Theoretical description of hydride-hydride interactions in selected hydrogen storage materials.

The high content of hydride-hydride contacts Hδ-···Î´-H in hydrogen storage materials appears to be relevant for hydrogen formation. At present time there is no consensus whether these contacts are attractive or repulsive. Accordingly, the main goal of this article is to shed light on physical factors which constitute homopolar hydride-hydride interactions Hδ-···Î´-H in selected transition metal complexes i.e. HCoL4, L = CO,PPh3,PH3. In order to achieve this goal, the charge and energy decomposition ETS-NOCV approach along with the Interacting Quantum Atoms (IQA) and reduced density gradient (NCI) are applied for the bonded adducts L4CoH···HCoL4. Based on DFT and correlated methods it has been shown, that hydride-hydride interactions might be attractive and even far stronger than classical hydrogen bonds. The stability of the adducts is increased by phosphine ligand installation: overall Hδ-···Î´-H bonding energy changes in the order: CO << PPh3 ~ PH3. It has been revealed that depending on monomer's conformations Hδ-···Î´-H bonds are dominated by charge delocalization or London dispersion forces and the electrostatic term is also relevant. It is finally determined by IQA energy decomposition, that diatomic hydride-hydride interaction CoH···HCo is chameleon-like, namely, it is attractive in CO4CoH···HCoCO4, whereas the repulsion is unveiled in (CO)3(PPh3)CoH···HCo(CO)3(PPh3).

Probing Protein-Ligand Methyl-π Interaction Geometries through Chemical Shift Measurements of Selectively Labeled Methyl Groups.

Fragment-based drug design is heavily dependent on the optimization of initial low-affinity binders. Herein we introduce an approach that uses selective labeling of methyl groups in leucine and isoleucine side chains to directly probe methyl-π contacts, one of the most prominent forms of interaction between proteins and small molecules. Using simple NMR chemical shift perturbation experiments with selected BRD4-BD1 binders, we find good agreement with a commonly used model of the ring-current effect as well as the overall interaction geometries extracted from the Protein Data Bank. By combining both interaction geometries and chemical shift calculations as fit quality criteria, we can position dummy aromatic rings into an AlphaFold model of the protein of interest. The proposed method can therefore provide medicinal chemists with important information about binding geometries of small molecules in fast and iterative matter, even in the absence of high-resolution experimental structures.

Highly Accurate Prediction of NMR Chemical Shifts from Low-Level Quantum Mechanics Calculations Using Machine Learning.

Theoretical predictions of NMR chemical shifts from first-principles can greatly facilitate experimental interpretation and structure identification of molecules in gas, solution, and solid-state phases. However, accurate prediction of chemical shifts using the gold-standard coupled cluster with singles, doubles, and perturbative triple excitations [CCSD(T)] method with a complete basis set (CBS) can be prohibitively expensive. By contrast, machine learning (ML) methods offer inexpensive alternatives for chemical shift predictions but are hampered by generalization to molecules outside the original training set. Here, we propose several new ideas in ML of the chemical shift prediction for H, C, N, and O that first introduce a novel feature representation, based on the atomic chemical shielding tensors within a molecular environment using an inexpensive quantum mechanics (QM) method, and train it to predict NMR chemical shieldings of a high-level composite theory that approaches the accuracy of CCSD(T)/CBS. In addition, we train the ML model through a new progressive active learning workflow that reduces the total number of expensive high-level composite calculations required while allowing the model to continuously improve on unseen data. Furthermore, the algorithm provides an error estimation, signaling potential unreliability in predictions if the error is large. Finally, we introduce a novel approach to keep the rotational invariance of the features using tensor environment vectors (TEVs) that yields a ML model with the highest accuracy compared to a similar model using data augmentation. We illustrate the predictive capacity of the resulting inexpensive shift machine learning (iShiftML) models across several benchmarks, including unseen molecules in the NS372 data set, gas-phase experimental chemical shifts for small organic molecules, and much larger and more complex natural products in which we can accurately differentiate between subtle diastereomers based on chemical shift assignments.

Ligand 1 H NMR Chemical Shifts as Accurate Reporters for Protein-Ligand Binding Interfaces in Solution.

The availability of high-resolution 3D structural information is crucial for investigating guest-host systems across a wide range of fields. In the context of drug discovery, the information is routinely used to establish and validate structure-activity relationships, grow initial hits from screening campaigns, and to guide molecular docking. For the generation of protein-ligand complex structural information, X-ray crystallography is the experimental method of choice, however, with limited information on protein flexibility. An experimentally verified structural model of the binding interface in the native solution-state would support medicinal chemists in their molecular design decisions. Here we demonstrate that protein-bound ligand 1 H NMR chemical shifts are highly sensitive and accurate probes for the immediate chemical environment of protein-ligand interfaces. By comparing the experimental ligand 1 H chemical shift values with those computed from the X-ray structure using quantum mechanics methodology, we identify significant disagreements for parts of the ligand between the two experimental techniques. We show that quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) ensembles can be used to refine initial X-ray co-crystal structures resulting in a better agreement with experimental 1 H ligand chemical shift values. Overall, our findings highlight the usefulness of ligand 1 H NMR chemical shift information in combination with a QM/MM MD workflow for generating protein-ligand ensembles that accurately reproduce solution structural data.

Harnessing PROTAC technology to combat stress hormone receptor activation.

Counteracting the overactivation of glucocorticoid receptors (GR) is an important therapeutic goal in stress-related psychiatry and beyond. The only clinically approved GR antagonist lacks selectivity and induces unwanted side effects. To complement existing tools of small-molecule-based inhibitors, we present a highly potent, catalytically-driven GR degrader, KH-103, based on proteolysis-targeting chimera technology. This selective degrader enables immediate and reversible GR depletion that is independent of genetic manipulation and circumvents transcriptional adaptations to inhibition. KH-103 achieves passive inhibition, preventing agonistic induction of gene expression, and significantly averts the GR's genomic effects compared to two currently available inhibitors. Application in primary-neuron cultures revealed the dependency of a glucocorticoid-induced increase in spontaneous calcium activity on GR. Finally, we present a proof of concept for application in vivo. KH-103 opens opportunities for a more lucid interpretation of GR functions with translational potential.

Correction: Mahmoudi et al. Solvent-Induced Formation of Novel Ni(II) Complexes Derived from Bis-Thiosemicarbazone Ligand: An Insight from Experimental and Theoretical Investigations. Int. J. Mol. Sci. 2021, 22, 5337.

We received a complaint from the Université Catholique de Louvain [...].

Solvent-Induced Formation of Novel Ni(II) Complexes Derived from Bis-Thiosemicarbazone Ligand: An Insight from Experimental and Theoretical Investigations.

In this work, we report solvent-induced complexation properties of a new N2S2 tetradentate bis-thiosemicarbazone ligand (H2LI), prepared by the condensation of 4-phenylthiosemicarbazide with bis-aldehyde, namely 2,2'-(ethane-1,2-diylbis(oxy)dibenzaldehyde, towards nickel(II). Using ethanol as a reaction medium allowed the isolation of a discrete mononuclear homoleptic complex [NiLI] (1), for which its crystal structure contains three independent molecules, namely 1-I, 1-II, and 1-III, in the asymmetric unit. The doubly deprotonated ligand LI in the structure of 1 is coordinated in a cis-manner through the azomethine nitrogen atoms and the thiocarbonyl sulfur atoms. The coordination geometry around metal centers in all the three crystallographically independent molecules of 1 is best described as the seesaw structure. Interestingly, using methanol as a reaction medium in the same synthesis allowed for the isolation of a discrete mononuclear homoleptic complex [Ni(LII)2] (2), where LII is a monodeprotonated ligand 2-(2-(2-(2-(dimethoxymethyl)phenoxy)ethoxy)benzylidene)-N-phenylhydrazine-1-carbothioamide (HLII). The ligand LII was formed in situ from the reaction of LI with methanol upon coordination to the metal center under synthetic conditions. In the structure of 2, two ligands LII are coordinated in a trans-manner through the azomethine nitrogen atom and the thiocarbonyl sulfur atom, also yielding a seesaw coordination geometry around the metal center. The charge and energy decomposition scheme ETS-NOCV allows for the conclusion that both structures are stabilized by a bunch of London dispersion-driven intermolecular interactions, including predominantly N-H∙∙∙S and N-H∙∙∙O hydrogen bonds in 1 and 2, respectively; they are further augmented by less typical C-H∙∙∙X (where X = S, N, O, π), CH∙∙∙HC, π∙∙∙π stacking and the most striking, attractive long-range intermolecular C-H∙∙∙Ni preagostic interactions. The latter are found to be determined by both stabilizing Coulomb forces and an exchange-correlation contribution as revealed by the IQA energy decomposition scheme. Interestingly, the analogous long-range C-H∙∙∙S interactions are characterized by a repulsive Coulomb contribution and the prevailing attractive exchange-correlation constituent. The electron density of the delocalized bonds (EDDB) method shows that the nickel(II) atom shares only ~0.8|e| due to the σ-conjugation with the adjacent in-plane atoms, demonstrating a very weak σ-metalloaromatic character.

Origin of Hydrocarbons Stability from a Computational Perspective: A Case Study of Ortho-Xylene Isomers.

It is shown herein that intuitive and text-book steric-clash based interpretation of the higher energy "in-in" xylene isomer (as arising solely from the repulsive CH⋅⋅⋅HC contact) with respect to the corresponding global-minimum "out-out" configuration (where the clashing C-H bonds are tilted out) is misleading. It is demonstrated that the two hydrogen atoms engaged in the CH⋅⋅⋅HC contact in "in-in" are involved in attractive interaction so they cannot explain the lower stability of this isomer. We have proven, based on the arsenal of modern bonding descriptors (EDDB, HOMA, NICS, FALDI, ETS-NOCV, DAFH, FAMSEC, IQA), that in order to understand the relative stability of "in-in" versus "out-out" xylenes isomers one must consider the changes in the electronic structure encompassing the entire molecules as arising from the cooperative action of hyperconjugation, aromaticity and unintuitive London dispersion plus charge delocalization based intra-molecular CH⋅⋅⋅HC interactions.