this paper, I defend a strict singular view for bare singulars and show that Turkish actually patterns with English where this correlation is exhibited asymmetrically. I claim that bare singulars in Turkish denote atomic properties and that bare plurals have a number neutral semantics as standardly assumed for English. I argue that the apparent number neutrality of bare singulars in the three cases arises via singular kind reference, which I show to extend to the phenomenon called pseudo-incorporation and a construction that I call kind specification. I argue that pseudo-incorporation occurs in non-case-marked argument positions following Öztürk (Case, referentiality, and phrase structure, Amsterdam, Benjamins, Publishing Company, 2005) and the existential copular construction, whereas kind specification is realized in the predicate position. The different behaviors of bare singulars in Turkish and English stem from the fact that singular kind reference is used more extensively in Turkish than in English. Furthermore, while there are well-known asymmetries between singular and plural kind reference cross-linguistically, Turkish manifests a more restricted distribution for bare plurals than English in the positions where pseudo-incorporation and kind specification are in evidence. I explain this as a blocking effect, specific to Turkish, by singular kind terms on plural kind terms.

Quantitative structure-activity relationship study on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a 1,2,4-Triazol-3-yl group as a ZBG

QSAR study has been carried out on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a1,2,4-triazol-3-yl group as a ZBG in 0D- to 2D-Dragon descriptors. The derived QSAR models have revealed that the number of Sulfur atoms (descriptor nS), Balaban mean square distance index (descriptor MSD), molecular electrotopological variation (descriptor DELS), structural information content index of neighborhood symmetry of 2nd and 3rd order (descriptors SIC2 and SIC3), average valence connectivity index chi-4 (descriptor X4Av) in addition to 1st order Galvez topological charge index (descriptor JGI1) and global topological charge index (descriptor JGT) played a pivotal role in rationalization of MMP-13 inhibition activity of titled compounds. Atomic properties such as mass and volume in terms of atomic properties weighted descriptors MATS5m and MATS3v, and certain atom centred fragments such as CH2RX (descriptor C-006), X--CX--X (descriptor C-044), H attached to heteroatom (descriptor H-050) and H attached to C0(sp3) with 1X attached to next C (descriptor H-052) are also predominant to explain MMP-13 inhibition actions of fused pyrimidines. PLS analysis has also corroborated the dominance of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high-quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.

General QSPR Protocol for Atomic/Inter-atomic Properties Predictions: Fragments based Graph Convolutional Neural Network (F-GCN)

In this study, a general quantitative structure-property relationship (QSPR) protocol, fragments based graph convolutional neural network (F-GCN), was developed for atomic and inter-atomic properties predictions. We applied this novel artificial intelligence (AI) tool in NMR chemical shifts and bond dissociation energies (BDEs) predictions. The predicted results were comparable to experimental measurement, while the computational cost was substantially reduced, with respect to pure density functional theory (DFT) calculations. The two important features of F-GCN can be summarised as: first, it could utilise different levels of molecular fragments centered at the target chemical bonds for atomic and inter-atomic information extraction; second, the designed architecture is also open to include additional descriptors for more accurate solution of chemical environment, making itself more efficient for local properties descriptions. And during our test, the averaged prediction error of ¹H NMR chemical shifts can be as small as 0.32 ppm; and the error of C-H BDEs estimations, is 2.7 kcal/mol. Moreover, we further demonstrated the applicability of this developed F-GCN model via several challenging structural assignments. The success of the F-GCN in atomic and inter-atomic predictions also indicates an essential improvement of computational chemistry with the assistance of AI tools.

In Silico Modelling: Electronic Properties of Phosphorene Monoflakes and Biflakes Substituted With Al, Si, and S Heteroatoms

This contribution explores the systematic substitution of monoflakes (Mfs) and biflakes (Bfs) phosphorene with aluminum, silicon, and sulfur. All this was investigated using functional TPSS and CASSCF calculations. Al and Si substitution produces significant structural changes in both Mfs and Bfs compared to S-substituted and pristine systems. However, in Mfs, all heteroatoms generate a decrease in band gap and the ionization potentials (IP), and an increase in electron affinity (EA) in comparison with pristine phosphorene. Al doping improves the hole mobility in the phosphorene monoflake, while Si and S substitutions exhibit a similar behavior on EAs and reorganization energies. For Bfs, the interlaminar interactions Si-Si and Al-P cause structural changes and higher binding energies for Si-Bfs and Al-Bfs. Regarding the electronic properties of Bfs, substitution with Si does not produce significant variations in the band gap. However, it conduces to the formation of hole transport materials concerning its monolayer counterpart. It also is observed in Al-systems, whereas for S-complexes, no correlation was identified between the doping level and reorganization energies. Also, the substitution with Al and S leads to an opposite behavior of the band gap and IP values, while the variation in EA is similar. In summary, the nature of heteroatom and the doping degree can modify the semiconductor character and electronic properties of phosphorene mono- and the biflakes, whose trends are closely related to the atomic properties of heteroatoms considered. Overall, these computational calculations provide significant insights into the study of doped phosphorene materials.

General QSPR Protocol for Atomic/Inter-atomic Properties Predictions: Fragments based Graph Convolutional Neural Network (F-GCN)

In this study, a general quantitative structure-property relationship (QSPR) protocol, fragments based graph convolutional neural network (F-GCN), was developed for atomic and inter-atomic properties predictions. We applied this novel artificial intelligence (AI) tool in NMR chemical shifts and bond dissociation energies (BDEs) predictions. The predicted results were comparable to experimental measurement, while the computational cost was substantially reduced, with respect to pure density functional theory (DFT) calculations. The two important features of F-GCN can be summarised as: first, it could utilise different levels of molecular fragments centered at the target chemical bonds for atomic and inter-atomic information extraction; second, the designed architecture is also open to include additional descriptors for more accurate solution of chemical environment, making itself more efficient for local properties descriptions. And during our test, the averaged prediction error of ¹H NMR chemical shifts can be as small as 0.32 ppm; and the error of C-H BDEs estimations, is 2.7 kcal/mol. Moreover, we further demonstrated the applicability of this developed F-GCN model via several challenging structural assignments. The success of the F-GCN in atomic and inter-atomic predictions also indicates an essential improvement of computational chemistry with the assistance of AI tools.