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Macrocyclization of acyclic compounds is a powerful strategy for improving inhibitor potency and selectivity. Here we have optimized 2-aminopyrimidine-based macrocycles to use these compounds as chemical tools for the ephrin kinase family. Starting with a promiscuous macrocyclic inhibitor, 6, we performed a structure-guided activity relationship and selectivity study using a panel of over 100 kinases. The crystal structure of EPHA2 in complex with the developed macrocycle 23provided a basis for further optimization by specifically targeting the back pocket, resulting in compound 55, a potent inhibitor of EPHA2/A4 and GAK. Subsequent front-pocket derivatization resulted in an interesting in celluloselectivity profile, favoring EPHA4 over the other ephrin receptor kinase family members. The dual EPHA2/A4 and GAK inhibitor 55prevented dengue virus infection of Huh7 liver cells. However, further investigations are needed to determine whether this was a compound-specific effect or target-related.

The pyrazolo[1,5-a]pyrimidine scaffold is a promising scaffold to develop potent and selective CSNK2 inhibitors with antiviral activity against β-coronaviruses. Herein, we describe the discovery of a 1,2,4-triazole group to substitute a key amide group for CSNK2 binding present in many potent pyrazolo[1,5-a]pyrimidine inhibitors. Crystallographic evidence demonstrates that the 1,2,4-triazole replaces the amide in forming key hydrogen bonds with Lys68 and a water molecule buried in the ATP-binding pocket. This isosteric replacement improves potency and metabolic stability at a cost of solubility. Optimization for potency, solubility, and metabolic stability led to the discovery of the potent and selective CSNK2 inhibitor 53. Despite excellent in vitro metabolic stability, rapid decline in plasma concentration of 53in vivo was observed and may be attributed to lung accumulation, although in vivo pharmacological effect was not observed. Further optimization of this novel chemotype may validate CSNK2 as an antiviral target in vivo.

TRIM7 is a ubiquitin E3 ligase with key regulatory functions, mediating viral infection, tumor biology, innate immunity, and cellular processes, such as autophagy and ferroptosis. It contains a PRYSPRY domain that specifically recognizes degron sequences containing C-terminal glutamine. Ligands that bind to the TRIM7 PRYSPRY domain may have applications in the treatment of viral infections, as modulators of inflammation, and in the design of a new class of PROTACs (PROteolysis TArgeting Chimeras) that mediate the selective degradation of therapeutically relevant proteins (POIs). Here, we developed an assay toolbox for the comprehensive evaluation of TRIM7 ligands. Using TRIM7 degron sequences together with a structure-based design, we developed the first series of peptidomimetic ligands with low micromolar affinity. The terminal carboxylate moiety was required for ligand activity but prevented cell penetration. A prodrug strategy using an ethyl ester resulted in enhanced permeability, which was evaluated using confocal imaging.

Mammalian STE20-like (MST) kinases 1–4 play key roles in regulating the Hippo and autophagy pathways, and their dysregulation has been implicated in cancer development. In contrast to the well-studied MST1/2, the roles of MST3/4 are less clear, in part due to the lack of potent and selective inhibitors. Here, we re-evaluated literature compounds, and used structure-guided design to optimize the p21-activated kinase (PAK) inhibitor G-5555 (8) to selectively target MST3/4. These efforts resulted in the development of MR24 (24) and MR30 (27) with good kinome-wide selectivity and high cellular potency. The distinct cellular functions of closely related MST kinases can now be elucidated with subfamily-selective chemical tool compounds using a combination of the MST1/2 inhibitor PF-06447475 (2) and the two MST3/4 inhibitors developed. We found that MST3/4-selective inhibition caused a cell-cycle arrest in the G1 phase, whereas MST1/2 inhibition resulted in accumulation of cells in the G2/M phase.

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features in simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations with only a modest increase in cost.

Leucettinibs are substituted 2-aminoimidazolin-4-ones (inspired by the marine sponge natural product Leucettamine B) developed as pharmacological inhibitors of DYRK1A (dual-specificity, tyrosine phosphorylation-regulated kinase 1A), a therapeutic target for indications such as Down syndrome and Alzheimer’s disease. Leucettinib-21 was selected as a drug candidate following extensive structure/activity studies and multiparametric evaluations. We here report its physicochemical properties (X-ray powder diffraction, differential scanning calorimetry, stability, solubility, crystal structure) and drug-like profile. Leucettinib-21’s selectivity (analyzed by radiometric, fluorescence, interaction, thermal shift, residence time assays) reveals DYRK1A as the first target but also some “off-targets” which may contribute to the drug’s biological effects. Leucettinib-21 was cocrystallized with CLK1 and modeled in the DYRK1A structure. Leucettinib-21 inhibits DYRK1A in cells (demonstrated by direct catalytic activity and phosphorylation levels of Thr286-cyclin D1 or Thr212-Tau). Leucettinib-21 corrects memory disorders in the Down syndrome mouse model Ts65Dn and is now entering safety/tolerance phase 1 clinical trials.

Dual-specificity, tyrosine phosphorylation-regulated kinases (DYRKs) and cdc2-like kinases (CLKs) recently attracted attention due to their central involvement in various pathologies. We here describe a family of DYRK/CLK inhibitors derived from Leucettines and the marine natural product Leucettamine B. Forty-five N2-functionalized 2-aminoimidazolin-4-ones bearing a fused [6 + 5]-heteroarylmethylene were synthesized. Benzothiazol-6-ylmethylene was selected as the most potent residue among 15 different heteroarylmethylenes. 186 N2-substituted 2-aminoimidazolin-4-ones bearing a benzothiazol-6-ylmethylene, collectively named Leucettinibs, were synthesized and extensively characterized. Subnanomolar IC50(0.5–20 nM on DYRK1A) inhibitors were identified and one Leucettinib was modeled in DYRK1A and co-crystallized with CLK1 and the weaker inhibited off-target CSNK2A1. Kinase-inactive isomers of Leucettinibs (>3–10 μM on DYRK1A), named iso-Leucettinibs, were synthesized and characterized as suitable negative control compounds for functional experiments. Leucettinibs, but not iso-Leucettinibs, inhibit the phosphorylation of DYRK1A substrates in cells. Leucettinibs provide new research tools and potential leads for further optimization toward therapeutic drug candidates.

Well-characterized small molecules are essential tools for studying the biology and therapeutic relevance of a target protein. However, many compounds reported in the literature and routinely studied in biomedical research lack the potency and selectivity required for mechanistic cellular studies on the function of a given protein. Furthermore, commercially available compounds often do not include useful tools developed by industry as part of their research and development efforts, as they frequently remain proprietary. The freely available donated chemical probe (DCP) library, fueled by generous donations of compounds from industry and academia, enables easy access to a steadily growing collection of these valuable and well-characterized tools. Here, we provide a systematic description of the current DCP library collection and their associated comprehensive characterization data, including a variety of in vitroand cellular assays. Of note, we characterized the set in relevant human primary models by employing hepatotoxicity screening in primary human liver spheroids and viability screening in patient-derived colorectal cancer organoids and matched normal-adjacent epithelium. Taken together, the DCP library represents a well-annotated, openly available collection of tool compounds for studying a wide range of targets, including kinases, G-protein-coupled receptors, and ion channels. As such, it represents a unique resource for the biomedical research community.

The dynamics of molecules are governed by rare event transitions between long-lived (metastable) states. To explore these transitions efficiently, many enhanced sampling protocols have been introduced that involve using simulations with biases or changed temperatures. Two established statistically optimal estimators for obtaining unbiased equilibrium properties from such simulations are the multistate Bennett acceptance ratio (MBAR) and the transition-based reweighting analysis method (TRAM). Both MBAR and TRAM are solved iteratively and can suffer from long convergence times. Here, we introduce stochastic approximators (SA) for both estimators, resulting in SAMBAR and SATRAM, which are shown to converge faster than their deterministic counterparts, without significant accuracy loss. Both methods are demonstrated on different molecular systems.

Activating mutations in the epidermal growth factor receptor (EGFR) are frequent oncogenic drivers of non-small-cell lung cancer (NSCLC). The most frequent alterations in EGFR are short in-frame deletions in exon 19 (Del19) and the missense mutation L858R, which both lead to increased activity and sensitization of NSCLC to EGFR inhibition. The first approved EGFR inhibitors used for first-line treatment of NSCLC, gefitinib and erlotinib, are quinazoline-based. However, both inhibitors have several known off-targets, and they also potently inhibit wild-type (WT) EGFR, resulting in side effects. Here, we applied a macrocyclic strategy on a quinazoline-based scaffold as a proof-of-concept study with the goal of increasing kinome-wide selectivity of this privileged inhibitor scaffold. Kinome-wide screens and SAR studies yielded 3f, a potent inhibitor for the most common EGFR mutation (EGFR Del19: 119 nM) with selectivity against the WT receptor (EGFR: >10 μM) and the kinome.

Serine/threonine kinase 17A (death-associated protein kinase-related apoptosis-inducing protein kinase 1─DRAK1) is a part of the death-associated protein kinase (DAPK) family and belongs to the so-called dark kinome. Thus, the current state of knowledge of the cellular function of DRAK1 and its involvement in pathophysiological processes is very limited. Recently, DRAK1 has been implicated in tumorigenesis of glioblastoma multiforme (GBM) and other cancers, but no selective inhibitors of DRAK1 are available yet. To this end, we optimized a pyrazolo[1,5-a]pyrimidine-based macrocyclic scaffold. Structure-guided optimization of this macrocyclic scaffold led to the development of CK156 (34), which displayed high in vitro potency (KD= 21 nM) and selectivity in kinomewide screens. Crystal structures demonstrated that CK156 (34) acts as a type I inhibitor. However, contrary to studies using genetic knockdown of DRAK1, we have seen the inhibition of cell growth of glioma cells in 2D and 3D culture only at low micromolar concentrations.

Molecular dynamics simulations provide a mechanistic description of molecules by relying on empirical potentials. The quality and transferability of such potentials can be improved leveraging data-driven models derived with machine learning approaches. Here, we present TorchMD, a framework for molecular simulations with mixed classical and machine learning potentials. All force computations including bond, angle, dihedral, Lennard-Jones, and Coulomb interactions are expressed as PyTorch arrays and operations. Moreover, TorchMD enables learning and simulating neural network potentials. We validate it using standard Amber all-atom simulations, learning an ab initio potential, performing an end-to-end training, and finally learning and simulating a coarse-grained model for protein folding. We believe that TorchMD provides a useful tool set to support molecular simulations of machine learning potentials. Code and data are freely available at github.com/torchmd.

Long-range Lennard-Jones (LJ) interactions have been incorporated into the CHARMM36 (C36) lipid force field (FF) using the LJ particle-mesh Ewald (LJ-PME) method in order to remove the inconsistency of bilayer and monolayer properties arising from the exclusion of long-range dispersion [Yu, Y.; Semi-automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion. J. Chem. Theory Comput.2021, 10.1021/acs.jctc.0c01326.(preceding article in this issue)]. The new FF is denoted C36/LJ-PME. While the first optimization was based on three phosphatidylcholines (PCs), this work extends the validation and parametrization to more lipids including PC, phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and ether lipids. The agreement with experimental structure data is excellent for PC, PE, and ether lipids. C36/LJ-PME also compares favorably with scattering data of PG bilayers but less so with NMR deuterium order parameters of 1,2-dimyristoyl-sn-glycero-3-phospho-(1′-rac-glycerol) (DMPG) at 303.15 K, indicating a need for future optimization regarding PG-specific parameters. Frequency dependence of NMR T1spin–lattice relaxation times is well-described by C36/LJ-PME, and the overall agreement with experiment is comparable to C36. Lipid diffusion is slower than C36 due to the added long-range dispersion causing a higher viscosity, although it is still too fast compared to experiment after correction for periodic boundary conditions. When using a 10 Å real-space cutoff, the simulation speed of C36/LJ-PME is roughly equal to C36. While more lipids will be incorporated into the FF in the future, C36/LJ-PME can be readily used for common lipids and extends the capability of the CHARMM FF by supporting monolayers and eliminating the cutoff dependence.

The development of the CHARMM lipid force field (FF) can be traced back to the early 1990s with its current version denoted CHARMM36 (C36). The parametrization of C36 utilized high-level quantum mechanical data and free energy calculations of model compounds before parameters were manually adjusted to yield agreement with experimental properties of lipid bilayers. While such manual fine-tuning of FF parameters is based on intuition and trial-and-error, automated methods can identify beneficial modifications of the parameters via their sensitivities and thereby guide the optimization process. This work introduces a semi-automated approach to reparametrize the CHARMM lipid FF with consistent inclusion of long-range dispersion through the Lennard-Jones particle-mesh Ewald (LJ-PME) approach. The optimization method is based on thermodynamic reweighting with regularization with respect to the C36 set. Two independent optimizations with different topology restrictions are presented. Targets of the optimizations are primarily liquid crystalline phase properties of lipid bilayers and the compression isotherm of monolayers. Pair correlation functions between water and lipid functional groups in aqueous solution are also included to address headgroup hydration. While the physics of the reweighting strategy itself is well-understood, applying it to heterogeneous, complex anisotropic systems poses additional challenges. These were overcome through careful selection of target properties and reweighting settings allowing for the successful incorporation of the explicit treatment of long-range dispersion, and we denote the newly optimized lipid force field as C36/LJ-PME. The current implementation of the optimization protocol will facilitate the future development of the CHARMM and related lipid force fields.

AbstractContinuous compression moulding (CCM) is an efficient process for manufacturing endless fibre-reinforced thermoplastic composites, so called organic sheets. The semi-finished products are fully impregnated and consolidated and can be thermoformed into complex 3D-geometries. Applications benefit from excellent weight-specific features as well as functional integration. Nevertheless, limited production speed and lower than acceptable manufacturing quality are still a challenge, especially with the use of high shrinkage polymers. Hence, porosities and defects due to pressure drops inside the laminate during impregnation and solidification can cause degradation in material properties. With the integration of an active adaptive pressing tool and an inline pressure measurement system, the process can be optimised towards guided impregnation and improved pressure distribution. A calculation method based on the B-factor method by Mayer has been adapted for the CCM process in order to enhance the tool design. Both, production speed as well as organic sheet quality can be improved with the optimised processing system presented in the following work.

Several simulations strategies have emerged to predict the permeability of solutes across membranes, which is important for many biological or industrial processes such as drug design. The widespread inhomogeneous solubility-diffusion (ISD) model is based on the Smoluchowski equation and describes permeation as purely diffusive. The counting method, which counts membrane transitions in a long molecular dynamics (MD) trajectory, is free of this diffusive assumption, but it lacks sufficient statistics when the permeation involves high free energy barriers. Metadynamics and variations thereof can overcome such barriers, but they generally lack the kinetics information. The milestoning framework has been used to describe permeation as a rare event, but it still relies on the Markovian assumption between the milestones. Replica Exchange Transition Interface Sampling (RETIS) has been shown to be an effective method for sampling rare events while simultaneously describing the kinetics without assumptions. This paper is the first permeation application of RETIS on an all-atom lipid bilayer consisting of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) to compute the entrance, escape and complete transition of molecular oxygen. Conventional MD was performed as a benchmark, and the MD rates from counting were converted to rate constants, giving good agreement with the RETIS values. Moreover, a correction factor was derived to convert the collective order parameter in RETIS, which was aimed to improve efficiency, to a single-particle order parameter. With this work, we showed how the exact kinetics of drug molecules permeation can be assessed with RETIS even if the permeation is truly a rare event or if the permeation is non-Markovian. RETIS will therefore be a valuable tool for future permeation studies.

Multi-subunit ATPase-dependent chromatin remodelling complexes SWI/SNF (switch/sucrose non-fermentable) are fundamental epigenetic regulators of gene transcription. Functional genomic studies revealed a remarkable mutation prevalence of SWI/SNF-encoding genes in 20–25% of all human cancers, frequently driving oncogenic programmes. Some SWI/SNF-mutant cancers are hypersensitive to perturbations in other SWI/SNF subunits, regulatory proteins and distinct biological pathways, often resulting in sustained anticancer effects and synthetic lethal interactions. Exploiting these vulnerabilities is a promising therapeutic strategy. Here, we review the importance of SWI/SNF chromatin remodellers in gene regulation as well as mechanisms leading to assembly defects and their role in cancer development. We will focus in particular on emerging strategies for the targeted therapy of SWI/SNF-deficient cancers using chemical probes, including proteolysis targeting chimeras, to induce synthetic lethality.

Accessibility of the human genome is modulated by the ATP-driven SWI/SNF chromatin remodeling multiprotein complexes BAF (BRG1/BRM-associated factor) and PBAF (polybromo-associated BAF factor), which involves reading of acetylated histone tails by the bromodomain-containing proteins SMARCA2 (BRM), SMARCA4 (BRG1), and polybromo-1. Dysregulation of chromatin remodeling leads to aberrant cell proliferation and differentiation. Here, we have characterized a set of potent and cell-active bromodomain inhibitors with pan-selectivity for canonical family VIII bromodomains. Targeted SWI/SNF bromodomain inhibition blocked the expression of key genes during adipogenesis, including the transcription factors PPARγ and C/EBPα, and impaired the differentiation of 3T3-L1 murine fibroblasts into adipocytes. Our data highlight the role of SWI/SNF bromodomains in adipogenesis and provide a framework for the development of SWI/SNF bromodomain inhibitors for indirect targeting of key transcription factors regulating cell differentiation.

The NUDIX hydrolase NUDT15 was originally implicated in sanitizing oxidized nucleotides, but was later shown to hydrolyze the active thiopurine metabolites, 6-thio-(d)GTP, thereby dictating the clinical response of this standard-of-care treatment for leukemia and inflammatory diseases. Nonetheless, its physiological roles remain elusive. Here, we sought to develop small-molecule NUDT15 inhibitors to elucidate its biological functions and potentially to improve NUDT15-dependent chemotherapeutics. Lead compound TH1760 demonstrated low-nanomolar biochemical potency through direct and specific binding into the NUDT15 catalytic pocket and engaged cellular NUDT15 in the low-micromolar range. We also employed thiopurine potentiation as a proxy functional readout and demonstrated that TH1760 sensitized cells to 6-thioguanine through enhanced accumulation of 6-thio-(d)GTP in nucleic acids. A biochemically validated, inactive structural analog, TH7285, confirmed that increased thiopurine toxicity takes place via direct NUDT15 inhibition. In conclusion, TH1760 represents the first chemical probe for interrogating NUDT15 biology and potential therapeutic avenues.

We have previously shown that the thermolabile, cavity-creating p53 cancer mutant Y220C can be reactivated by small-molecule stabilizers. In our ongoing efforts to unearth druggable variants of the p53 mutome, we have now analyzed the effects of other cancer-associated mutations at codon 220 on the structure, stability, and dynamics of the p53 DNA-binding domain (DBD). We found that the oncogenic Y220H, Y220N, and Y220S mutations are also highly destabilizing, suggesting that they are largely unfolded under physiological conditions. A high-resolution crystal structure of the Y220S mutant DBD revealed a mutation-induced surface crevice similar to that of Y220C, whereas the corresponding pocket’s accessibility to small molecules was blocked in the structure of the Y220H mutant. Accordingly, a series of carbazole-based small molecules, designed for stabilizing the Y220C mutant, also bound to and stabilized the folded state of the Y220S mutant, albeit with varying affinities due to structural differences in the binding pocket of the two mutants. Some of the compounds also bound to and stabilized the Y220N mutant, but not the Y220H mutant. Our data validate the Y220S and Y220N mutants as druggable targets and provide a framework for the design of Y220S or Y220N-specific compounds as well as compounds with dual Y220C/Y220S specificity for use in personalized cancer therapy.

In direct-current control scheme, self-oscillations or limit cycles occur due to the hysteresis controller. In this contribution, the different types of self-oscillations in a three-level hysteresis current controlled H-bridge are analyzed. The investigations are based on Tsypkin’s method for self-oscillations in relay control systems. So, the conditions for the different types of self-oscillations are given and the frequency of the oscillation and the on-to-off-ratio or pulse width of the switching hysteresis output are calculated exactly. The values correspond to the switching frequency and the duty cycle of the H-bridge. Furthermore, some analyses about the transfer characteristic of the control loop are made.

Atomistic biomolecular simulations predominantly utilize additive force fields (FF), where the electrostatic potential is modeled by fixed point charges. Among other consequences, the lack of polarizability in these models undermines the balance of hydrophilic/hydrophobic nonbonded interactions. Simulations of water/alkane systems using the TIP3P water model and CHARMM36 parameters reveal a 1 kcal/mol overestimate of the experimental transfer free energy of water to hexadecane; more recent optimized water models (SPC/E, TIP4P/2005, TIP4P-Ew, TIP3P-FB, TIP4P-FB, OPC, TIP4P-D) overestimate this transfer free energy by approximately 2 kcal/mol. In contrast, the polarizable SWM4-NDP and SWM6 water models reproduce experimental values to within statistical error. As an alternative to explicitly modeling polarizability, this paper develops an efficient automated workflow to optimize pair-specific Lennard-Jones parameters within an additive FF. Water/hexadecane is used as a prototype and the free energy of water transfer to hexadecane as a target. The optimized model yields quantitative agreement with the experimental transfer free energy and improves the water/hexadecane interfacial tension by 6%. Simulations of five different lipid bilayers show a strong increase of water permeabilities compared to the unmodified CHARMM36 lipid FF which consistently improves match with experiment: the order-of-magnitude underestimate for monounsaturated bilayers is rectified and the factor of 2.8–4 underestimate for saturated bilayers is turned into a factor of 1.5–3 overestimate. While agreement with experiment is decreased for the diffusion constant of water in hexadecane, alkane transfer free energies, and the bilayers’ area per lipid, the method provides a permeant-specific route to achieve a wide range of heterogeneous observables via rapidly optimized pairwise parameters.

Car and bike sharing in Germany is characterized by considerable dynamics (new providers, more and more rental vehicles, increasing numbers of users) and is often seen as an integral part of achieving sustainable mobility. Against this background, the authors examine the user acceptance of car- and bikesharing, the potential use, the proximity to public transport and the effects on private car ownership on the basis of an empirical study. [ABSTRACT FROM AUTHOR]

The diesel emission scandal and the nitrogen dioxide problem in dozens major German cities led to a first partial ban on diesel vehicles in Hamburg. However, the search for solutions also focuses on public transport, e. g. in the form of offering a fare free public transport. Based on an empirical analysis the view of consumers in Germany, Austria and Switzerland is analyzed with regard to the various possible solutions. Finally, implications for further discussion are derived. [ABSTRACT FROM AUTHOR]

MST1, MST2, MST3, MST4, and YSK1 are conserved members of the mammalian sterile 20-like serine/threonine (MST) family that regulate cellular functions such as proliferation and migration. The MST3 isozyme plays a role in regulating cell growth and apoptosis, and its dysregulation has been linked to high-grade tumors. To date, there are no isoform-selective inhibitors that could be used for validating the role of MST3 in tumorigenesis. We designed a series of 3-aminopyrazole-based macrocycles based on the structure of a promiscuous inhibitor. By varying the moieties targeting the solvent-exposed region and optimizing the linker, macrocycle JA310 (21c) was synthesized. JA310 exhibited high cellular potency for MST3 (EC50= 106 nM) and excellent kinome-wide selectivity. The crystal structure of the MST3–JA310 complex provided intriguing insights into the binding mode, which is associated with large-scale structural rearrangements. In summary, JA310 demonstrates the utility of macrocyclization for the design of highly selective inhibitors and presents the first chemical probe for MST3.

Coarse-grained (CG) molecular simulations have become a standard tool to study molecular processes on time and length scales inaccessible to all-atom simulations. Parametrizing CG force fields to match all-atom simulations has mainly relied on force-matching or relative entropy minimization, which require many samples from costly simulations with all-atom or CG resolutions, respectively. Here we present flow-matching, a new training method for CG force fields that combines the advantages of both methods by leveraging normalizing flows, a generative deep learning method. Flow-matching first trains a normalizing flow to represent the CG probability density, which is equivalent to minimizing the relative entropy without requiring iterative CG simulations. Subsequently, the flow generates samples and forces according to the learned distribution in order to train the desired CG free energy model via force-matching. Even without requiring forces from the all-atom simulations, flow-matching outperforms classical force-matching by an order of magnitude in terms of data efficiency and produces CG models that can capture the folding and unfolding transitions of small proteins.

Despite the recently growing interest in the acetylation of lysine residues by prokaryotic enzymes, the underlying biological function is still not well understood. Deacetylation is accomplished by proteins that belong to the histone deacetylase (HDAC) superfamily. In this report, we present the first crystal structure of PA3774, a histone deacetylase homologue from the human pathogen Pseudomonas aeruginosathat shares a high degree of homology with class IIb HDACs. We determined the crystal structure of the ligand-free enzyme and protein–ligand complexes with a trifluoromethylketone inhibitor and the reaction product acetate. Moreover, we produced loss of function mutants and determined the structure of the inhibitor-free PA3774H143Amutant, the inhibitor-free PA3774Y313Fmutant, and the PA3774Y313Fmutant in complex with the highly selective hydroxamate inhibitor PFSAHA. The overall structure reveals that the exceptionally long L1 loop mediates the formation of a tetramer composed of two “head-to-head” dimers. The distinctive dimer interface significantly confines the entrance area of the active site, suggesting a crucial role for substrate recognition and selectivity.

The mobilization of latent demand is one of the main challenges for marketing in public transport, if continuous increases in revenue and journeys are to be achieved. The paper presents a concept for the determination of potential public transport demand and applies this in an empirical analysis for the D-A-CH region. In addition, the drivers for the demand potential as well as the barriers to use the public transport are examined. [ABSTRACT FROM AUTHOR]

In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters’ influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task. [ABSTRACT FROM AUTHOR]

The highly conserved catalytic sites in protein kinases make it difficult to identify ATP competitive inhibitors with kinome-wide selectivity. Serendipitously, during a dedicated fragment campaign for the focal adhesion kinase (FAK), a scaffold that had lost its initial FAK affinity showed remarkable potency and selectivity for serine-arginine-protein kinases 1–3 (SRPK1–3). Non-conserved interactions with the uniquely structured hinge region of the SRPK family were the key drivers of the exclusive selectivity of the discovered fragment hit. Structure-guided medicinal chemistry efforts led to the SRPK inhibitor MSC-1186, which fulfills all hallmarks of a reversible chemical probe, including nanomolar cellular potency and excellent kinome-wide selectivity. The combination of MSC-1186with CDC2-like kinase (CLK) inhibitors showed additive attenuation of SR-protein phosphorylation compared to the single agents. MSC-1186and negative control (MSC-5360) are chemical probes available via the Structural Genomics Consortium chemical probe program (https://www.sgc-ffm.uni-frankfurt.de/).

3-Aminoindazoles are privileged scaffolds for bioactive drug-like molecules. In this study, a microwave-assisted cascade reaction for the synthesis of N-1 substituted 3-aminoindazoles with yields up to 81% has been developed. Starting from 3-(2-bromoaryl)-1,2,4-oxadiazol-5(4H)-ones, the reaction exhibits a broad substrate scope including anilines, aliphatic amines, and sulfonamides and bypasses selectivity issues between N-1 and 3-amino group. Furthermore, the Differential Scanning Fluorimetry screen of a kinase panel demonstrated the value of targeting N-1 substituted 3-aminoindazoles as kinase-biased fragments.

The new tridentate thioether ligands PhSi(CH2SMe)3(1) and Ph-p-C6H4Si(CH2SMe)3(2) have been synthesised and used for the preparation of the chelates fac-[W(κ3-1)(CO)3] and fac-[W(κ3-2)(CO)3], which were characterised by single-crystal X-ray diffraction. 1and 2were used as tripodal adsorbate molecules for the fabrication of self-assembled monolayers (SAMs) on gold. Film formation from solution was investigated in situby second harmonic generation (SHG) and ellipsometry, which revealed a two-stepped process (fast adsorption, followed by slow film ordering). SAMs of 2on gold were further investigated by ex situmethods, viz.high-resolution X-ray photoelectron spectroscopy (HRXPS), Fourier transform infrared reflection absorption spectroscopy (FTIRRAS), and scanning tunneling microscopy (STM). The latter two methods indicated dense packing of the tripodal anchor groups on the surface, with a substantially lower density of the biphenyl pricks. HRXPS showed three different binding states of sulfur, including a standard thiolate-type and a coordination-type state.

A three-dimensional field-based similarity search and alignment method for flexible molecules is introduced. The conformational space of a flexible molecule is represented in terms of fragments and torsional angles of allowed conformations. A user-definable property field is used to compute features of fragment pairs. Features are generalizations of CoMMA descriptors (Silverman, B.D. and Platt, D.E., J. Med. Chem., 39 (1996) 2129.) that characterize local regions of the property field by its local moments. The features are invariant under coordinate system transformations. Features taken from a query molecule are used to form alignments with fragment pairs in the database. An assembly algorithm is then used to merge the fragment pairs into full structures, aligned to the query. Key to the method is the use of a context adaptive descriptor scaling procedure as the basis for similarity. This allows the user to tune the weights of the various feature components based on examples relevant to the particular context under investigation. The property fields may range from simple, phenomenological fields, to fields derived from quantum mechanical calculations. We apply the method to the dihydrofolate/methotrexate benchmark system, and show that when one injects relevant contextual information into the descriptor scaling procedure, better results are obtained more efficiently. We also show how the method works and include computer times for a query from a database that represents approximately 23 million conformers of seventeen flexible molecules.

Branch and bound methods for the scheduling problem with multiprocessor tasks on dedicated processors and arbitrary precedences are presented. The methods are based on different representations of feasible schedules. Computational results show that the methods surpass each other on different types of problems with multiprocessor tasks.

Histone H3K4 methylation serves as a post-translational hallmark of actively transcribed genes and is introduced by histone methyltransferase (HMT) and its regulatory scaffolding proteins. One of these is the WD-repeat-containing protein 5 (WDR5) that has also been associated with controlling long noncoding RNAs and transcription factors including MYC. The wide influence of dysfunctional HMT complexes and the typically upregulated MYC levels in diverse tumor types suggested WDR5 as an attractive drug target. Indeed, protein–protein interface inhibitors for two protein interaction interfaces on WDR5 have been developed. While such compounds only inhibit a subset of WDR5 interactions, chemically induced proteasomal degradation of WDR5 might represent an elegant way to target all oncogenic functions. This study presents the design, synthesis, and evaluation of two diverse WDR5 degrader series based on two WIN site binding scaffolds and shows that linker nature and length strongly influence degradation efficacy.