Structure-activity Data Research Articles

Electrochemical CO2 Reduction over Cu-Based Gas Diffusion Electrodes: A Complementary Spectroscopic Study

Electrochemical CO2 reduction (eCO2R) over copper gas diffusion electrode (Cu-GDE) has the potential to generate multi carbon products (C2+ such as ethylene and ethanol) with renewable electricity at a commercial scale [1-3]. To unlock the potential, selectivity towards a desired product with acceptable current densities are a must [1-3]. Efforts are being made to understand catalyst structure, activity and selectivity relationships by different techniques, including a few in situ and operando X-ray absorption spectroscopy (XAS) studies [3-7]. However, there is no consensus on the active and selective site/phase composition of copper for ethylene production. On the one hand, the occurrence of only metallic Cu during the reaction is reported [3-7] while on the other hand, some of these studies find no correlation between the metallic Cu and eCO2R products distribution [3,4]. Differently, the occurrence of Cu(OH)2 and Cu2O (along with metallic Cu) during the reaction is also reported [5,6]. The discrepancies could be a result of varied experimental conditions and in situ / operando cell designs [3-7]. The latter could play a key role in obtaining reliable structure-activity data [8]. The observations emphasise the need for targeted and cell specific operando spectroscopic studies to unravel structure, activity and selectivity relationships [3].In the present study we report a novel operando XAS GDE flow cell with a three-phase system (i.e., gaseous CO2, liquid electrolyte and solid catalyst) to conduct experiments in a transmission mode that probes the Cu-GDE from surface to bulk and provides information on the copper oxidation and coordination states during the reaction. It would, however, not be able to distinguish between the surface and bulk composition [3] and hence complementary surface sensitive quasi in situ X-ray photoelectron spectroscopy (XPS) is employed to probe copper dynamics on the Cu-GDE surface [9]. The data are then complemented by Raman spectroscopy that monitors not only the surface adsorbed species but also the evolution of copper speciation (even very amorphous species) during the reaction [10].The dynamic behaviour of copper during the reaction is captured by X-ray absorption near edge structure (XANES) spectra. Linear combination analyses (LCA) show that within the first 20 min of the reaction, copper is only in oxidised state (mainly CuO and minority Cu2O), which is corroborated by the quasi in situ Raman spectroscopy and X-ray photoelectron spectroscopy(XPS). The majority of CuO is reduced to Cu2O (44%) and metallic Cu (44%) at 30 min of the reaction. The metallic Cu content increased to 77% at 60 min of the reaction, however remarkably the remainder (23%) of the copper is in the Cu2+ oxidation state. The latter is not detected by quasi in situ XPS that instead shows copper only in < 2+ oxidation state, potentially as metallic Cu. This implies that the bulk composition is different from the surface composition which is further confirmed by the quasi in situ Raman that shows the presence of copper oxides, Cu(OH)2 and CO adsorbed metallic Cu at 60 min. Based on the complementary spectroscopic data, eCO2R data will be correlated with the catalyst structure dynamics and structure-activity relations will be discussed.

Proposition of In silico Pharmacophore Models for Malaria: A Review.

In the field of medicinal chemistry, the concept of pharmacophore refers to the specific region of a molecule that possesses essential structural and chemical characteristics for binding to a receptor and eliciting biological activity. Understanding the pharmacophore is crucial for drug research and development, as it allows the design of new drugs. Malaria, a widespread disease, is commonly treated with chloroquine and artemisinin, but the emergence of parasite resistance limits their effectiveness. This study aims to explore computer simulations to discover a specific pharmacophore for Malaria, providing new alternatives for its treatment. A literature review was conducted, encompassing articles proposing a pharmacophore for Malaria, gathered from the "Web of Science" database, with a focus on recent publications to ensure up-to-date analysis. The selected articles employed diverse methods, including ligand-based and structurebased approaches, integrating molecular structure and biological activity data to yield comprehensive analyses. Affinity evaluation between the proposed pharmacophore and the target receptor involved calculating free energy to quantify their interaction. Multiple linear regression was commonly utilized, though it is sensitive to multicollinearity issues. Another recurrent methodology was the use of the Schrödinger package, employing tools such as the Phase module and the OPLS force field for interaction analysis. Pharmacophore model proposition allows threedimensional representations guiding the synthesis and design of new biologically active compounds, offering a promising avenue for discovering therapeutic agents to combat Malaria.

From mundane to surprising nonadditivity: drivers and impact on ML models.

Nonadditivity (NA) in Structure-Activity and Structure-Property Relationship (SAR) data is a rare but very information rich phenomenon. It can indicate conformational flexibility, structural rearrangements, and errors in assay results and structural assignment. While purely ligand-based conformational causes of NA are rather well understood and mundane, other factors are less so and cause surprising NA that has a huge influence on SAR analysis and ML model performance. We here report a systematic analysis across a wide range of properties (20 on-target biological activities and 4 physicochemical ADME-related properties) to understand the frequency of various different phenomena that may lead to NA. A set of novel descriptors were developed to characterize double transformation cycles and identify trends in NA. Double transformation cycles were classified into "surprising" and "mundane" categories, with the majority being classed as mundane. We also examined commonalities among surprising cycles, finding LogP differences to have the most significant impact on NA. A distinct behavior of NA for on-target sets compared to ADME sets was observed. Finally, we show that machine learning models struggle with highly nonadditive data, indicating that a better understanding of NA is an important future research direction.

Task-Similarity is a Crucial Factor for Few-Shot Meta-Learning of Structure-Activity Relationships.

Machine learning models support computer-aided molecular design and compound optimization. However, the initial phases of drug discovery often face a scarcity of training data for these models. Meta-learning has emerged as a potentially promising strategy, harnessing the wealth of structure-activity data available for known targets to facilitate efficient few-shot model training for the specific target of interest. In this study, we assessed the effectiveness of two different meta-learning methods, namely model-agnostic meta-learning (MAML) and adaptive deep kernel fitting (ADKF), specifically in the regression setting. We investigated how factors such as dataset size and the similarity of training tasks impact predictability. The results indicate that ADKF significantly outperformed both MAML and a single-task baseline model on the inhibition data. However, the performance of ADKF varied across different test tasks. Our findings suggest that considerable enhancements in performance can be anticipated primarily when the task of interest is similar to the tasks incorporated in the meta-learning process.

Structure Activity of β-Amidomethyl Vinyl Sulfones as Covalent Inhibitors of Chikungunya nsP2 Cysteine Protease with Anti-alphavirus Activity.

Despite their widespread impact on human health there are no approved drugs for combating alphavirus infections. The heterocyclic β-aminomethyl vinyl sulfone RA-0002034 (1a) is a potent irreversible covalent inhibitor of the alphavirus nsP2 cysteine protease with broad spectrum antiviral activity. Analogs of 1a that varied each of three regions of the molecule were synthesized to establish structure-activity relationships for inhibition of Chikungunya (CHIKV) nsP2 protease and viral replication. The covalent warhead was highly sensitive to modifications of the sulfone or vinyl substituents. However, numerous alterations to the core 5-membered heterocycle and its aryl substituent were well tolerated and several analogs were identified that enhanced CHIKV nsP2 binding. For example, the 4-cyanopyrazole analog 8d exhibited a kinact /Ki ratio >10,000 M-1s-1. 3-Arylisoxazole was identified an isosteric replacement for the 5-membered heterocycle, which circumvented the intramolecular cyclization that complicated the synthesis of pyrazole-based inhibitors like 1a. The accumulated structure-activity data was used to build a ligand-based model of the enzyme active site, which can be used to guide the design of covalent nsP2 protease inhibitors as potential therapeutics against alphaviruses.

Exploring Subsite Selectivity within Plasmodium vivax N-Myristoyltransferase Using Pyrazole-Derived Inhibitors.

N-myristoyltransferase (NMT) is a promising antimalarial drug target. Despite biochemical similarities between Plasmodium vivax and human NMTs, our recent research demonstrated that high selectivity is achievable. Herein, we report PvNMT-inhibiting compounds aimed at identifying novel mechanisms of selectivity. Various functional groups are appended to a pyrazole moiety in the inhibitor to target a pocket formed beneath the peptide binding cleft. The inhibitor core group polarity, lipophilicity, and size are also varied to probe the water structure near a channel. Selectivity index values range from 0.8 to 125.3. Cocrystal structures of two selective compounds, determined at 1.97 and 2.43 Å, show that extensions bind the targeted pocket but with different stabilities. A bulky naphthalene moiety introduced into the core binds next to instead of displacing protein-bound waters, causing a shift in the inhibitor position and expanding the binding site. Our structure-activity data provide a conceptual foundation for guiding future inhibitor optimizations.

Silicon-Rhodamine Functionalized Evocalcet Probes Potently and Selectively Label Calcium Sensing Receptors In Vitro, In Vivo, and Ex Vivo.

The calcium sensing receptor (CaSR) is a ubiquitously expressed G-protein coupled receptor (GPCR) that regulates extracellular calcium signals via the parathyroid glands. CaSR has recently also been implicated in noncalcitropic pathophysiologies like asthma, gut inflammation, and cancer. To date, molecular tools that enable the bioimaging of CaSR in tissues are lacking. Based on in silico analyses of available structure-activity relationship data on CaSR ligands, we designed and prepared silicon-rhodamine (SiR) conjugates of the clinically approved drug evocalcet. The new probes EvoSiR4 and EvoSiR6, with differing linker lengths at the evocalcet carboxyl end, both showed a 6-fold and 3-fold increase in potency toward CaSR (EC50 < 45 nM) compared to evocalcet and the evocalcet-linker conjugate, respectively, in an FLIPR-based cellular functional assay. The specificity of the EvoSiR probes toward CaSR binding and the impact of albumin was evaluated in live cell experiments. Both probes showed strong albumin binding, which facilitated the clearance of nonspecific binding interactions. Accordingly, in zebrafish embryos, EvoSiR4 specifically labeled the high CaSR expressing neuromasts of the lateral line in vivo. EvoSiR4 was also assessed in human parathyroid tissues ex vivo, showing a specific absolute CaSR-associated fluorescence compared to that of parathyroid autofluorescence. In summary, functionalization of evocalcet by SiR led to the preparation of potent and specific fluorescent CaSR probes. EvoSiR4 is a versatile small-molecular probe that can be employed in CaSR-related biomedical analyses where antibodies are not applicable.

Determination of Pharmacokinetic and Toxicological Parameters of Some Commonly Used Statin Group Drugs

Statins work as inhibitors of the HMG-CoA reductase enzyme and are the most commonly prescribed cholesterol-lowering drug group for people with cardiovascular disease or risk. This study aimed to determine the pharmacokinetic parameters and toxicities of conventional and new-generation cholesterol drugs such as atorvastatin, fluvastatin, lovastatin, pravastatin, simvastatin, rosuvastatin and pitavastatin. Absorption, distribution, metabolism, and excretion (ADME) parameters and toxicity predictions of drugs were made using in silico modeling, which gives faster results than animal experiments and does not involve any laboratory costs. In calculations made using structural similarity, compounds' pharmacokinetic properties and toxicity predictions are obtained based on previously known structure-activity data. The study results showed that the toxicity classifications of the drugs were 5 (LD: 5000 mg/kg) for atorvastatin and 6 (LD: 8939 mg/kg) for pravastatin, respectively. The toxicity classes were found to be 4 for all the other statin group drugs. The results showed that pravastatin had the lowest toxicity among investigated cholesterol drugs, while pitavastatin and fluvastatin had the highest toxic effects. Accordingly, it is recommended that the consequences of using pravastatin and atorvastatin, cholesterol drugs with lower toxicity classes, should be investigated more seriously in terms of minimum toxic substance intake for patient groups requiring high doses of medication.

Generalizability Improvement of Interpretable Symbolic Regression Models for Quantitative Structure-Activity Relationships.

In the pursuit of optimal quantitative structure-activity relationship (QSAR) models, two key factors are paramount: the robustness of predictive ability and the interpretability of the model. Symbolic regression (SR) searches for the mathematical expressions that explain a training data set. Thus, the models provided by SR are globally interpretable. We previously proposed an SR method that can generate interpretable expressions by humans. This study introduces an enhanced symbolic regression method, termed filter-induced genetic programming 2 (FIGP2), as an extension of our previously proposed SR method. FIGP2 is designed to improve the generalizability of SR models and to be applicable to data sets in which cost-intensive descriptors are employed. The FIGP2 method incorporates two major improvements: a modified domain filter to eradicate diverging expressions based on optimal calculation and the introduction of a stability metric to penalize expressions that would lead to overfitting. Our retrospective comparative analysis using 12 structure-activity relationship data sets revealed that FIGP2 surpassed the previously proposed SR method and conventional modeling methods, such as support vector regression and multivariate linear regression in terms of predictive performance. Generated mathematical expressions by FIGP2 were relatively simple and not divergent in the domain of function. Taken together, FIGP2 can be used for making interpretable regression models with predictive ability.

Discovery of Potential Prolyl-tRNA Synthetase Allosteric Inhibitor Through Virtual Screening and In Vitro Assay against Plasmodium falciparum

Objectives: This study aimed to identify novel antimalarial compounds based on allosteric inhibitor of prolyl-tRNA synthetase using hierarchical virtual screening. Materials and Methods: Pharmacophore model was designed initially, based on the structure-activity relationships data between several pyrazole-urea analogues and their IC50 enzymatic value. The model obtained was applied to screen ZINC15 database, after which followed by drug-likeness, toxicophore, and PAINS filter. The hit compounds were docked against P. falciparum prolyl-tRNA synthetase enzyme, using validated docking method. The resulting docking poses were ranked based on the docking score and re-evaluated based on the pharmacophore criteria. Top five compounds were obtained from this step and then evaluated using molecular dynamics simulation to verify its stability and hydrogen bond dynamics over 50 nanoseconds. MM-PBSA analysis was also performed to estimate their binding free energy. Ultimately, their potential bioactivity as antimalarial candidates have been verified against 3D7 strain. Results: The results showed that all five compounds obtained from virtual screening possess micromolar potency in vitro. Two compounds (ZINC 1029449 and ZINC1029453), yield high antimalarial activity (0.44 and 0.72 μM, respectively) Conclusions: Overall, the virtual screening approach has successfully produced lead compounds which can be further optimized to be antimalarial agents.

Consensus docking aid to model the activity of an inhibitor of DNA methyltransferase 1 inspired by de novo design

The structure-activity relationships data available in public databases of inhibitors of DNA methyltransferases (DNMTs), families of epigenetic targets, plus the structural information of DNMT1, enables the development of a robust structure-based drug design strategy to study, at the molecular level, the activity of DNMTs inhibitors. In this study, we discuss a consensus molecular docking strategy to aid in explaining the activity of small molecules tested as inhibitors of DNMT1. The consensus docking approach, which was based on three validated docking algorithms of different designs, had an overall good agreement with the experimental enzymatic inhibition assays reported in the literature. The docking protocol was used to explain, at the molecular level, the activity profile of a novel DNMT1 inhibitor with a distinct chemical scaffold whose identification was inspired byde novodesign and complemented with similarity searching.

Drug-Induced Conformational Dynamics of P-Glycoprotein Underlies the Transport of Camptothecin Analogs.

P-glycoprotein (Pgp) plays a pivotal role in drug bioavailability and multi-drug resistance development. Understanding the protein's activity and designing effective drugs require insight into the mechanisms underlying Pgp-mediated transport of xenobiotics. In this study, we investigated the drug-induced conformational changes in Pgp and adopted a conformationally-gated model to elucidate the Pgp-mediated transport of camptothecin analogs (CPTs). While Pgp displays a wide range of conformations, we simplified it into three model states: 'open-inward', 'open-outward', and 'intermediate'. Utilizing acrylamide quenching of Pgp fluorescence as a tool to examine the protein's tertiary structure, we observed that topotecan (TPT), SN-38, and irinotecan (IRT) induced distinct conformational shifts in the protein. TPT caused a substantial shift akin to AMPPNP, suggesting ATP-independent 'open-outward' conformation. IRT and SN-38 had relatively moderate effects on the conformation of Pgp. Experimental atomic force microscopy (AFM) imaging supports these findings. Further, the rate of ATPase hydrolysis was correlated with ligand-induced Pgp conformational changes. We hypothesize that the separation between the nucleotide-binding domains (NBDs) creates a conformational barrier for substrate transport. Substrates that reduce the conformational barrier, like TPT, are better transported. The affinity for ATP extracted from Pgp-mediated ATP hydrolysis kinetics curves for TPT was about 2-fold and 3-fold higher than SN-38 and IRT, respectively. On the contrary, the dissociation constants (KD) determined by fluorescence quenching for these drugs were not significantly different. Saturation transfer double difference (STDD) NMR of TPT and IRT with Pgp revealed that similar functional groups of the CPTs are accountable for Pgp-CPTs interactions. Efforts aimed at modifying these functional groups, guided by available structure-activity relationship data for CPTs and DNA-Topoisomerase-I complexes, could pave the way for the development of more potent next-generation CPTs.

Computer-aided drug repurposing to tackle antibiotic resistance based on topological data analysis

The progressive emergence of antimicrobial resistance has become a global health problem in need of rapid solution. Research into new antimicrobial drugs is imperative. Drug repositioning, together with computational mathematical prediction models, could be a fast and efficient method of searching for new antibiotics. The aim of this study was to identify compounds with potential antimicrobial capacity against Escherichia coli from US Food and Drug Administration-approved drugs, and the similarity between known drug targets and E. coli proteins using a topological structure-activity data analysis model. This model has been shown to identify molecules with known antibiotic capacity, such as carbapenems and cephalosporins, as well as new molecules that could act as antimicrobials. Topological similarities were also found between E. coli proteins and proteins from different bacterial species such as Mycobacterium tuberculosis, Pseudomonas aeruginosa and Salmonella Typhimurium, which could imply that the selected molecules have a broader spectrum than expected. These molecules include antitumor drugs, antihistamines, lipid-lowering agents, hypoglycemic agents, antidepressants, nucleotides, and nucleosides, among others. The results presented in this study prove the ability of computational mathematical prediction models to predict molecules with potential antimicrobial capacity and/or possible new pharmacological targets of interest in the design of new antibiotics and in the better understanding of antimicrobial resistance.

The importance of the PapR7 C-terminus and amide protons in mediating quorum sensing in Bacilluscereus

The opportunistic human pathogen Bacillus cereus controls the expression of key infection-promoting phenotypes using bacterial quorum sensing (QS). QS signal transduction within the species is controlled by an autoinducing peptide, PapR7, and its cognate receptor, PlcR, indicating that the PlcR:PapR interface is a prime target for QS inhibitor development. The C-terminal region of the peptide (PapR7; ADLPFEF) has been successfully employed as a scaffold to develop potent QS modulators. Despite the noted importance of the C-terminal carboxylate and amide protons in crystallographic data, their role in QS activity has yet to be explored. In this study, an N-methyl scan of PapR7 was conducted in conjunction with a C-terminal modification of previously identified B. cereus QS inhibitors. The results indicate that the amide proton at Glu6 and the C-terminal carboxylate are important for effective QS inhibition of the PlcR regulon. Through β-galactosidase and hemolysis assays, a series of QS inhibitors were discovered, including several capable of inhibiting QS with nanomolar potency. These inhibitors, along with the structure–activity data reported, will serve as valuable tools for disrupting the B. cereus QS pathway towards developing novel anti-infective strategies.

Exploiting Chemical Protein Synthesis to Study the Role of Tyrosine Sulfation on Anticoagulants from Hematophagous Organisms.

ConspectusTyrosine sulfation is a post-translational modification (PTM) that modulates function by mediating key protein-protein interactions. One of the early proteins shown to possess this PTM was hirudin, produced in the salivary glands of the medicinal leech Hirudo medicinalis, whereby tyrosine sulfation led to a ∼10-fold improvement in α-thrombin inhibitory activity. Outside of this pioneering discovery, the involvement of tyrosine sulfation in modulating the activity of salivary proteins from other hematophagous organisms was unknown. We hypothesized that the intrinsic instability of the tyrosine sulfate functionality, particularly under the acidic conditions used to isolate and analyze peptides and proteins, has led to poor detection during the isolation and/or expression of these molecules.Herein, we summarize our efforts to interrogate the functional role of tyrosine sulfation in the thrombin inhibitory and anticoagulant activity of salivary peptides and proteins from a range of different blood feeding organisms, including leeches, ticks, mosquitoes, and flies. Specifically, we have harnessed synthetic chemistry to efficiently generate homogeneously sulfated peptides and proteins for detailed structure-function studies both in vitro and in vivo.Our studies began with the leech protein hirudin P6 (from Hirudinaria manillensis), which is both sulfated on tyrosine and O-glycosylated at a nearby threonine residue. Synthetically, this was achieved through solid-phase peptide synthesis (SPPS) with a late-stage on-resin sulfation, followed by native chemical ligation and a folding step to generate six differentially modified variants of hirudin P6 to assess the functional interplay between O-glycosylation and tyrosine sulfation. A one-pot, kinetically controlled ligation of three peptide fragments was used to assemble homogeneously sulfoforms of madanin-1 and chimadanin from the tick Haemaphysalis longicornis. Dual tyrosine sulfation at two distinct sites was shown to increase the thrombin inhibitory activity by up to 3 orders of magnitude through a novel interaction with exosite II of thrombin. The diselenide-selenoester ligation developed by our lab provided us with a means to rapidly assemble a library of different sulfated tick anticoagulant proteins: the andersonins, hyalomins, madanin-like proteins, and hemeathrins, thus enabling the generation of key structure-activity data on this family of proteins. We have also confirmed the presence of tyrosine sulfation in the anticoagulant proteins of Anopheles mosquitoes (anophelins) and the Tsetse fly (TTI) via insect expression and mass spectrometric analysis. These molecules were subsequently synthesized and assessed for thrombin inhibitory and anticoagulant activity. Activity was significantly improved by the addition of tyrosine sulfate modifications and led to molecules with potent antithrombotic activity in an in vivo murine thrombosis model.The Account concludes with our most recent work on the design of trivalent hybrids that tandemly occupy the active site and both exosites (I and II) of α-thrombin, with a TTI-anophelin hybrid (Ki = 20 fM against α-thrombin) being one of the most potent protease inhibitors and anticoagulants ever generated. Taken together, this Account highlights the importance of the tyrosine sulfate post-translational modification within salivary proteins from blood feeding organisms for enhancing anticoagulant activity. This work lays the foundation for exploiting native or engineered variants as therapeutic leads for thrombotic disorders in the future.

Optimization of pyridylpiperazine-based inhibitors of the Escherichia coli AcrAB-TolC efflux pump

Multidrug–resistant Escherichia coli is a continuously growing worldwide public health problem, in which the well-known AcrAB-TolC tripartite RND efflux pump is a critical driver. We have previously described pyridylpiperazines as a novel class of allosteric inhibitors of E. coli AcrB which bind to a unique site in the protein transmembrane domain, allowing for the potentiation of antibiotic activity. Here, we show a rational optimization of pyridylpiperazines by modifying three specific derivatization points of the pyridine core to improve the potency and the pharmacokinetic properties of this chemical series. In particular, this work found that the introduction of a primary amine to the pyridine through ester (29, BDM91270) or oxadiazole (44, BDM91514) based linkers allowed for analogues with improved antibiotic boosting potency through AcrB inhibition. In vitro studies, using genetically engineered mutants, showed that this improvement in potency is mediated through novel interactions with distal acidic residues of the AcrB binding pocket. Of the two leads, compound 44 was found to have favorable physico-chemical properties and suitable plasma and microsomal stability. Together, this work expands the current structure-activity relationship data on pyridylpiperazine efflux pump inhibitors, and provides a promising step towards future in vivo proof of concept of pyridylpiperazines as antibiotic potentiators.

Synthesis and preliminary evaluation of benzylaminoimidazoline derivatives as novel norepinephrine transporter ligands.

A series of benzylaminoimidazoline derivatives was synthesized and evaluated for norepinephrine transporter (NET) targeting. Among them, N-(3-iodobenzyl)-4,5-dihydro-1H-imidazol-2-amine (Compound 9) displayed the highest affinity for NET (IC50 = 5.65 ± 0.97 μM). The corresponding radiotracer [125 I]9 was further prepared by copper-mediated radioiodination and evaluated both in vitro and in vivo. The cellular uptake results suggested that [125 I]9 was specifically taken up by the NET-expressing SK-N-SH cell line. Biodistribution studies showed that [125 I]9 accumulated in the heart (5.54 ± 1.24 %ID/g at 5 min p.i. and 0.79 ± 0.08 %ID/g at 2 h p.i.) and adrenal gland (14.83 ± 3.47 %ID/g at 5 min p.i. and 3.87 ± 0.24 %ID/g at 2 h p.i.). The uptake in the heart and adrenal gland could be significantly inhibited by preinjection of desipramine (DMI). These results indicated that the benzylaminoimidazoline derivatives retained affinity for NET, which could provide structure-activity relationship data for further studies.

Structure of the complex between calmodulin and a functional construct of eukaryotic elongation factor 2 kinase bound to an ATP-competitive inhibitor

The calmodulin-activated α-kinase, eukaryotic elongation factor 2 kinase (eEF-2K), serves as a master regulator of translational elongation by specifically phosphorylating and reducing the ribosome affinity of the guanosine triphosphatase, eukaryotic elongation factor 2 (eEF-2). Given its critical role in a fundamental cellular process, dysregulation of eEF-2K has been implicated in several human diseases, including those of the cardiovascular system, chronic neuropathies, and many cancers, making it a critical pharmacological target. In the absence of high-resolution structural information, high-throughput screening efforts have yielded small-molecule candidates that show promise as eEF-2K antagonists. Principal among these is the ATP-competitive pyrido-pyrimidinedione inhibitor, A-484954, which shows high specificity toward eEF-2K relative to a panel of "typical" protein kinases. A-484954 has been shown to have some degree of efficacy in animal models of several disease states. It has also been widely deployed as a reagent in eEF-2K-specific biochemical and cell-biological studies. However, given the absence of structural information, the precise mechanism of the A-484954-mediated inhibition of eEF-2K has remained obscure. Leveraging our identification of the calmodulin-activatable catalytic core of eEF-2K, and our recent determination of its long-elusive structure, here we present the structural basis for its specific inhibition by A-484954. This structure, which represents the first for an inhibitor-bound catalytic domain of a member of the α-kinase family, enables rationalization of the existing structure-activity relationship data for A-484954 variants and lays the groundwork for further optimization of this scaffold to attain enhanced specificity/potency against eEF-2K.

Structure–Activity Relationships for Hypervalent Iodine Electrocatalysis

AbstractThe design and optimization of novel electrocatalysts requires robust structure–activity data to correlate catalyst structure with electrochemical behavior. Aryl iodides have been gaining attention as metal-free electrocatalysts but experimental data are available for only a limited set of structures. Herein we report electrochemical data for a family of 70 aryl iodides. Half-peak potentials are utilized as proxies for reduction potentials and reveal that, despite differences in electrochemical reversibility, the potential for one-electron oxidation of 4-substituted aryl iodides to the corresponding iodanyl radicals is well-correlated with standard Hammett parameters. Additional data are presented for 3- and 2-substituted aryl iodides, including structures with potentially chelating 2-substituents that are commonly encountered in hypervalent iodine reagents. Finally, potential decomposition processes relevant to the (in)stability of iodanyl radicals are presented. We anticipate that the collected data will advance the design and application of aryl iodide electrocatalysis.

The most common linkers in bioactive molecules and their bioisosteric replacement network

Structures of the large majority of bioactive molecules are composed of several rings that are decorated by substituents and connected by linkers. While numerous cheminformatics studies focusing on rings and substituents are available, practically nothing has been published about the third important structural constituent of bioactive molecules - the linkers. The current study attempts to fill this gap. The most common linkers present in bioactive molecules are identified, their properties analyzed and a method for linker similarity search introduced. The bioisosteric replacement network of linkers is generated based on a large corpus of structure–activity data from medicinal chemistry literature. The results are presented in a graphical form and the underlying data are also made available for download. This analysis is intended to help medicinal chemists to better understand the role of linkers, particularly heterocyclic rings in bioactive molecules and to select an optimal set of linkers in their future project.