No abstract

The facile abstraction of bis-allylic hydrogens from polyunsaturated fatty acids (PUFAs) is the hallmark chemistry responsible for initiation and propagation of autoxidation reactions. The products of these autoxidation reactions can form cross-links to other membrane components, damage proteins and nucleic acid. We report that PUFAs deuterated at bis-allylic sites are much more resistant to autoxidation reactions, due to the isotope effect. This is shown using coenzyme Q-deficient Saccharomyces cerevisiae coq mutants with defects in biosynthesis of coenzyme Q (Q). Q functions in respiratory energy metabolism and also functions as a lipid-soluble antioxidant. Yeast coq mutants incubated in the presence of the PUFAs α-linolenic or linoleic acid exhibit 99% loss of colony formation after four hours, demonstrating a profound loss of viability. In contrast, coq mutants treated with monounsaturated oleic acid or with one of the deuterated PUFAs:11,11-D2-Linoleic or 11,11,14,14-D4-αLinolenic retain viability similar to wild-type yeast. Deuterated PUFAs also confer protection to wild-type yeast subjected to heat stress. These results indicate that isotope-reinforced PUFAs are stabilized compared to standard PUFAs, and they protect coq mutants and wild-type yeast cells against the toxic effects of lipid autoxidation products. These findings suggest new approaches to controlling ROS-inflicted cellular damage and oxidative stress.

A new multi-label deep neural network architecture is used to combine Infrared and mass spectra, trained on single compounds to predict functional groups, and experimentally validated on complex mixtures.

Figure S1: Distribution of RMSD values (Å) for all ligand poses generated by CANDOCK for docked poses in the CASF-2016 benchmark for (a) rigid-protein docking, (b) semi-flexible protein, and (c) fully-flexible protein docking.

Islet β-cell dysfunction and aggressive macrophage activity are early features in the pathogenesis of type 1 diabetes (T1D). 12/15-Lipoxygenase (12/15-LOX) is induced in β-cells and macrophages during T1D and produces proinflammatory lipids and lipid peroxides that exacerbate β-cell dysfunction and macrophage activity. Inhibition of 12/15-LOX provides a potential therapeutic approach to prevent glycemic deterioration in T1D. Two inhibitors recently identified by our groups through screening efforts, ML127 and ML351, have been shown to selectively target 12/15-LOX with high potency. Only ML351 exhibited no apparent toxicity across a range of concentrations in mouse islets, and molecular modeling has suggested reduced promiscuity of ML351 compared with ML127. In mouse islets, incubation with ML351 improved glucose-stimulated insulin secretion in the presence of proinflammatory cytokines and triggered gene expression pathways responsive to oxidative stress and cell death. Consistent with a role for 12/15-LOX in promoting oxidative stress, its chemical inhibition reduced production of reactive oxygen species in both mouse and human islets in vitro. In a streptozotocin-induced model of T1D in mice, ML351 prevented the development of diabetes, with coincident enhancement of nuclear Nrf2 in islet cells, reduced β-cell oxidative stress, and preservation of β-cell mass. In the nonobese diabetic mouse model of T1D, administration of ML351 during the prediabetic phase prevented dysglycemia, reduced β-cell oxidative stress, and increased the proportion of anti-inflammatory macrophages in insulitis. The data provide the first evidence to date that small molecules that target 12/15-LOX can prevent progression of β-cell dysfunction and glycemic deterioration in models of T1D.

Small molecule docking has proven to be invaluable for drug design and discovery. However, existing docking methods have several limitations, such as, ignoring interactions with essential components in the chemical environment of the binding pocket (e.g. cofactors, metal-ions, etc.), incomplete sampling of chemically relevant ligand conformational space, and they are unable to consistently correlate docking scores of the best binding pose with experimental binding affinities. We present CANDOCK, a novel docking algorithm that utilizes a hierarchical approach to reconstruct ligands from an atomic grid using graph theory and generalized statistical potential functions to sample chemical relevant ligand conformations. Our algorithm accounts for protein flexibility, solvent, metal ions and cofactors interactions in the binding pocket that are traditionally ignored by current methods. We evaluate the algorithm on the PDBbind and Astex proteins to show its ability to reproduce the binding mode of the ligands that is independent of the initial ligand conformation in these benchmarks. Finally, we identify the best selector and ranker potential functions, such that, the statistical score of best selected docked pose correlates with the experimental binding affinities of the ligands for any given protein target. Our results indicate that CANDOCK is a generalized flexible docking method that addresses several limitations of current docking methods by considering all interactions in the chemical environment of a binding pocket for correlating the best docked pose with biological activity.

The effective fragment potential (EFP) is a quantum mechanics (QM)-based model designed to accurately describe intermolecular interactions. Hybrid QM/EFP calculations combine quantum mechanical methods with an EFP embedding to study complex systems in which many-body effects are relevant. As in EFP-only calculations, non-bonded interactions between the QM region and EFP fragments are computed as a sum of electrostatic, polarization, dispersion, and exchange-repulsion energies. The exchange-repulsion term is a computational bottleneck of the EFP calculations. Here, we present a general procedure for computing the QM/EFP exchange-repulsion interactions based on one-electron contributions to the QM Hamiltonian, by using Gaussian functions to represent localized molecular orbitals of the effective fragments. The accuracy of the exchange-repulsion and total QM/EFP interaction energies is evaluated on a diverse set of dimers, including complexes from the S22 dataset of non-covalent interactions. In most cases, the QM/EFP energies are at least as accurate as corresponding EFP energies. A simple and computationally efficient form of the introduced QM/EFP exchange-repulsion term will facilitate further developments and applications of QM/EFP methods.

Acute myeloid leukemia (AML) is an aggressive malignancy with only a handful of therapeutic options. About 30% of AML patients harbor mutated FLT3 kinase, and thus, this cancer-driver has become a hotly pursued AML target. Herein we report a new class of FLT3 inhibitors, which potently inhibit the proliferation of acute myeloid leukemia (AML) cells at nanomolar concentrations.