Discovery of CDC42 Inhibitors with a Favorable Pharmacokinetic Profile and Anticancer In Vivo Efficacy.

We previously reported trisubstituted pyrimidine lead compounds, namely, ARN22089 and ARN25062, which block the interaction between CDC42 with its specific downstream effector, a PAK protein. This interaction is crucial for the progression of multiple tumor types. Such inhibitors showed anticancer efficacy in vivo. Here, we describe a second class of CDC42 inhibitors with favorable drug-like properties. Out of the 25 compounds here reported, compound 15 (ARN25499) stands out as the best lead compound with an improved pharmacokinetic profile, increased bioavailability, and efficacy in an in vivo PDX tumor mouse model. Our results indicate that these CDC42 inhibitors represent a promising chemical class toward the discovery of anticancer drugs, with ARN25499 as an additional lead candidate for preclinical development.

Development of an asymmetric formal synthesis of (-)-quinagolide via enzymatic resolution and stereoselective iminium ion reduction.

The stereoselective reduction of a diastereoisomeric mixture of benzo[g]octahydroquinolinium ion was examined in detail. A diastereoselective borohydride reduction in combination with an efficient deacylative enzymatic resolution of its ß-aminoester precursor are the key steps for a stereoselective installation of the three chiral centres present in the (3S,4aS,10aR)-eutomer of the medicinal drug quinagolide. The obtained data paves the way for an easy and practical attainment of chiral 3-substituted octahydrobenzo[g]quinolines that are privileged structures in medicinal chemistry.

Design, synthesis, docking, and biochemical characterization of non-nucleoside SARS-CoV-2 RdRp inhibitors.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide pandemic. The identification of effective antiviral drugs remains an urgent medical need. In this context, here we report 17 new 1,4-benzopyrone derivatives, which have been designed, synthesized, and characterized for their ability to block the RNA-dependent RNA polymerase (RdRp) enzyme, a promising target for antiviral drug discovery. This compound series represents a good starting point for developing non-nucleoside inhibitors of RdRp. Compounds 4, 5, and 8 were the most promising drug-like candidates with good potency in inhibiting RdRp, improved in vitro pharmacokinetics compared to the initial hits, and no cytotoxicity effects on normal cell (HEK-293). Compound 8 (ARN25592) stands out as the most promising inhibitor. Our results indicate that this new chemical class of 1,4-benzopyrone derivatives deserves further exploration towards novel and potent antiviral drugs for the treatment of SARS-CoV-2 and potentially other viruses.

Copper-Catalyzed Ring-Opening Reactions of Alkyl Aziridines with B2pin2: Experimental and Computational Studies.

The possibility to form new C-B bonds with aziridines using diboron derivatives continues to be a particularly challenging field in view of the direct preparation of functionalized ß-aminoboronates, which are important compounds in drug discovery, being a bioisostere of ß-aminoacids. We now report experimental and computational data that allows the individuation of the structural requisites and of reaction conditions necessary to open alkyl aziridines using bis(pinacolate)diboron (B2pin2) in a regioselective nucleophilic addition reaction under copper catalysis.

A Machine Learning Approach to Investigate the Uncertainty of Tissue-Level Injury Metrics for Cerebral Contusion.

Controlled cortical impact (CCI) on porcine brain is often utilized to investigate the pathophysiology and functional outcome of focal traumatic brain injury (TBI), such as cerebral contusion (CC). Using a finite element (FE) model of the porcine brain, the localized brain strain and strain rate resulting from CCI can be computed and compared to the experimentally assessed cortical lesion. This way, tissue-level injury metrics and corresponding thresholds specific for CC can be established. However, the variability and uncertainty associated with the CCI experimental parameters contribute to the uncertainty of the provoked cortical lesion and, in turn, of the predicted injury metrics. Uncertainty quantification via probabilistic methods (Monte Carlo simulation, MCS) requires a large number of FE simulations, which results in a time-consuming process. Following the recent success of machine learning (ML) in TBI biomechanical modeling, we developed an artificial neural network as surrogate of the FE porcine brain model to predict the brain strain and the strain rate in a computationally efficient way. We assessed the effect of several experimental and modeling parameters on four FE-derived CC injury metrics (maximum principal strain, maximum principal strain rate, product of maximum principal strain and strain rate, and maximum shear strain). Next, we compared the in silico brain mechanical response with cortical damage data from in vivo CCI experiments on pig brains to evaluate the predictive performance of the CC injury metrics. Our ML surrogate was capable of rapidly predicting the outcome of the FE porcine brain undergoing CCI. The now computationally efficient MCS showed that depth and velocity of indentation were the most influential parameters for the strain and the strain rate-based injury metrics, respectively. The sensitivity analysis and comparison with the cortical damage experimental data indicate a better performance of maximum principal strain and maximum shear strain as tissue-level injury metrics for CC. These results provide guidelines to optimize the design of CCI tests and bring new insights to the understanding of the mechanical response of brain tissue to focal traumatic brain injury. Our findings also highlight the potential of using ML for computationally efficient TBI biomechanics investigations.

An Overview of the Effectiveness of Bicycle Helmet Designs in Impact Testing.

Cycling accidents are the leading cause of sports-related head injuries in the US. Conventional bicycle helmets typically consist of polycarbonate shell over Expanded Polystyrene (EPS) foam and are tested with drop tests to evaluate a helmet's ability to reduce head kinematics. Within the last decade, novel helmet technologies have been proposed to mitigate brain injuries during bicycle accidents, which necessitates the evaluation of their effectiveness in impact testing as compared to conventional helmets. In this paper, we reviewed the literature to collect and analyze the kinematic data of drop test experiments carried out on helmets with different technologies. In order to provide a fair comparison across different types of tests, we clustered the datasets with respect to their normal impact velocities, impact angular momentum, and the type of neck apparatus. When we analyzed the data based on impact velocity and angular momentum clusters, we found that the bicycle helmets that used rotation damping based technology, namely MIPS, had significantly lower peak rotational acceleration (PRA) and Generalized Acceleration Model for Brain Injury Threshold (GAMBIT) as compared to the conventional EPS liner helmets (p < 0.01). SPIN helmets had a superior performance in PRA compared to conventional helmets (p < 0.05) in the impact angular momentum clustered group, but not in the impact-velocity clustered comparisons. We also analyzed other recently developed helmets that primarily use collapsible structures in their liners, such as WaveCel and Koroyd. In both of the impact velocity and angular momentum groups, helmets based on the WaveCel technology had significantly lower peak linear acceleration (PLA), PRA, and GAMBIT at low impact velocities as compared to the conventional helmets, respectively (p < 0.05). The protective gear with the airbag technology, namely Hövding, also performed significantly better compared to the conventional helmets in the analyzed kinematic-based injury metrics (p < 0.001), possibly due to its advantage in helmet size and stiffness. We also observed that the differences in the kinematic datasets strongly depend on the type of neck apparatus. Our findings highlight the importance and benefits of developing new technologies and impact testing standards for bicycle helmet designs for better prevention of traumatic brain injury (TBI).

Investigation of tissue level tolerance for cerebral contusion in a controlled cortical impact porcine model.

OBJECTIVE: Cerebral contusions (CC) represent a frequent lesion in traumatic brain injury, with potential morbidity from mass effect and tissue loss. Better understanding of the mechanical etiology will help to improve head protection. The goal of this study is to investigate the threshold for mechanical impact parameters to induce CC in an in vivo porcine controlled cortical impact model. METHODS: Thirty-four adult male pigs underwent craniotomy and controlled cortical impact with a hemispherical tip on intact dura under general anesthesia. Peak impact depth varied between 1.1 and 12.6 mm, and impact velocity between 0.4 and 2.2 m/s while the dwell time was kept at 200 ms. Two days following impact, the animals underwent magnetic resonance (MR) imaging of the brain, and were subsequently sacrificed for brain extraction. CC damage was investigated by magnetic resonance imaging and histology. RESULTS: All animals recovered from the impact without overt neurological deficit. Provoked injuries were histologically confirmed to be CC. Decreasing probability of cortical damage and white matter edema volume was observed with decreasing impact depth and velocity. No CC could be demonstrated below a product of impact depth and velocity of 0.8 mm*m/s, whereas the probability for CC was one third below 15 mm*m/s. The threshold for CC development as estimated from the current series of experiments, was situated at an impact depth of 2.0 mm and impact velocity of 0.4 m/s. CONCLUSION: Mechanical thresholds for CC development could be explored in the current porcine controlled cortical impact model. Findings will be used to further refine a cerebral contusion porcine model with volumetric histology data in light of future finite element cerebral contusion validation studies.

Experimental and Computational Studies Unraveling the Peculiarity of Enolizable Oxoesters in the Organocatalyzed Mannich-Type Addition to Cyclic N-Acyl Iminium Ions.

γ- and δ-Oxoesters are easily available starting materials that have been sparingly used in some organocatalyzed reactions proceeding with a high enantioselectivity. In our experimentation we found that the use of these compounds as the enolizable (nucleophilic) component in organocatalyzed Mannich-type reactions using in situ-generated cyclic N-acyl iminium ions gave low diastereoselectivity and low to moderate values of enantioselectivity. This significant drop of facial selectivity with respect to simple aliphatic aldehydes has been rationalized by means of density functional theory (DFT) calculations.

Nitroso Diels-Alder Cycloadducts Derived From N-Acyl-1,2-dihydropyridines as a New Platform to Molecular Diversity.

This review focuses upon the use of nitroso Diels-Alder reactions as a structural complexity generating reaction that has been so far a quite scarcely treated topic, despite its potential. In particular, the use of N-acyl-1,2-dihydropyridines as a non-symmetrical diene component in nitroso Diels-Alder reactions encompasses an initial diversification of pathways giving rise to different cycloadducts (direct and inverse). Selective elaborations of these cycloadducts, basically using a reagent-based approach, deliver a discrete number of structurally diverse compounds, including some original heterobicyclic scaffolds and functionalized heterocycles. This forward synthetic planning allowed the individuation of a new biologically active compound based on a novel oxadiaza-bicyclic-[3.3.1]-nonene scaffold which is still under preclinical evaluation.

Direct enantioselective vinylogous Mannich-type reactions of acyclic enals: New experimental insights into the E/Z-dilemma.

The direct heterofunctionalization of acyclic α,ß-unsaturated aldehydes with N-acylquinolinium ions contemplating the formation of two stereocentres is studied using dienamine catalysis. This work gives some new experimental insights on the remote stereocontrol in dienamine catalysis using unbiased aliphatic systems and large electrophiles, pointing to a (Z)-preference of the reactive configuration of the second double bond.

Organocatalytic alkylation of carbohydrate-containing aldehydes with dihydroquinoline N,O-acetals: Absolute configuration of 1,2-dihydroquinolines.

The direct catalytic α-amidoalkylation of dihydroquinolines with aldehydes bearing oxygen functionalities at different positions in a Mannich-type reaction has been studied. ß-Alkoxy-aldehyde 1d gave high enantioselectivity, albeit with an inherently poor diastereoselectivity, while the use of α-alkoxy aldehydes 1c was detrimental also to enantioselectivity. Mannich-type reactions have been studied for the first time using new chiral carbohydrate-derived aldehydes 1a,b showing a reactivity markedly influenced by the presence of water. The chiral glycidic backbone showed a slight but significant influence on the overall stereochemical outcome only when present in α-position of the aldehyde. The absolute stereochemistry of the products was studied by electronic circular dichroism (ECD) spectra and compared with theoretical calculations. ECD analysis easily provides the absolute configuration of 1,2-dihydroquinoline derivatives such as quinoline-1(2H)-carboxylates.

Regio- and Stereodivergent Allylic Reductions of Bicyclic Piperidine Enecarbamate Derivatives.

The particular nature of tetrahydropyrido[4,3- e]-1,4,2-dioxazines of type 1 allows the regio- and stereoselective obtainment of substituted N-carbamoyl tetrahydropyridines by common reducing agents. A completely novel, biologically active, bicyclic 1,3-diaza-4-oxa-[3.3.1]-nonene scaffold can be generated by the use of lithium triethylborohydride through unprecedented cascade syn-SN2' reduction/carbamate reduction/cyclization reactions. The remarkable regioselectivity switches in the allylic reduction process have been rationalized with the aid of computational studies.