540 Chemie und zugeordnete Wissenschaften
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In integrative structural biology/hybrid modeling approaches, we integrate structural models of macromolecules and experimental data to obtain faithful representations of the structures underlying the data. For example, in ensemble refinement by reweighting we first generate structural ensembles of flexible and dynamic biological macromolecules in molecular simulations. In a subsequent reweighting step, we refine the statistical weights of the structures to strike a balance between the information provided by simulations and by experimental data. For the "Bayesian inference of ensembles" approach (BioEn), we present two complementary methods to solve the underlying challenging high-dimensional optimization problem. We systematically investigate reliability, accuracy, and efficiency of these methods and integrate molecular dynamics simulations of the disordered peptide Ala-5 and NMR J-couplings. We provide an open-source library free of charge at https://github.com/bio-phys/BioEn.
In integrative structural biology/hybrid modeling approaches, we integrate structural models of macromolecules and experimental data to obtain faithful representations of the structures underlying the data. For example, in ensemble refinement by reweighting we first generate structural ensembles of flexible and dynamic biological macromolecules in molecular simulations. In a subsequent reweighting step, we refine the statistical weights of the structures to strike a balance between the information provided by simulations and by experimental data. For the "Bayesian inference of ensembles" approach (BioEn), we present two complementary methods to solve the underlying challenging high-dimensional optimization problem. We systematically investigate reliability, accuracy, and efficiency of these methods and integrate molecular dynamics simulations of the disordered peptide Ala-5 and NMR J-couplings. We provide an open-source library free of charge at https://github.com/bio-phys/BioEn.
Light-driven sodium pumps (NaRs) are unique ion-transporting microbial rhodopsins. The major group of NaRs is characterized by an NDQ motif and has two aspartic acid residues in the central region essential for sodium transport. Here we identified a new subgroup of the NDQ rhodopsins bearing an additional glutamic acid residue in the close vicinity to the retinal Schiff base. We thoroughly characterized a member of this subgroup, namely the protein ErNaR from Erythrobacter sp. HL-111 and showed that the additional glutamic acid results in almost complete loss of pH sensitivity for sodium-pumping activity, which is in contrast to previously studied NaRs. ErNaR is capable of transporting sodium efficiently even at acidic pH levels. X-ray crystallography and single particle cryo-electron microscopy reveal that the additional glutamic acid residue mediates the connection between the other two Schiff base counterions and strongly interacts with the aspartic acid of the characteristic NDQ motif. Hence, it reduces its pKa. Our findings shed light on a new subgroup of NaRs and might serve as a basis for their rational optimization for optogenetics.
Isothermal titration calorimetry (ITC) is a widely used technique for the characterization of protein-protein and protein-ligand interactions. It provides information on the stoichiometry, affinity, and the thermodynamic driving forces of interactions. This chapter exemplifies the use of ITC to investigate interactions between human autophagy modifiers (LC3/GABARAP proteins) and their interaction partners, the LIR motif containing sequences. The purpose of this report is to present a detailed protocol for the production of LC3/GABARAP-interacting LIR peptides using E. coli expression systems. In addition, we outline the design of ITC experiments using the LC3/GABARAP:peptide interactions as an example. Comprehensive troubleshooting notes are provided to facilitate the adaptation of these protocols to different ligand-receptor systems. The methodology outlined for studying protein-ligand interactions will help to avoid common errors and misinterpretations of experimental results.
Although iron-based catalysts are regarded as a promising alternative to precious metal catalysts, their precise electronic structures during catalysis still pose challenges for computational descriptions. A particularly urgent question is the influence of the environment on the electronic structure, and how to describe this properly with computational methods. Here, we study an iron porphyrin chloride complex adsorbed on a graphene sheet using density functional theory calculations to detail how much the electronic structure is influenced by the presence of a graphene layer. Our results indicate that weak interactions due to van der Waals forces dominate between the porphyrin complex and graphene, and only a small amount of charge is transferred between the two entities. Furthermore, the interplay of the ligand field environment, strong p − d hybridization, and correlation effects within the complex are strongly involved in determining the spin state of the iron ion. By bridging molecular chemistry and solid state physics, this study provides first steps towards a joint analysis of the properties of iron-based catalysts from first principles.
Bleaching-independent, whole-cell, 3D and multi-color STED imaging with exchangeable fluorophores
(2018)
We demonstrate bleaching-independent STED microscopy using fluorogenic labels that reversibly bind to their target structure. A constant exchange of labels guarantees the removal of photobleached fluorophores and their replacement by intact fluorophores, thereby circumventing bleaching-related limitations of STED super-resolution imaging in fixed and living cells. Foremost, we achieve a constant labeling density and demonstrate a fluorescence signal for long and theoretically unlimited acquisition times. Using this concept, we demonstrate whole-cell, 3D, multi-color and live cell STED microscopy with up to 100 min acquisition time.
Single-particle electron cryo-microscopy (cryoEM) has undergone a “resolution revolution” that makes it possible to characterize megadalton (MDa) complexes at atomic resolution without crystals. To fully exploit the new opportunities in molecular microscopy, new procedures for the cloning, expression and purification of macromolecular complexes need to be explored. Macromolecular assemblies are often unstable, and invasive construct design or inadequate purification conditions or sample preparation methods can result in disassembly or denaturation. The structure of the 2.6 MDa yeast fatty acid synthase (FAS) has been studied by electron microscopy since the 1960s. We report a new, streamlined protocol for the rapid production of purified yeast FAS for structure determination by high-resolution cryoEM. Together with a companion protocol for preparing cryoEM specimens on a hydrophilized graphene layer, our new protocol has yielded a 3.1 Å map of yeast FAS from 15,000 automatically picked particles within a day. The high map quality enabled us to build a complete atomic model of an intact fungal FAS.
Engineering of assembly line polyketide synthases (PKSs) to produce novel bioactive compounds has been a goal for over twenty years. The apparent modularity of PKSs has inspired many engineering attempts in which entire modules or single domains were exchanged. In recent years, it has become evident that certain domain-domain interactions are evolutionarily optimized, and if disrupted, cause a decrease of the overall turnover rate of the chimeric PKS. In this study, we compared different types of chimeric PKSs in order to define the least invasive interface and to expand the toolbox for PKS engineering. We generated bimodular chimeric PKSs in which entire modules were exchanged, while either retaining a covalent linker between heterologous modules or introducing a non-covalent docking domain- or SYNZIP domain-mediated interface. These chimeric systems exhibited non-native domain-domain interactions during intermodular polyketide chain translocation. They were compared to otherwise equivalent bimodular PKSs in which a non-covalent interface was introduced between the condensing and processing parts of a module, resulting in non-native domain interactions during the extender unit acylation and polyketide chain elongation steps of their catalytic cycles. We show that the natural PKS docking domains can be efficiently substituted with SYNZIP domains and that the newly introduced non-covalent interface between the condensing and processing parts of a module can be harnessed for PKS engineering. Additionally, we established SYNZIP domains as a new tool for engineering PKSs by efficiently bridging non-native interfaces without perturbing PKS activity.
Modular polyketide synthases (PKSs) produce complex, bioactive secondary metabolites in assembly line-like multistep reactions. Longstanding efforts to produce novel, biologically active compounds by recombining intact modules to new modular PKSs have mostly resulted in poorly active chimeras and decreased product yields. Recent findings demonstrate that the low efficiencies of modular chimeric PKSs also result from rate limitations in the transfer of the growing polyketide chain across the non-cognate module:module interface and further processing of the non-native polyketide substrate by the ketosynthase (KS) domain. In this study, we aim at disclosing and understanding the low efficiency of chimeric modular PKSs and at establishing guidelines for modular PKSs engineering. To do so, we work with a bimodular PKS testbed and systematically vary substrate specificity, substrate identity, and domain:domain interfaces of the KS involved reactions. We observe that KS domains employed in our chimeric bimodular PKSs are bottlenecks with regards to both substrate specificity as well as interaction with the ACP. Overall, our systematic study can explain in quantitative terms why early oversimplified engineering strategies based on the plain shuffling of modules mostly failed and why more recent approaches show improved success rates. We moreover identify two mutations of the KS domain that significantly increased turnover rates in chimeric systems and interpret this finding in mechanistic detail.
Introduction: In the development of bio-enabling formulations, innovative in vivo predictive tools to understand and predict the in vivo performance of such formulations are needed. Etravirine, a non-nucleoside reverse transcriptase inhibitor, is currently marketed as an amorphous solid dispersion (Intelence® tablets). The aims of this study were 1) to investigate and discuss the advantages of using biorelevant in vitro setups in simulating the in vivo performance of Intelence® 100 mg and 200 mg tablets, in the fed state, 2) to build a Physiologically Based Pharmacokinetic (PBPK) model by combining experimental data and literature information with the commercially available in silico software Simcyp® Simulator V17.1 (Certara UK Ltd.), and 3) to discuss the challenges when predicting the in vivo performance of an amorphous solid dispersion and identify the parameters which influence the pharmacokinetics of etravirine most.
Methods: Solubility, dissolution and transfer experiments were performed in various biorelevant media simulating the fasted and fed state environment in the gastrointestinal tract. An in silico PBPK model for healthy volunteers was developed in the Simcyp® Simulator, using in vitro results and data available from the literature as input. The impact of pre- and post-absorptive parameters on the pharmacokinetics of etravirine was investigated using simulations of various scenarios.
Results: In vitro experiments indicated a large effect of naturally occurring solubilizing agents on the solubility of etravirine. Interestingly, supersaturated concentrations of etravirine were observed over the entire duration of dissolution experiments on Intelence® tablets. Coupling the in vitro results with the PBPK model provided the opportunity to investigate two possible absorption scenarios, i.e. with or without implementation of precipitation. The results from the simulations suggested that a scenario in which etravirine does not precipitate is more representative of the in vivo data. On the post-absorptive side, it appears that the concentration dependency of the unbound fraction of etravirine in plasma has a significant effect on etravirine pharmacokinetics.
Conclusions: The present study underlines the importance of combining in vitro and in silico biopharmaceutical tools to advance our knowledge in the field of bio-enabling formulations. Future studies on other bio-enabling formulations can be used to further explore this approach to support rational formulation design as well as robust prediction of clinical outcomes.
Purpose: The design of biorelevant conditions for in vitro evaluation of orally administered drug products is contingent on obtaining accurate values for physiologically relevant parameters such as pH, buffer capacity and bile salt concentrations in upper gastrointestinal fluids.
Methods: The impact of sample handling on the measurement of pH and buffer capacity of aspirates from the upper gastrointestinal tract was evaluated, with a focus on centrifugation and freeze-thaw cycling as factors that can influence results. Since bicarbonate is a key buffer system in the fasted state and is used to represent conditions in the upper intestine in vitro, variations on sample handling were also investigated for bicarbonate-based buffers prepared in the laboratory.
Results: Centrifugation and freezing significantly increase pH and decrease buffer capacity in samples obtained by aspiration from the upper gastrointestinal tract in the fasted state and in bicarbonate buffers prepared in vitro. Comparison of data suggested that the buffer system in the small intestine does not derive exclusively from bicarbonates.
Conclusions: Measurement of both pH and buffer capacity immediately after aspiration are strongly recommended as “best practice” and should be adopted as the standard procedure for measuring pH and buffer capacity in aspirates from the gastrointestinal tract. Only data obtained in this way provide a valid basis for setting the physiological parameters in physiologically based pharmacokinetic models.
Objectives Supersaturating formulations hold great promise for delivery of poorly soluble active pharmaceutical ingredients (APIs). To profit from supersaturating formulations, precipitation is hindered with precipitation inhibitors (PIs), maintaining drug concentrations for as long as possible. This review provides a brief overview of supersaturation and precipitation, focusing on precipitation inhibition. Trial-and-error PI selection will be examined alongside established PI screening techniques. Primarily, however, this review will focus on recent advances that utilise advanced analytical techniques to increase mechanistic understanding of PI action and systematic PI selection.
Key Findings. Advances in mechanistic understanding have been made possible by the use of analytical tools such as spectroscopy, microscopy and mathematical and molecular modelling, which have been reviewed herein. Using these techniques, PI selection can instead be guided by molecular rationale. However, more work is required to see wide-spread application of such an approach for PI selection.
Conclusions PIs are becoming increasingly important in enabling formulations. Trial-and-error approaches have seen success thus far. However, it is essential to learn more about the mode of action of PIs if the most optimal formulations are to be realised. Robust analytical tools, and the knowledge of where and how they can be applied, will be essential in this endeavour.
Supersaturating formulations are widely used to improve the oral bioavailability of poorly soluble drugs. However, supersaturated solutions are thermodynamically unstable and such formulations often must include a precipitation inhibitor (PI) to sustain the increased concentrations to ensure that sufficient absorption will take place from the gastrointestinal tract. Recent advances in understanding the importance of drug-polymer interaction for successful precipitation inhibition have been encouraging. However, there still exists a gap in how this newfound understanding can be applied to improve the efficiency of PI screening and selection, which is still largely carried out with trial and error-based approaches. The aim of this study was to demonstrate how drug-polymer mixing enthalpy, calculated with the Conductor like Screening Model for Real Solvents (COSMO-RS), can be used as a parameter to select the most efficient precipitation inhibitors, and thus realise the most successful supersaturating formulations. This approach was tested for three different Biopharmaceutical Classification System (BCS) II compounds: dipyridamole, fenofibrate and glibenclamide, formulated with the supersaturating formulation, mesoporous silica. For all three compounds, precipitation was evident in mesoporous silica formulations without a precipitation inhibitor. Of the nine precipitation inhibitors studied, there was a strong positive correlation between the drug-polymer mixing enthalpy and the overall formulation performance, as measured by the area under the concentration-time curve in in vitro dissolution experiments. The data suggest that a rank-order based approach using calculated drug-polymer mixing enthalpy can be reliably used to select precipitation inhibitors for a more focused screening. Such an approach improves efficiency of precipitation inhibitor selection, whilst also improving the likelihood that the most optimal formulation will be realised.
Objectives: The objective of this review is to provide an overview of PK/PD models, focusing on drug-specific PK/PD models and highlighting their value-added in drug development and regulatory decision-making.
Key findings: Many PK/PD models, with varying degrees of complexity and physiological understanding, have been developed to evaluate the safety and efficacy of drug products. In special populations (e.g. pediatrics), in cases where there is genetic polymorphism and in other instances where therapeutic outcomes are not well described solely by PK metrics, the implementation of PK/PD models is crucial to assure the desired clinical outcome. Since dissociation between the pharmacokinetic and pharmacodynamic profiles is often observed, it is proposed that physiologically-based pharmacokinetic (PBPK) and PK/PD models be given more weight by regulatory authorities when assessing the therapeutic equivalence of drug products.
Summary: Modeling and simulation approaches already play an important role in drug development. While slowly moving away from “one-size fits all” PK methodologies to assess therapeutic outcomes, further work is required to increase confidence in PK/PD models in translatability and prediction of various clinical scenarios to encourage more widespread implementation in regulatory decision-making.