Regulation of Zbp1 by miR-99b-5p in microglia controls the development of schizophrenia-like symptoms in mice.

Current approaches to the treatment of schizophrenia have mainly focused on the protein-coding part of the genome; in this context, the roles of microRNAs have received less attention. In the present study, we analyze the microRNAome in the blood and postmortem brains of schizophrenia patients, showing that the expression of miR-99b-5p is downregulated in both the prefrontal cortex and blood of patients. Lowering the amount of miR-99b-5p in mice leads to both schizophrenia-like phenotypes and inflammatory processes that are linked to synaptic pruning in microglia. The microglial miR-99b-5p-supressed inflammatory response requires Z-DNA binding protein 1 (Zbp1), which we identify as a novel miR-99b-5p target. Antisense oligonucleotides against Zbp1 ameliorate the pathological effects of miR-99b-5p inhibition. Our findings indicate that a novel miR-99b-5p-Zbp1 pathway in microglia might contribute to the pathogenesis of schizophrenia.

A Single-Cell Transcriptomic Analysis of the Mouse Hippocampus After Voluntary Exercise.

Exercise has been recognized as a beneficial factor for cognitive health, particularly in relation to the hippocampus, a vital brain region responsible for learning and memory. Previous research has demonstrated that exercise-mediated improvement of learning and memory in humans and rodents correlates with increased adult neurogenesis and processes related to enhanced synaptic plasticity. Nevertheless, the underlying molecular mechanisms are not fully understood. With the aim to further elucidate these mechanisms, we provide a comprehensive dataset of the mouse hippocampal transcriptome at the single-cell level after 4 weeks of voluntary wheel-running. Our analysis provides a number of interesting observations. For example, the results suggest that exercise affects adult neurogenesis by accelerating the maturation of a subpopulation of Prdm16-expressing neurons. Moreover, we uncover the existence of an intricate crosstalk among multiple vital signaling pathways such as NF-κB, Wnt/ß-catenin, Notch, and retinoic acid (RA) pathways altered upon exercise in a specific cluster of excitatory neurons within the Cornu Ammonis (CA) region of the hippocampus. In conclusion, our study provides an important resource dataset and sheds further light on the molecular changes induced by exercise in the hippocampus. These findings have implications for developing targeted interventions aimed at optimizing cognitive health and preventing age-related cognitive decline.

Correction to "Micelle Maker: An Online Tool for Generating Equilibrated Micelles as Direct Input for Molecular Dynamics Simulations".

[This corrects the article DOI: 10.1021/acsomega.7b00820.].

Exercise as a model to identify microRNAs linked to human cognition: a role for microRNA-409 and microRNA-501.

MicroRNAs have been linked to synaptic plasticity and memory function and are emerging as potential biomarkers and therapeutic targets for cognitive diseases. Most of these data stem from the analysis of model systems or postmortem tissue from patients which mainly represents an advanced stage of pathology. Due to the in-accessibility of human brain tissue upon experimental manipulation, it is still challenging to identify microRNAs relevant to human cognition, which is however a key step for future translational studies. Here, we employ exercise as an experimental model for memory enhancement in healthy humans with the aim to identify microRNAs linked to memory function. By analyzing the circulating smallRNAome we find a cluster of 18 microRNAs that are highly correlated to cognition. MicroRNA-409-5p and microRNA-501-3p were the most significantly regulated candidates. Functional analysis revealed that the two microRNAs are important for neuronal integrity, synaptic plasticity, and morphology. In conclusion, we provide a novel approach to identify microRNAs linked to human memory function.

Long Time-Scale Atomistic Simulations of the Structure and Dynamics of Transcription Factor-DNA Recognition.

Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse-grained and atomistic simulations of transcription factor-DNA recognition, to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs microsecond time scale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA and in the presence of both specific and nonspecific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and nonspecific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to nonspecific complexes), which may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.

Protein-RNA interactions: structural characteristics and hotspot amino acids.

Structural information about protein-RNA complexes supports the understanding of crucial recognition processes in the cell, and it can allow the development of high affinity ligands to interfere with these processes. In this respect, the identification of amino acid hotspots is particularly important. In contrast to protein-protein interactions, in silico approaches for protein-RNA interactions lag behind in their development. Herein, we report an analysis of available protein-RNA structures. We assembled a data set of 322 crystal and NMR structures and analyzed them regarding interface properties. In addition, we describe a computational alanine-scanning approach which provides interaction scores for interface amino acids, allowing the identification of potential hotspots in protein-RNA interfaces. We have made the computational approach available as an online tool, which allows interaction scores to be calculated for any structure of a protein-RNA complex by uploading atomic coordinates to the PRI HotScore web server (https://pri-hotscore.labs.vu.nl).

Amyloid-ß Peptide Interactions with Amphiphilic Surfactants: Electrostatic and Hydrophobic Effects.

The amphiphilic nature of the amyloid-ß (Aß) peptide associated with Alzheimer's disease facilitates various interactions with biomolecules such as lipids and proteins, with effects on both structure and toxicity of the peptide. Here, we investigate these peptide-amphiphile interactions by experimental and computational studies of Aß(1-40) in the presence of surfactants with varying physicochemical properties. Our findings indicate that electrostatic peptide-surfactant interactions are required for coclustering and structure induction in the peptide and that the strength of the interaction depends on the surfactant net charge. Both aggregation-prone peptide-rich coclusters and stable surfactant-rich coclusters can form. Only Aß(1-40) monomers, but not oligomers, are inserted into surfactant micelles in this surfactant-rich state. Surfactant headgroup charge is suggested to be important as electrostatic peptide-surfactant interactions on the micellar surface seems to be an initiating step toward insertion. Thus, no peptide insertion or change in peptide secondary structure is observed using a nonionic surfactant. The hydrophobic peptide-surfactant interactions instead stabilize the Aß monomer, possibly by preventing self-interaction between the peptide core and C-terminus, thereby effectively inhibiting the peptide aggregation process. These findings give increased understanding regarding the molecular driving forces for Aß aggregation and the peptide interaction with amphiphilic biomolecules.

Structure-Based Design of Non-natural Macrocyclic Peptides That Inhibit Protein-Protein Interactions.

Macrocyclic peptides can interfere with challenging biomolecular targets including protein-protein interactions. Whereas there are various approaches that facilitate the identification of peptide-derived ligands, their evolution into higher affinity binders remains a major hurdle. We report a virtual screen based on molecular docking that allows the affinity maturation of macrocyclic peptides taking non-natural amino acids into consideration. These macrocycles bear large and flexible substituents that usually complicate the use of docking approaches. A virtual library containing more than 1400 structures was screened against the target focusing on docking poses with the core structure resembling a known bioactive conformation. Based on this screen, a macrocyclic peptide 22 involving two non-natural amino acids was evolved showing increased target affinity and biological activity. Predicted binding modes were verified by X-ray crystallography. The presented workflow allows the screening of large macrocyclic peptides with diverse modifications thereby expanding the accessible chemical space and reducing synthetic efforts.

Micelle Maker: An Online Tool for Generating Equilibrated Micelles as Direct Input for Molecular Dynamics Simulations.

Micelles play an important role in both experimental and computational studies of the effect of lipid interactions on biological systems. The spherical geometry and the dynamical behavior of micelles makes generating micelle structures for use in molecular simulations challenging. An easy tool for generating simulation-ready micelle models, covering a broad range of lipids, is highly desirable. Here, we present a new Web server, Micelle Maker, which can provide equilibrated micelle models as a direct input for subsequent molecular dynamics simulations from a broad range of lipids (currently 25 lipid types, including 24 glycolipids). The Web server, which is available at http://www.micellemaker.net, uses error checking routines to prevent clashes during the initial placement of the lipids and uses AMBER's GLYCAM library for generating minimized or equilibrated micelle models, but the resulting structures can be used as starting points for simulations with any force field or simulation package. Extensive validation simulations with an overall simulation time of 12 µs using eight micelle models where assembly information is available show that all of the micelles remain very stable over the whole simulation time. Finally, we discuss the advantages of Micelle Maker relative to other approaches in the field.

Increased Conformational Flexibility of a Macrocycle-Receptor Complex Contributes to Reduced Dissociation Rates.

Constraining a peptide in its bioactive conformation by macrocyclization represents a powerful strategy to design modulators of challenging biomolecular targets. This holds particularly true for the development of inhibitors of protein-protein interactions which often involve interfaces lacking defined binding pockets. Such flat surfaces are demanding targets for traditional small molecules rendering macrocyclic peptides promising scaffolds for novel therapeutics. However, the contribution of peptide dynamics to binding kinetics is barely understood which impedes the design process. Herein, we report unexpected trends in the binding kinetics of two closely related macrocyclic peptides that bind their receptor protein with high affinity. Isothermal titration calorimetry, 19 F NMR experiments and molecular dynamics simulations reveal that increased conformational flexibility of the macrocycle-receptor complex reduces dissociation rates and contributes to complex stability. This observation has impact on macrocycle design strategies that have so far mainly focused on the stabilization of bioactive ligand conformations.

De novo active sites for resurrected Precambrian enzymes.

Protein engineering studies often suggest the emergence of completely new enzyme functionalities to be highly improbable. However, enzymes likely catalysed many different reactions already in the last universal common ancestor. Mechanisms for the emergence of completely new active sites must therefore either plausibly exist or at least have existed at the primordial protein stage. Here, we use resurrected Precambrian proteins as scaffolds for protein engineering and demonstrate that a new active site can be generated through a single hydrophobic-to-ionizable amino acid replacement that generates a partially buried group with perturbed physico-chemical properties. We provide experimental and computational evidence that conformational flexibility can assist the emergence and subsequent evolution of new active sites by improving substrate and transition-state binding, through the sampling of many potentially productive conformations. Our results suggest a mechanism for the emergence of primordial enzymes and highlight the potential of ancestral reconstruction as a tool for protein engineering.

Enzyme Architecture: Modeling the Operation of a Hydrophobic Clamp in Catalysis by Triosephosphate Isomerase.

Triosephosphate isomerase (TIM) is a proficient catalyst of the reversible isomerization of dihydroxyacetone phosphate (DHAP) to d-glyceraldehyde phosphate (GAP), via general base catalysis by E165. Historically, this enzyme has been an extremely important model system for understanding the fundamentals of biological catalysis. TIM is activated through an energetically demanding conformational change, which helps position the side chains of two key hydrophobic residues (I170 and L230), over the carboxylate side chain of E165. This is critical both for creating a hydrophobic pocket for the catalytic base and for maintaining correct active site architecture. Truncation of these residues to alanine causes significant falloffs in TIM's catalytic activity, but experiments have failed to provide a full description of the action of this clamp in promoting substrate deprotonation. We perform here detailed empirical valence bond calculations of the TIM-catalyzed deprotonation of DHAP and GAP by both wild-type TIM and its I170A, L230A, and I170A/L230A mutants, obtaining exceptional quantitative agreement with experiment. Our calculations provide a linear free energy relationship, with slope 0.8, between the activation barriers and Gibbs free energies for these TIM-catalyzed reactions. We conclude that these clamping side chains minimize the Gibbs free energy for substrate deprotonation, and that the effects on reaction driving force are largely expressed at the transition state for proton transfer. Our combined analysis of previous experimental and current computational results allows us to provide an overview of the breakdown of ground-state and transition state effects in enzyme catalysis in unprecedented detail, providing a molecular description of the operation of a hydrophobic clamp in triosephosphate isomerase.

Active Site Hydrophobicity and the Convergent Evolution of Paraoxonase Activity in Structurally Divergent Enzymes: The Case of Serum Paraoxonase 1.

Serum paraoxonase 1 (PON1) is a native lactonase capable of promiscuously hydrolyzing a broad range of substrates, including organophosphates, esters, and carbonates. Structurally, PON1 is a six-bladed ß-propeller with a flexible loop (residues 70-81) covering the active site. This loop contains a functionally critical Tyr at position 71. We have performed detailed experimental and computational analyses of the role of selected Y71 variants in the active site stability and catalytic activity in order to probe the role of Y71 in PON1's lactonase and organophosphatase activities. We demonstrate that the impact of Y71 substitutions on PON1's lactonase activity is minimal, whereas the kcat for the paraoxonase activity is negatively perturbed by up to 100-fold, suggesting greater mutational robustness of the native activity. Additionally, while these substitutions modulate PON1's active site shape, volume, and loop flexibility, their largest effect is in altering the solvent accessibility of the active site by expanding the active site volume, allowing additional water molecules to enter. This effect is markedly more pronounced in the organophosphatase activity than the lactonase activity. Finally, a detailed comparison of PON1 to other organophosphatases demonstrates that either a similar "gating loop" or a highly buried solvent-excluding active site is a common feature of these enzymes. We therefore posit that modulating the active site hydrophobicity is a key element in facilitating the evolution of organophosphatase activity. This provides a concrete feature that can be utilized in the rational design of next-generation organophosphate hydrolases that are capable of selecting a specific reaction from a pool of viable substrates.

Translocation of an Intracellular Protein via Peptide-Directed Ligation.

Ligand-directed reactions allow chemical transformations at very low reactant concentrations and can thus provide access to efficient approaches for the post-translational modification of proteins. The development of these proximity-induced reactions is hampered by the number of appropriate ligands and the lack of design principles. Addressing these limitations, we report a proximity-induced labeling system which applies a moderate affinity peptide ligand. The design process was structure-guided and supported by molecular dynamics simulations. We show that selective protein labeling can be performed inside living cells enabling the subcellular translocation of a protein via ligand-directed chemistry for the first time.

Spatiotemporal imaging of small GTPases activity in live cells.

Ras-like small GTPases function as molecular switches and regulate diverse cellular events. To examine the dynamics of signaling requires spatiotemporal visualization of their activity in the cell. Current small GTPase sensors rely on specific effector domains that are available for only a small number of GTPases and compete for endogenous regulator/effector binding. Here, we describe versatile conformational sensors for GTPase activity (COSGAs) based on the conserved GTPase fold. Conformational changes upon GDP/GTP exchange were directly observed in solution, on beads, and in live cells by Förster resonance energy transfer (FRET). The COSGAs allow for monitoring of Rab1 and K-Ras activity in live cells using fluorescence lifetime imaging microscopy. We found that Rab1 is largely active in the cytoplasm and inactive at the Golgi, suggesting that the Golgi serves as the terminal of the Rab1 functional cycle. K-Ras displays polarized activity at the plasma membrane, with less activity at the edge of the cell and membrane ruffles.

DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking.

The distance-dependent knowledge-based DrugScore(PPI) potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking "unbound perturbation" ("unbound docking") decoys generated by Baker and coworkers a 4-fold (1.5-fold) enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScore(PPI)/FRODOCK finds up to 10% (15%) more high accuracy solutions in the top 1 (top 10) predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ∼ 2-fold to 18% (58%) for an at least acceptable solution in the top 10 (top 100) predictions when performing knowledge-driven unbound docking. This suggests that DrugScore(PPI) balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScore(PPI)/FRODOCK will be successful.

CNA web server: rigidity theory-based thermal unfolding simulations of proteins for linking structure, (thermo-)stability, and function.

The Constraint Network Analysis (CNA) web server provides a user-friendly interface to the CNA approach developed in our laboratory for linking results from rigidity analyses to biologically relevant characteristics of a biomolecular structure. The CNA web server provides a refined modeling of thermal unfolding simulations that considers the temperature dependence of hydrophobic tethers and computes a set of global and local indices for quantifying biomacromolecular stability. From the global indices, phase transition points are identified where the structure switches from a rigid to a floppy state; these phase transition points can be related to a protein's (thermo-)stability. Structural weak spots (unfolding nuclei) are automatically identified, too; this knowledge can be exploited in data-driven protein engineering. The local indices are useful in linking flexibility and function and to understand the impact of ligand binding on protein flexibility. The CNA web server robustly handles small-molecule ligands in general. To overcome issues of sensitivity with respect to the input structure, the CNA web server allows performing two ensemble-based variants of thermal unfolding simulations. The web server output is provided as raw data, plots and/or Jmol representations. The CNA web server, accessible at http://cpclab.uni-duesseldorf.de/cna or http://www.cnanalysis.de, is free and open to all users with no login requirement.

How good are state-of-the-art docking tools in predicting ligand binding modes in protein-protein interfaces?

Protein-protein interfaces (PPIs) are an important class of drug targets. We report on the first large-scale validation study on docking into PPIs. DrugScore-adapted AutoDock3 and Glide showed good success rates with a moderate drop-off compared to docking to "classical targets". An analysis of the binding energetics in a PPI allows identifying those interfaces that are amenable for docking. The results are important for deciding if structure-based design approaches can be applied to a particular PPI.

NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins.

The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.

Target Flexibility in RNA-Ligand Docking Modeled by Elastic Potential Grids.

The highly flexible nature of RNA provides a formidable challenge for structure-based drug design approaches that target RNA. We introduce an approach for modeling target conformational changes in RNA-ligand docking based on potential grids that are represented as elastic bodies using Navier's equation. This representation provides an accurate and efficient description of RNA-ligand interactions even in the case of a moving RNA structure. When applied to a data set of 17 RNA-ligand complexes, filtered out of the largest validation data set used for RNA-ligand docking so far, the approach is twice as successful as docking into an apo structure and still half as successful as redocking to the holo structure. The approach allows considering RNA movements of up to 6 Å rmsd and is based on a uniform and robust parametrization of the properties of the elastic potential grids, so that the approach is applicable to different RNA-ligand complex classes.