PURPOSE:Dysregulations of key signaling pathways in metabolic syndrome are multifactorial, eventually leading to cardiovascular events. Hyperglycemia in conjunction with dyslipidemia induces insulin resistance and provokes release of proinflammatory cytokines resulting in chronic inflammation, accelerated lipid peroxidation with further development of atherosclerotic alterations and diabetes. We have proposed a novel combinatorial approach using FDA approved compounds targeting IL-17a and DPP4 to ameliorate a significant portion of the clustered clinical risks in patients with metabolic syndrome. In our current research we have modeled the outcomes of metabolic syndrome treatment using two distinct drug classes.METHODS:Targets were chosen based on the clustered clinical risks in metabolic syndrome: dyslipidemia, insulin resistance, impaired glucose control, and chronic inflammation. Drug development platform, BIOiSIM™, was used to narrow down two different drug classes with distinct modes of action and modalities. Pharmacokinetic and pharmacodynamic profiles of the most promising drugs were modeling showing predicted outcomes of combinatorial therapeutic interventions.RESULTS:Preliminary studies demonstrated that the most promising drugs belong to DPP-4 inhibitors and IL-17A inhibitors. Evogliptin was chosen to be a candidate for regulating glucose control with long term collateral benefit of weight loss and improved lipid profiles. Secukinumab, an IL-17A sequestering agent used in treating psoriasis, was selected as a repurposed candidate to address the sequential inflammatory disorders that follow the first metabolic insult.CONCLUSIONS:Our analysis suggests this novel combinatorial therapeutic approach inducing DPP4 and Il-17a suppression has a high likelihood of ameliorating a significant portion of the clustered clinical risk in metabolic syndrome.

We present the development of the BIOiSIM™ pKa model for predicting aqueous molecular ionization. Assessment and optimization of drug pKa occurs early in drug discovery; thus, models for high-throughput pKa prediction must balance computational cost, scalability, accuracy, and applicability to diverse chemical structures. Key to our pKa prediction model is a set of low computational cost, quantum mechanical charge descriptors that incorporate not only ionizable group charges, but the additional atoms and bonds likely to modulate pKa. The finalized machine learning models produced good accuracy on the test holdout set (R2 = 0.9, mean absolute error = 0.6-0.7, root mean square error = 1.0) and show good generalizability predicting the most acidic and basic ionization centers of the SAMPL6 external benchmark validation set (mean absolute error = 0.8, root mean square error = 1.0). Performance of the model is comparable to commercial pKa predictors but is trained on less data and exhibits higher scalability needed for pharmacokinetic modeling.

Dysregulations of key signaling pathways leading to metabolic syndrome (MetS) are complex eventually leading to cardiovascular events and type 2 diabetes. Dyslipidemia induces progression of insulin resistance and provokes release of proinflammatory cytokines resulting in chronic inflammation, acceleration of lipid peroxidation with further development of atherosclerotic alterations and diabetes. We have proposed a novel combinatorial approach using FDA approved compounds targeting IL-17a and DPP4 to ameliorate a significant portion of the clustered clinical risks in patients with MetS. As MetS is considered a multifactorial disorder, the treatment measures cannot be focused on the specific pathway because other metabolic changes keep the pathological processes in progression. In our present research we have modeled an outcomes of metabolic syndrome treatment using two distinct drug classes. Targets were chosen based on the clustered clinical risks in MetS; dyslipidemia, insulin resistance, impaired glucose control, and chronic inflammation. The AI/ML platform, BIOiSIM, was used in narrowing down two different drug classes with distinct mode of action and modalities. Preliminary studies demonstrated that the most promising drugs belong to DPP-4 inhibitors and IL-17A inhibitors. Alogliptin was chosen to be a candidate for regulating glucose control with long term collateral benefit of weight loss and improved lipid profiles. Secukinumab, IL-17A sequestering agent used in treating psoriasis, was selected as a candidate to address inflammatory disorders. Our analysis suggests this novel combinatorial approach has a high likelihood of ameliorating a significant portion of the clustered clinical risk in MetS. Author summary Metabolic syndrome is a global epidemic affecting a significant population worldwide. This syndrome is the manifestation of clustered clinical conditions that cannot be fully ameliorated with monotherapies. No therapeutic approaches were confirmed to be effective in deceleration of the metabolic syndrome progression. Artificial intelligence driven computation methods were used to predict efficacy of innovative combinatorial therapy using IL-17A sequestering agent and a DPP-4 inhibitor. They are expected to mitigate a significant portion of the clustered risks in metabolic syndrome disrupting key pathological pathways playing important role in development of this syndrome. The main therapeutic effects are related to reduction of the elevated lipid level and high glucose concentration. Combinatorial treatment could potentially stop or reverse a significant portion of the clinical risks in metabolic syndrome globally. Repurposing of approved FDA drugs can have increased likelihood of approval of the new therapeutic regimens and can reach patients faster with reduced costs of treatment.

The full scope and limitations of the catalytic acylative kinetic resolution of a range of tertiary heterocyclic alcohols (78 examples, s up to >200) is reported under operationally-simple conditions, using low loadings of a commercially available Lewis basic isothiourea catalyst, HyperBTM (generally 1 mol %). The protocol is highly effective for the kinetic resolution of 3-substituted 3-hydroxyoxindole and alpha-substituted alpha-hydroxylactam derivatives bearing up to three potential recognition motifs at the stereogenic tertiary carbinol center. The full power of this methodology has been showcased through the synthesis of highly enantioenriched biologically-active target compounds in both enantiomeric forms. To provide further insight into the reaction mechanism, a detailed kinetic analysis of this Lewis base-catalyzed acylation of tertiary alcohols is reported using the variable time normalization analysis (VTNA) method.

Fluoroquinolones (FQs) are a widespread class of broad-spectrum antibiotics prescribed as a first line of defense, and, in some cases, as the only treatment against bacterial infection. However, when administered orally, reduced absorption and bioavailability can occur due to chelation in the gastrointestinal tract (GIT) with multivalent metal cations acquired from diet, coadministered compounds (sucralfate, didanosine), or drug formulation. Predicting the extent to which this interaction reduces in vivo antibiotic absorption and systemic exposure remains desirable yet challenging. In this study, we focus on quinolone interactions with magnesium, calcium and aluminum as found in dietary supplements, antacids (Maalox) orally administered therapies (sucralfate, didanosine). The effect of FQ–metal complexation on absorption rate was investigated through a combined molecular and pharmacokinetic (PK) modeling study. Quantum mechanical calculations elucidated FQ–metal binding energies, which were leveraged to predict the magnitude of reduced bioavailability via a quantitative structure–property relationship (QSPR). This work will help inform clinical FQ formulation design, alert to possible dietary effects, and shed light on drug–drug interactions resulting from coadministration at an earlier stage in the drug development pipeline.

Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API–carrier mixture and the principal API–carrier non-bonding interactions are critical factors for rational drug development and formulation decisions. Experimental determination of these interactions, solubility, and dissolution mechanisms is time-consuming, costly, and reliant on trial and error. To that end, molecular modeling has been applied to simulate ASD properties and mechanisms. Quantum mechanical methods elucidate the strength of API–carrier non-bonding interactions, while molecular dynamics simulations model and predict ASD physical stability, solubility, and dissolution mechanisms. Statistical learning models have been recently applied to the prediction of a variety of drug formulation properties and show immense potential for continued application in the understanding and prediction of ASD solubility. Continued theoretical progress and computational applications will accelerate lead compound development before clinical trials. This article reviews in silico research for the rational formulation design of low-solubility drugs. Pertinent theoretical groundwork is presented, modeling applications and limitations are discussed, and the prospective clinical benefits of accelerated ASD formulation are envisioned.

Enantioselective additions to oxocarbenium ions are high-value synthetic transformations but have proven challenging to achieve. In particular, the oxa-Pictet-Spengler reaction has only recently been rendered enantioselective. We report experimental and computational studies on the mechanism of this unusual transformation. Herein we reveal that this reaction is hypothesized to proceed through a self-assembled ternary hydrogen bonding complex involving the substrate, chiral phosphate ion, and a urea hydrogen-bond donor. The computed transition state reveals C2-symmetric grooves in the chiral phosphate that are occupied by the urea and substrate. Occupation of one of these grooves by the urea co-catalyst tunes the available reactive volume and enhances the stereoselectivity of the chiral phosphate catalyst.

The reaction mechanism for lignin electrolysis has been rarely studied. In a previous work, we reported the electrolysis of lignin on a Polymer Electrolyte Membrane (PEM) alkaline electrolyzer with PtRu-based anodes. Even though the performance of this technology was proven in a low range of applied potentials (<1.2 V) and reaction temperatures (<90 degrees C), the activity of the system was strongly hindered, leading to low H(2)production rates. The aim of this work is to study the main limitations of PtRu electrodes for lignin electro-oxidation. 2-Phenoxyethanol, 2-PE, has been chosen as a model molecule of the beta-O-4 linkage, which represents 60% of the lignin bio-polymer. The performed electrochemical experiments, together with the HPLC analysis of the anodic products and the thermodynamic DFT computations, suggest that the electro-oxidation of the 2-PE organic molecule is very limited and leads to the production of the carboxylic acid as the final reaction product. In addition, the electro-catalytic system was severely poisoned, probably owing to the presence of some reaction by-products. All in all, this study allows advancing one step-forward towards understanding the reaction mechanism and the main limitations of the lignin electrolysis technology in the above described system.

Hydroxide ion is shown to be a potent disruptor of Ru-catalyzed olefin metathesis, in a study of the Hoveyda catalyst HII. Addition of [(NBu4)-Bu-n][OH] immediately terminates metathesis via HII, an effect traced to formation of bis(hydroxide) complex HII-OH. The latter was synthesized for direct study. HII-OH initiates very slowly on reaction with olefins, and decomposes in the first cycle of metathesis. Computational analysis reveals rapid bimolecular coupling between HII-OH and its four-coordinate methylidene derivative. Importantly, fully decomposed catalyst also accelerates decomposition of HII-OH. The H-bonding capacity of the hydroxide ligand is proposed as a powerful driving force for degradation.

Axially chiral phenols are attractive targets in organic synthesis. This motif is central to many natural products and widely used as precursors to, or directly, as chiral ligands and catalysts. Despite their utility few simple catalytic methods are available for their synthesis in high enantiopurity. Herein the atropselective acylation of a range of symmetric biaryl diols is investigated using isothiourea catalysis. Studies on a model biaryl diol substrate shows that the high product er observed in the process is a result of two successive enantioselective reactions consisting of an initial enantioselective desymmetrization coupled with a second chiroablative kinetic resolution. Extension of this process to a range of substrates, including a challenging tetraorthosubstituted biaryl diol, led to highly enantioenriched products (14 examples, up to 98:2 er), with either HyperBTM or BTM identified as the optimal catalyst depending upon the substitution pattern within the substrate. Computation has been used to understand the factors that lead to high enantiocontrol in this process, with maintenance of planarity to maximize a 1,5-S⋅⋅⋅O interaction within the key acyl ammonium intermediate identified as the major feature that determines atropselective acylation and thus product enantioselectivity.

The enantioselective preparation of a range of perfluoroalkyl-substituted beta-lactones through an isothiourea (HyperBTM) catalysed reaction using symmetric anhydrides as ammonium enolate precursors and perfluoroalkylketones (R-F = CF3, C2F5, C4F9) is reported. Following optimisation, high diastereo- and enantioselectivity was observed for beta-lactone formation using C2F5- and C4F9-substituted ketones at room temperature (26 examples, up to >95 : 5 dr and >99 : 1 er), whilst -78 degrees C was necessary for optimal dr and er with CF3-substituted ketones (11 examples, up to >95 : 5 dr and >99 : 1 er). Derivatisation of the beta-lactones through ring-opening, as well as a two-step conversion to give perfluoroalkyl-substituted oxetanes, is demonstrated without loss of stereochemical integrity. Density functional theory computations, alongside C-13 natural abundance KIE studies, have been used to probe the reaction mechanism with a concerted asynchronous [2 + 2]-cycloaddition pathway favoured over a stepwise aldol-lactonisation process.

Polycyclic aromatic hydrocarbons (PAHs) undergo transformation reactions with atmospheric photochemical oxidants, such as hydroxyl radicals (OH•), nitrogen oxides (NOx), and ozone (O3). The most common PAH-transformation products (PAH-TPs) are nitrated, oxygenated, and hydroxylated PAHs (NPAHs, OPAHs, and OHPAHs, respectively), some of which are known to pose potential human health concerns. We sampled four theoretical approaches for predicting the location of reactive sites on PAHs (i.e., the carbon where atmospheric oxidants attack), and hence the chemoselectivity of the PAHs. All computed results are based on density functional theory (B3LYP/6-31G(d) optimized structures and energies). The four approaches are (1) Clar's prediction of aromatic resonance structures, (2) thermodynamic stability of all OHPAH adduct intermediates, (3) computed atomic charges (Natural Bond order, ChelpG, and Mulliken) at each carbon on the PAH, and (4) average local ionization energy (ALIE) at atom or bond sites. To evaluate the accuracy of these approaches, the predicted PAH-TPs were compared to published laboratory observations of major NPAH, OPAH, and OHPAH products in both gas and particle phases. We found that the Clar's resonance structures were able to predict the least stable rings on the PAHs but did not offer insights in terms of which individual carbon is most reactive. The OHPAH adduct thermodynamics and the ALIE approaches were the most accurate when compared to laboratory data, showing great potential for predicting the formation of previously unstudied PAH-TPs that are likely to form in the atmosphere.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

A combination of experimental and computational studies have identified a C=O⋅⋅⋅isothiouronium interaction as key to efficient enantiodiscrimination in the kinetic resolution of tertiary heterocyclic alcohols bearing up to three potential recognition motifs at the stereogenic tertiary carbinol center. This discrimination was exploited in the isothiourea-catalyzed acylative kinetic resolution of tertiary heterocyclic alcohols (38 examples, s factors up to >200). The reaction proceeds at low catalyst loadings (generally 1 mol %) with either isobutyric or acetic anhydride as the acylating agent under mild conditions.

Since the first report of a facile, room temperature process to access aza-ortho-quinone methides (aoQMs) by Corey in 1999, this chemistry has remained dormant until our report of an enantioselective catalytic example in 2014. We report a theoretical and experimental study of the key to success behind these successful examples to enable broader exploitation of this useful intermediate. We have discovered that transformations involving the aoQM are remarkably facile with barriers <17 kcal/mol. The main difficulty of exploiting aoQM in synthesis is that they are unstable (ΔG > 30 kcal/mol), precluding their formation under mild conditions. The use of Cs2CO3 as base is critical. It provides a thermodynamically and kinetically favorable means to form aoQMs, independent of the salt solubility and base strength. The exothermic formation of salt byproducts provides a driving force (average ΔG = -30.8 kcal/mol) compensating for the majority of the inherent unfavorable thermodynamics of aoQM formation.

A mechanistic study of the isothiourea-catalyzed enantioselective [2,3]-rearrangement of allylic ammonium ylides is described. Reaction kinetic analyses using 19F NMR and density functional theory computations have elucidated a reaction profile and allowed identification of the catalyst resting state and turnover-rate limiting step. A catalytically relevant catalyst-substrate adduct has been observed, and its constitution elucidated unambiguously by 13C and 15N isotopic labeling. Isotopic entrainment has shown the observed catalyst-substrate adduct to be a genuine intermediate on the productive cycle toward catalysis. The influence of HOBt as an additive upon the reaction, catalyst resting state, and turnover-rate limiting step has been examined. Crossover experiments have probed the reversibility of each of the proposed steps of the catalytic cycle. Computations were also used to elucidate the origins of stereocontrol, with a 1,5-S···O interaction and the catalyst stereodirecting group providing transition structure rigidification and enantioselectivity, while preference for cation-π interactions over C-H···π is responsible for diastereoselectivity.

The Armillaria and Lactarius genera of fungi produce the antimicrobial and cytotoxic mellolide, protoilludane, and marasmane sesquiterpenoids. We report a unified synthetic strategy to access the protoilludane, mellolide, and marasmane families of natural products. The key features of these syntheses are 1) the organocatalytic, enantioselective construction of key chiral intermediates from a simple achiral precursor, 2) the utility of a key 1,2-cyclobutanediol intermediate to serve as a precursor to each natural product class, and 3) a direct chemical conversion of a protoilludane to a marasmane through serendipitous ring contraction, which provides experimental support for their proposed biosynthetic relationships.