Beyond the Status Quo: Density Functional Tight Binding and Neural Network Potentials as a Versatile Simulation Strategy to Characterize Host-Guest Interactions in Metal- and Covalent Organic Frameworks.

In recent years, research focused on synthesis, characterization, and application of metal-organic frameworks (MOFs) has attracted increased interest, from both an experimental as well as a theoretical perspective. Self-consistent charge density functional tight binding (SCC DFTB) in conjunction with a suitable constrained molecular dynamics (MD) simulation protocol provides a versatile and flexible platform for the study of pristine MOFs as well as guest@MOF systems. Although being a semi-empirical quantum mechanical method, SCC DFTB inherently accounts for polarization and many-body contributions, which may become a limiting factor in purely force field-based simulation studies. A number of examples such as CO2, indigo, and drug molecules embedded in various MOF hosts are discussed to highlight the capabilities of the presented simulation approach. Furthermore, a promising extension of the outlined simulation strategy toward the treatment of covalent organic frameworks utilizing state-of-the-art neural network potentials providing a description at DFT accuracy and force field cost is outlined.

Constitutive Correlations for Mass Transport in Fibrous Media Based on Asymptotic Homogenization.

Mass transport in textiles is crucial. Knowledge of effective mass transport properties of textiles can be used to improve processes and applications where textiles are used. Mass transfer in knitted and woven fabrics strongly depends on the yarn used. In particular, the permeability and effective diffusion coefficient of yarns are of interest. Correlations are often used to estimate the mass transfer properties of yarns. These correlations commonly assume an ordered distribution, but here we demonstrate that an ordered distribution leads to an overestimation of mass transfer properties. We therefore address the impact of random ordering on the effective diffusivity and permeability of yarns and show that it is important to account for the random arrangement of fibers in order to predict mass transfer. To do this, Representative Volume Elements are randomly generated to represent the structure of yarns made from continuous filaments of synthetic materials. Furthermore, parallel, randomly arranged fibers with a circular cross-section are assumed. By solving the so-called cell problems on the Representative Volume Elements, transport coefficients can be calculated for given porosities. These transport coefficients, which are based on a digital reconstruction of the yarn and asymptotic homogenization, are then used to derive an improved correlation for the effective diffusivity and permeability as a function of porosity and fiber diameter. At porosities below 0.7, the predicted transport is significantly lower under the assumption of random ordering. The approach is not limited to circular fibers and may be extended to arbitrary fiber geometries.

Bayesian logical neural networks for human-centered applications in medicine.

Background: Medicine is characterized by its inherent uncertainty, i.e., the difficulty of identifying and obtaining exact outcomes from available data. Electronic Health Records aim to improve the exactitude of health management, for instance using automatic data recording techniques or the integration of structured as well as unstructured data. However, this data is far from perfect and is usually noisy, implying that epistemic uncertainty is almost always present in all biomedical research fields. This impairs the correct use and interpretation of the data not only by health professionals but also in modeling techniques and AI models incorporated in professional recommender systems. Method: In this work, we report a novel modeling methodology combining structural explainable models, defined on Logic Neural Networks which replace conventional deep-learning methods with logical gates embedded in neural networks, and Bayesian Networks to model data uncertainties. This means, we do not account for the variability of the input data, but we train single models according to the data and deliver different Logic-Operator neural network models that could adapt to the input data, for instance, medical procedures (Therapy Keys depending on the inherent uncertainty of the observed data. Result: Thus, our model does not only aim to assist physicians in their decisions by providing accurate recommendations; it is above all a user-centered solution that informs the physician when a given recommendation, in this case, a therapy, is uncertain and must be carefully evaluated. As a result, the physician must be a professional who does not solely rely on automatic recommendations. This novel methodology was tested on a database for patients with heart insufficiency and can be the basis for future applications of recommender systems in medicine.

Discovery of Potent and Exquisitely Selective Inhibitors of Kinase CK1 with Tunable Isoform Selectivity.

Casein kinases 1 (CK1) are key signaling molecules that have emerged recently as attractive therapeutic targets in particular for the treatment of hematological malignancies. Herein, we report the identification of a new class of potent and highly selective inhibitors of CK1α, δ and ϵ. Based on their optimal in vitro and in vivo profiles and their exclusive selectivity, MU1250, MU1500 and MU1742 were selected as quality chemical probes for those CK1 isoforms. At proper concentrations, MU1250 and MU1500 allow for specific targeting of CK1δ or dual inhibition of CK1δ/ϵ in cells. The compound MU1742 also efficiently inhibits CK1α and, to our knowledge, represents the first potent and highly selective inhibitor of this enzyme. In addition, we demonstrate that the central 1H-pyrrolo[2,3-b]pyridine-imidazole pharmacophore can be used as the basis of highly selective inhibitors of other therapeutically relevant protein kinases, e.g. p38α, as exemplified by the compound MU1299.

Comparing the efficiency of six clearing methods in developing seeds of Arabidopsis thaliana.

KEY MESSAGE: ClearSee alpha and FAST9 were optimized for imaging Arabidopsis seeds up to the torpedo stages. The methods preserve the fluorescence of reporter proteins and seed shape, allowing phenotyping embryos in intact seeds. Tissue clearing methods eliminate the need for sectioning, thereby helping better understand the 3D organization of tissues and organs. In the past fifteen years, clearing methods have been developed to preserve endogenous fluorescent protein tags. Some of these methods (ClearSee, TDE, PEA-Clarity, etc.) were adapted to clear various plant species, with the focus on roots, leaves, shoot apical meristems, and floral parts. However, these methods have not been used in developing seeds beyond the early globular stage. Tissue clearing is problematic in post-globular seeds due to various apoplastic barriers and secondary metabolites. In this study, we compared six methods for their efficiency in clearing Arabidopsis thaliana seeds at post-globular embryonic stages. Three methods (TDE, ClearSee, and ClearSee alpha) have already been reported in plants, whereas the others (fsDISCO, FAST9, and CHAPS clear) are used in this context for the first time. These methods were assessed for seed morphological changes, clearing capacity, removal of tannins, and spectral properties. We tested each method in seeds from globular to mature stages. The pros and cons of each method are listed herein. ClearSee alpha appears to be the method of choice as it preserves seed morphology and prevents tannin oxidation. However, FAST9 with 60% iohexol as a mounting medium is faster, clears better, and appears suitable for embryonic shape imaging. Our results may guide plant researchers to choose a suitable method for imaging fluorescent protein-labeled embryos in intact Arabidopsis seeds.

Synthesis and Profiling of Highly Selective Inhibitors of Methyltransferase DOT1L Based on Carbocyclic C-Nucleosides.

Histone methyltransferase DOT1L is an attractive therapeutic target for the treatment of hematological malignancies. Here, we report the design, synthesis, and profiling of new DOT1L inhibitors based on nonroutine carbocyclic C-nucleoside scaffolds. The experimentally observed SAR was found to be nontrivial as seemingly minor changes of individual substituents resulted in significant changes in the affinity to DOT1L. Molecular modeling suggested that these trends could be related to significant conformational changes of the protein upon interaction with the inhibitors. The compounds 22 and (-)-53 (MU1656), carbocyclic C-nucleoside analogues of the natural nucleoside derivative EPZ004777, and the clinical candidate EPZ5676 (pinometostat) potently and selectively inhibit DOT1L in vitro as well as in the cell. The most potent compound MU1656 was found to be more metabolically stable and significantly less toxic in vivo than pinometostat itself.

Highly selective inhibitors of protein kinases CLK and HIPK with the furo[3,2-b]pyridine core.

The furo [3,2-b]pyridine motif represents a relatively underexplored central pharmacophore in the area of kinase inhibitors. Herein, we report flexible synthesis of 3,5-disubstituted furo [3,2-b]pyridines that relies on chemoselective couplings of newly prepared 5-chloro-3-iodofuro [3,2-b]pyridine. This methodology allowed efficient second-generation synthesis of the state-of-the-art chemical biology probe for CLK1/2/4 MU1210, and identification of the highly selective inhibitors of HIPKs MU135 and MU1787 which are presented and characterized in this study, including the X-ray crystal structure of MU135 in HIPK2. chemical biology probe.

Furo[3,2-b]pyridine: A Privileged Scaffold for Highly Selective Kinase Inhibitors and Effective Modulators of the Hedgehog Pathway.

Reported is the identification of the furo[3,2-b]pyridine core as a novel scaffold for potent and highly selective inhibitors of cdc-like kinases (CLKs) and efficient modulators of the Hedgehog signaling pathway. Initially, a diverse target compound set was prepared by synthetic sequences based on chemoselective metal-mediated couplings, including assembly of the furo[3,2-b]pyridine scaffold by copper-mediated oxidative cyclization. Optimization of the subseries containing 3,5-disubstituted furo[3,2-b]pyridines afforded potent, cell-active, and highly selective inhibitors of CLKs. Profiling of the kinase-inactive subset of 3,5,7-trisubstituted furo[3,2-b]pyridines revealed sub-micromolar modulators of the Hedgehog pathway.

A Concise Synthesis of Forskolin.

A 24-step synthesis of (±)-forskolin is presented, which delivered hundred milligram quantities of this complex diterpene in one pass. Transformations key to our approach include: a) a strategic allylic transposition, b) stepwise assembly of a sterically encumbered isoxazole ring, and c) citric acid-modified Upjohn dihydroxylation of a resilient tetrasubstituted olefin. The developed route has exciting potential for the preparation of new forskolin analogues inaccessible by semisynthesis.

Diastereoselective Flexible Synthesis of Carbocyclic C-Nucleosides.

Carbocyclic C-nucleosides are quite rare. Our route enables flexible preparation of three classes of these nucleoside analogs from common precursors-properly substituted cyclopentanones, which can be prepared racemic (in six steps) or optically pure (in ten steps) from inexpensive norbornadiene. The methodology allows flexible manipulation of individual positions around the cyclopentane ring, namely highly diastereoselective installation of carbo- and heterocyclic substituents at position 1', orthogonal functionalization of position 5', and efficient inversion of stereochemistry at position 2'. Newly prepared carbocyclic C-analog of tubercidine, profiled in MCF7 (breast cancer) and HFF1 (human foreskin fibroblasts) cell cultures, is less potent than tubercidine itself, but more selectively toxic toward the tumorigenic cells.

Biology-oriented synthesis of a withanolide-inspired compound collection reveals novel modulators of hedgehog signaling.

Biology-oriented synthesis employs the structural information encoded in complex natural products to guide the synthesis of compound collections enriched in bioactivity. The trans-hydrindane dehydro-δ-lactone motif defines the characteristic scaffold of the steroid-like withanolides, a plant-derived natural product class with a diverse pattern of bioactivity. A withanolide-inspired compound collection was synthesized by making use of three key intermediates that contain this characteristic framework derivatized with different reactive functional groups. Biological evaluation of the compound collection in cell-based assays that monitored biological signal-transduction processes revealed a novel class of Hedgehog signaling inhibitors that target the protein Smoothened.

Are time-dependent fluorescence shifts at the tunnel mouth of haloalkane dehalogenase enzymes dependent on the choice of the chromophore?

Time-dependent fluorescence shifts (TDFS) of chromophores selectively attached to proteins may give information on the dynamics of the probed protein moieties and their degree of hydration. Previously, we demonstrated that a coumarin dye selectively labeling the tunnel mouth of different haloalkane dehalogenases (HLDs) can distinguish between different widths of tunnel mouth openings. In order to generalize those findings analogous experiments were performed using a different chromophore probing the same region of these enzymes. To this end we synthesized and characterized three new fluorescent probes derived from dimethylaminonaphthalene bearing a linker almost identical to that of the coumarin dye used in our previous study. Labeling efficiencies, acrylamide quenching, fluorescence anisotropies, and TDFS for the examined fluorescent substrates confirm the picture gained from the coumarin studies: the different tunnel mouth opening, predicted by crystal structures, is reflected in the hydration and tunnel mouth dynamics of the investigated HLDs. Comparison of the TDFS reported by the coumarin dye with those obtained with the new dimethylaminonaphthalene dyes shows that the choice of chromophore may strongly influence the recorded TDFS characteristics. The intrinsic design of our labeling strategy and the variation of the linker length ensure that both dyes probe the identical enzyme region; moreover, the covalently fixed position of the chromophore does not allow for a major relocalization within the HLD structures. Our study shows, for the first time, that TDFS may strongly depend on the choice of the chromophore, even though the identical region of a protein is explored.

Covalent bonding of azoles to quaternary protoberberine alkaloids.

Adducts of the quaternary protoberberine alkaloids (QPA) berberine, palmatine, and coptisine were prepared with nucleophiles derived from pyrrole, pyrazole, imidazole, and 1,2,4-triazole. The products, 8-substituted 7,8-dihydroprotoberberines, were identified by mass spectrometry and 1D and 2D NMR spectroscopy, including (1)H--(15)N shift correlations at natural abundance. In addition, two adducts of QPA with chloroform and methanethiolate were characterized by using NMR data. Single-crystal X-ray structures of 8-pyrrolyl-7,8-dihydroberberine, 8-pyrazolyl-7,8-dihydroberberine, and 8-imidazolyl-7,8-dihydroberberine are also presented.