Discovery of Potent Benzothiazole Inhibitors of Oxidoreductase NQO2, a Target for Inflammation and Cancer.

Inhibitors of NQO2 (NRH: quinone oxidoreductase) have potential application in several areas of medicine and pharmacology, including cancer, neurodegeneration (PD and AD), stroke, and diabetes. Here, resveratrol, a known inhibitor of NQO2, was used as the lead by replacing the double bond in resveratrol with a benzothiazole scaffold. Fifty-five benzothiazoles were designed as NQO2 inhibitors and synthesized, comprising five benzothiazole series with 3,5-dimethoxy, 2,4-dimethoxy, 2,5-dimethoxy, 3,4-dimethoxy, and 3,4,5-trimethoxy substituents, the key synthetic step being a Jacobson cyclisation with the appropriate thiobenzamide.

Virtual screening-led design of inhibitor scaffolds for the NLRP3 inflammasome.

The NLRP3 inflammasome is a key target for drug discovery due to its implication in a range of inflammation-related diseases. In this work, we identify new inhibitors of the NLRP3 inflammasome via a hierarchical virtual screening strategy using molecular similarity, docking and MD simulation. The most potent inhibitors identified from a subsequent biological assay (IC of 1 - 4 μM) feature a sulfonamide group, a motif known to favour NLRP3 inhibition, in conjunction with an indole, benzofuran or tricyclic 6,7-dihydro-5H-indeno[5,6-b]furan ring, yielding novel scaffolds.

Stable and accurate atomistic simulations of flexible molecules using conformationally generalisable machine learned potentials.

Computational simulation methods based on machine learned potentials (MLPs) promise to revolutionise shape prediction of flexible molecules in solution, but their widespread adoption has been limited by the way in which training data is generated. Here, we present an approach which allows the key conformational degrees of freedom to be properly represented in reference molecular datasets. MLPs trained on these datasets using a global descriptor scheme are generalisable in conformational space, providing quantum chemical accuracy for all conformers.

Structural determination of oleanane-28,13β-olide and taraxerane-28,14β-olide fluoro-lactonization products from the reaction of oleanolic acid with Selectfluor.

The X-ray crystal structure data of 12-α-fluoro-3β-hy-droxy-olean-28,13β-olide methanol hemisolvate, 2CHFO·CHOH, (), and 12-α-fluoro-3β-hy-droxy-taraxer-28,14β-olide methanol hemisolvate, 2CHFO·CHOH, (), are described. The fluoro-lactonization of oleanolic acid using Selectfluor yielded a mixture of the six-membered δ-lactone () and the unusual seven-membered γ-lactone () following a 1,2-shift of methyl C-27 from C-14 to C-13.

Chronic Cellulitis in the Unhoused: Case Study and Treatment Considerations.

This report seeks to discuss sequelae of chronic cellulitis that is commonly treated in the ambulatory setting, as exacerbated by the conditions of living outside. Further we hope to identify etiologic factors that contribute to complication development. Additionally, this article will touch on unique treatment plan considerations for unhoused patients with the intention to educate providers and reduce mortality and morbidity relating to pedal skin and soft tissue infections in this population.

Boosting the Accuracy and Chemical Space Coverage of the Detection of Small Colloidal Aggregating Molecules Using the BAD Molecule Filter.

The ability to conduct effective high throughput screening (HTS) campaigns in drug discovery is often hampered by the detection of false positives in these assays due to small colloidally aggregating molecules (SCAMs). SCAMs can produce artifactual hits in HTS by nonspecific inhibition of the protein target. In this work, we present a new computational prediction tool for detecting SCAMs based on their 2D chemical structure.

Molecular dynamics simulations as a guide for modulating small molecule aggregation.

Small colloidally aggregating molecules (SCAMs) can be problematic for biological assays in drug discovery campaigns. However, the self-associating properties of SCAMs have potential applications in drug delivery and analytical biochemistry. Consequently, the ability to predict the aggregation propensity of a small organic molecule is of considerable interest.

Brazilin is a natural product inhibitor of the NLRP3 inflammasome.

Excessive or aberrant NLRP3 inflammasome activation has been implicated in the progression and initiation of many inflammatory conditions; however, currently no NLRP3 inflammasome inhibitors have been approved for therapeutic use in the clinic. Here we have identified that the natural product brazilin effectively inhibits both priming and activation of the NLRP3 inflammasome in cultured murine macrophages, a human iPSC microglial cell line and in a mouse model of acute peritoneal inflammation. Through computational modeling, we predict that brazilin can adopt a favorable binding pose within a site of the NLRP3 protein which is essential for its conformational activation.

A neural network potential based on pairwise resolved atomic forces and energies.

Molecular simulations have become a key tool in molecular and materials design. Machine learning (ML)-based potential energy functions offer the prospect of simulating complex molecular systems efficiently at quantum chemical accuracy. In previous work, we have introduced the ML-based PairF-Net approach to neural network potentials, that adopts a pairwise interatomic scheme to predicting forces within a molecular system.

A Selective Review and Virtual Screening Analysis of Natural Product Inhibitors of the NLRP3 Inflammasome.

The NLRP3 inflammasome is currently an exciting target for drug discovery due to its role in various inflammatory diseases; however, to date, no NLRP3 inhibitors have reached the clinic. Several studies have used natural products as hit compounds to facilitate the design of novel selective NLRP3 inhibitors. Here, we review selected natural products reported in the literature as NLRP3 inhibitors, with a particular focus on those targeting gout.

Cellulose Iβ microfibril interaction with pristine graphene in water: Effects of amphiphilicity by molecular simulation.

Graphene-cellulose interactions have considerable potential in the development of new materials. In previous computational work (Biomacromolecules2016, 16, 1771), we predicted that the model 100 hydrophobic surface of cellulose interacted favourably with pristine graphene in aqueous solution molecular dynamics simulations; conversely, a model of the hydrophilic 010 surface of cellulose exhibited progressive rearrangement to present a more hydrophobic face with the graphene, with weakened hydrogen bonds between cellulose chains and partial permeation of water. Here, we extend this work by simulating the interaction in aqueous solution of the amphiphilic 110 surface of a cellulose Iβ microfibril model, comprising 36 chains of 40 glucosyl residues, with an infinite sheet of pristine graphene.

Probing the effect of NEK7 and cofactor interactions on dynamics of NLRP3 monomer using molecular simulation.

The NLRP3 inflammasome is a cytoplasmic complex that regulates the activation of inflammatory cytokines and, given its implication in a range of diseases, is an important therapeutic target. The cofactor ATP and the centrosomal kinase NEK7 are important for NLRP3 activation. Here we have constructed and simulated computational models of full-length monomeric NLRP3 to shed light on the importance of NEK7 and cofactor interactions for its conformation and dynamics in aqueous solution.

Modeling pyranose ring pucker in carbohydrates using machine learning and semi-empirical quantum chemical methods.

Pyranose ring pucker is a key coordinate governing the structure, interactions and reactivity of carbohydrates. We assess the ability of the machine learning potentials, ANI-1ccx and ANI-2x, and the GFN2-xTB semiempirical quantum chemical method, to model ring pucker conformers of five monosaccharides and oxane in the gas phase. Relative to coupled-cluster quantum mechanical calculations, we find that ANI-1ccx most accurately reproduces the ring pucker energy landscape for these molecules, with a correlation coefficient r of 0.

Getting the word out: Methods of learning about research and motivations for participation in a study focusing on a reproductive-aged Latina/x population.

Background: Although one of the fastest-growing populations in the USA, Latinx individuals remain underrepresented in research. In this study, we aimed to identify how Latina/Latinx participants of the Environment, Leiomyomas, Latinas, and Adiposity Study (ELLAS) learned about the research study and what motivated them to participate.

Materials And Methods: Using a standardized survey tool, bilingual staff interviewed participants and asked them, 1) how they heard about ELLAS and 2) to identify and rank their top three reasons for participating in ELLAS.

Structure-based assessment and druggability classification of protein-protein interaction sites.

The featureless interface formed by protein-protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap.

SAR of Novel 3-Arylisoquinolinones: -Substitution on the Aryl Ring Dramatically Enhances Antiproliferative Activity through Binding to Microtubules.

A set of -substituted 3-arylisoquinolinones have been identified that show substantial cytotoxicity in breast, liver, lung and colon cancer cell lines; these are up to 700-fold more active than the corresponding analogues. These compounds were initially proposed as inhibitors of -ribosyl dihydronicotinamide (NRH): quinone oxidoreductase 2 (NQO2) but were found to be inactive against the enzyme. Instead, COMPARE analysis suggested that 6-fluoro-3-(-fluorophenyl)isoquinolin-1(2)-one () could mimic colchicine and interact with microtubules, a recognized target for cancer therapy.

The Phase II MutHER Study of Neratinib Alone and in Combination with Fulvestrant in HER2-Mutated, Non-amplified Metastatic Breast Cancer.

Purpose: HER2 mutations (HER2mut) induce endocrine resistance in estrogen receptor-positive (ER+) breast cancer.

Patients And Methods: In this single-arm multi-cohort phase II trial, we evaluated the efficacy of neratinib plus fulvestrant in patients with ER+/HER2mut, HER2 non-amplified metastatic breast cancer (MBC) in the fulvestrant-treated (n = 24) or fulvestrant-naïve cohort (n = 11). Patients with ER-negative (ER-)/HER2mut MBC received neratinib monotherapy in an exploratory ER- cohort (n = 5).

Analysis of the pan-Asian subgroup of patients in the NALA Trial: a randomized phase III NALA Trial comparing neratinib+capecitabine (N+C) vs lapatinib+capecitabine (L+C) in patients with HER2+metastatic breast cancer (mBC) previously treated with two or more HER2-directed regimens.

Purpose: Neratinib, an irreversible pan-HER tyrosine kinase inhibitor, has demonstrated systemic efficacy and intracranial activity in various stages of HER2+breast cancer. NALA was a phase III randomized trial that assessed the efficacy and safety of neratinib+capecitabine (N+C) against lapatinib+capecitabine (L+C) in HER2+ metastatic breast cancer (mBC) patients who had received ≥ 2 HER2-directed regimens. Descriptive analysis results of the Asian subgroup in the NALA study are reported herein.

Biomarker Analysis of the Phase III NALA Study of Neratinib + Capecitabine versus Lapatinib + Capecitabine in Patients with Previously Treated Metastatic Breast Cancer.

Purpose: Neratinib plus capecitabine (N+C) demonstrated significant progression-free survival (PFS) benefit in NALA (NCT01808573), a randomized phase III trial comparing N+C with lapatinib + capecitabine (L+C) in 621 patients with HER2-positive (HER2) metastatic breast cancer (MBC) who had received ≥2 prior HER2-directed regimens in the metastatic setting. We evaluated correlations between exploratory biomarkers and PFS.

Patients And Methods: Somatic mutations were evaluated by next-generation sequencing on primary or metastatic samples.

A pilot randomized controlled trial of a fruit and vegetable prescription program at a federally qualified health center in low income uncontrolled diabetics.

Eating a healthy diet is important for managing diabetes. Although there are high rates of diabetes in low-income urban areas, these patients often have limited access to fruits and vegetables. The 15-week Fresh Prescription (Fresh Rx) program was designed to improve access and consumption of fruits and vegetables among low-income patients with diabetes in Detroit, MI.

Immigration law enforcement, social support, and health for Latino immigrant families in Southeastern Michigan.

Rationale: Social support is a key determinant of physical and mental health outcomes. Implementation of restrictive immigration policies in the U.S.

Efficacy of Neratinib Plus Capecitabine in the Subgroup of Patients with Central Nervous System Involvement from the NALA Trial.

Background: Neratinib has efficacy in central nervous system (CNS) metastases from HER2-positive metastatic breast cancer (MBC). We report outcomes among patients with CNS metastases at baseline from the phase III NALA trial of neratinib plus capecitabine (N + C) versus lapatinib plus capecitabine (L + C).

Materials And Methods: NALA was a randomized, active-controlled trial in patients who received two or more previous HER2-directed regimens for HER2-positive MBC.