Mchughreyes5194

Accurate quantification of protein-ligand interactions remains a key challenge to structure-based drug design. However, traditional machine learning (ML)-based methods based on handcrafted descriptors, one-dimensional protein sequences, and/or two-dimensional graph representations limit their capability to learn the generalized molecular interactions in 3D space. Here, we proposed a novel deep graph representation learning framework named InteractionGraphNet (IGN) to learn the protein-ligand interactions from the 3D structures of protein-ligand complexes. In IGN, two independent graph convolution modules were stacked to sequentially learn the intramolecular and intermolecular interactions, and the learned intermolecular interactions can be efficiently used for subsequent tasks. Extensive binding affinity prediction, large-scale structure-based virtual screening, and pose prediction experiments demonstrated that IGN achieved better or competitive performance against other state-of-the-art ML-based baselines and docking programs. More importantly, such state-of-the-art performance was proven from the successful learning of the key features in protein-ligand interactions instead of just memorizing certain biased patterns from data.CRISPR/Cas has recently emerged as the most reliable system for genome engineering in various species. However, concerns about risks associated with the CRISPR/Cas technology are increasing on potential unintended DNA changes that might accidentally arise from CRISPR gene editing. Developing a system that can detect and report the presence of active CRISPR/Cas tools in biological systems is therefore very necessary. Here, we developed four real-time detection systems that can spontaneously indicate the presence of active CRISPR-Cas tools for genome editing and gene regulation including CRISPR/Cas9 nuclease, base editing, prime editing, and CRISPRa in plants. Using the fluorescence-based molecular biosensors, we demonstrated that the activities of CRISPR/Cas9 nuclease, base editing, prime editing, and CRISPRa can be effectively detected in transient expression via protoplast transformation and leaf infiltration (in Arabidopsis, poplar, and tobacco) and stable transformation in Arabidopsis.Coherent phase boundaries are widely expected as segregation-free boundaries due to their low interfacial energies and lack of trapping sites for impurities. Here, we report an equilibrium segregation of W atoms at fully coherent terraces of a Fe3O4 (111)/Fe2O3 (0001) phase boundary that was never expected previously. Through comparison of pristine and W-doped Fe3O4/Fe2O3 phase boundaries, it is revealed that the spin polarization of O atoms at the interface plays an important role in the periodic segregation of W atoms. Unusual spin-polarized O atoms with large magnetic moments are periodically arranged in the interfacial O plane of the pristine phase boundary. After doping of W at this boundary, W atoms will selectively substitute the Fe atoms of Fe2O3 that directly bond with three spin-polarized O atoms, thereby resulting in the complete neutralization of the magnetic moments of the spin-polarized O atoms. These findings reveal that coherent phase boundaries are able to trap impurities and local spin polarization is one of the driving forces for dopant segregation, suggesting that elemental doping is an efficient way for tailoring the physical properties of boundaries in magnetic materials and devices.Positive outcomes in biochemical and biological assays of food compounds may appear due to the well-described capacity of some compounds to form colloidal aggregates that adsorb proteins, resulting in their denaturation and loss of function. This phenomenon can lead to wrongly ascribing mechanisms of biological action for these compounds (false positives) as the effect is nonspecific and promiscuous. Similar false positives can show up due to chemical (photo)reactivity, redox cycling, metal chelation, interferences with the assay technology, membrane disruption, etc., which are more frequently observed when the tested molecule has some definite interfering substructures. Although discarding false positives can be achieved experimentally, it would be very useful to have in advance a prognostic value for possible aggregation and/or interference based only in the chemical structure of the compound tested in order to be aware of possible issues, help in prioritization of compounds to test, design of appropriate assays, etc. Previously, we applied cheminformatic tools derived from the drug discovery field to identify putative aggregators and interfering substructures in a database of food compounds, the FooDB, comprising 26,457 molecules at that time. Here, we provide an updated account of that analysis based on a current, much-expanded version of the FooDB, comprising a total of 70,855 compounds. In addition, we also apply a novel machine learning model (SCAM Detective) to predict aggregators with 46-53% increased accuracies over previous models. In this way, we expect to provide the researchers in the mode of action of food compounds with a much improved, robust, and widened set of putative aggregators and interfering substructures of food compounds.Four porphyrins equipped with imidazolium rings on the para positions of their meso aryl groups were prepared and used as tetrakis(N-heterocyclic carbene) (NHC) precursors for the synthesis of porphyrin cages assembled from eight NHC-M bonds (M = Ag+ or Au+). The conformation of the obtained porphyrin cages in solution and their encapsulation properties strongly depend on the structure of the spacer -(CH2)n- (n = 0 or 1) between meso aryl groups and peripheral NHC ligands. In the absence of methylene groups (n = 0), porphyrin cages are rather rigid and the short porphyrin-porphyrin distance prevents the encapsulation of guest molecules like 1,4-diazabicyclo[2.2.2]octane (DABCO). By contrast, the presence of methylene functions (n = 1) between meso aryl groups and peripheral NHCs offers additional flexibility to the system, allowing the inner space between the two porphyrins to expand enough to encapsulate guest molecules like water molecules or DABCO. The peripheral NHC-wingtip groups also play a significant role in the encapsulation properties of the porphyrin cages.Black tea is one of the most popular beverages in the world, and numerous epidemiological studies have shown that drinking black tea is good for health. As a natural tea pigment formed during the fermentation of black tea, the content of theaflavins accounts for only 2-6% of the dry weight of black tea, but they have a great impact on the color and taste of black tea soup. Recently, a large number of studies have shown that theaflavins have a significant anticancer effect. In this Perspective, we first state the physical and chemical properties, separation and purification methods, and biological formation pathways of theaflavins and analyze their safety and oral bioavailability and the structure-activity relationship of their antioxidant and anticancer activities; then, we describe in detail their anticancer effect in vitro and in vivo and highlight their various molecular targets involved in cancer inhibition. The anticancer molecular targets of theaflavins are mainly cell-cycle regulatory proteins, apoptosis-related proteins, cell-migration-related proteins, and growth transcription factors. Finally, the possibility of developing new health-care food based on theaflavins is discussed. This Perspective is expected to provide a theoretical basis for the anticancer application of theaflavins in the future.The chain shuttling ring-opening copolymerization of l-lactide with ε-caprolactone has been achieved using two aluminum catalysts presenting different selectivities and benzyl alcohol as chain transfer agent. A newly synthesized aminobisphenolate supported aluminum complex affords the synthesis of lactone rich poly(l-lactide-co-lactone) statistical copolymeric blocks, while Al(OiPr)3 produces semicrystalline poly(l-lactide) rich blocks. Transalkoxylation is shown to operate efficiently. The crystalline ratios and glass transition temperatures of these new classes of polylactide based block copolymers can be tuned by adjusting the catalysts and the comonomers ratio.The agro-industry produces numerous byproducts that are currently underused, and its waste contributes to environmental pollution. These byproducts represent an important and economical source of bioactive ingredients, which can promote the sustainable development of high-value-added functional foods. In this context, micro- and nanoencapsulation systems allow for the incorporation and stabilization of the bioactive agents in foods. This perspective will review recent advances in the use of agro-industrial byproducts as a source of bioactive agents. In addition, the latest advances in micro- and nanoencapsulation to improve the stability, solubility, and bioaccessibility of bioactive agents as functional food ingredients are exposed.Tankyrase 1 and 2 (TNKS1/2) catalyze post-translational modification by poly-ADP-ribosylation of a plethora of target proteins. In this function, TNKS1/2 also impact the WNT/β-catenin and Hippo signaling pathways that are involved in numerous human disease conditions including cancer. Targeting TNKS1/2 with small-molecule inhibitors shows promising potential to modulate the involved pathways, thereby potentiating disease intervention. Based on our 1,2,4-triazole-based lead compound 1 (OM-1700), further structure-activity relationship analyses of East-, South- and West-single-point alterations and hybrids identified compound 24 (OM-153). Compound 24 showed picomolar IC50 inhibition in a cellular (HEK293) WNT/β-catenin signaling reporter assay, no off-target liabilities, overall favorable absorption, distribution, metabolism, and excretion (ADME) properties, and an improved pharmacokinetic profile in mice. Moreover, treatment with compound 24 induced dose-dependent biomarker engagement and reduced cell growth in the colon cancer cell line COLO 320DM.Water capture mechanisms of zeolitic imidazolate framework ZIF-90 are revealed by differentiating the water clustering and the center pore filling step, using vibrational sum-frequency generation spectroscopy (VSFG) at a one-micron spatial resolution and state-of-the-art molecular dynamics (MD) simulations. Through spectral line shape comparison between VSFG and IR spectra, the relative humidity dependence of VSFG intensity, and MD simulations, based on MB-pol, we found water clustering and center pore filling happen nearly simultaneously within each pore, with water filling the other pores sequentially. The integration of nonlinear optics with MD simulations provides critical mechanistic insights into the pore filling mechanism and suggests that the relative strength of the hydrogen bonds governs the water uptake mechanisms. This molecular-level detailed mechanism can inform the rational optimization of metal-organic frameworks for water harvesting.The rapid and unexpected spread of SARS-CoV-2 worldwide has caused unprecedented disruption to daily life and has brought forward critical challenges for public health. The disease was the largest cause of death in the United States in early 2021. Likewise, the COVID-19 pandemic has highlighted the need for rapid and accurate diagnoses at scales larger than ever before. To improve the availability of current gold standard diagnostic testing methods, the development of point-of-care devices that can maintain gold standard sensitivity while reducing the cost and providing portability is much needed. In this work, we combine the amplification capabilities of reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) techniques with high-sensitivity end-point detection of crumpled graphene field-effect transistors (cgFETs) to develop a portable detection cell. This electrical detection method takes advantage of the ability of graphene to adsorb single-stranded DNA due to noncovalent π-π bonds but not double-stranded DNA.