Structural mechanism of the recovery-stroke in Myosin II molecular motor at atomic detail

Das molekulare Motorprotein Myosin wandelt chemische Energie aus der ATP Hydolyse in mechanische Arbeit um, die dazu genutzt wird um Myosin- und Aktin-Filamente gegeneinander zu verschieben und so z.B. die Muskelkontraktion zu ermoeglichen. Der Mechanismus dieser chemisch-mechanischen Kopplung, der fuer die Funktion von Myosin essenziell ist, ist nur in Ansaetzen verstanden. In dieser Arbeit wird ein rechnergesttzter Ansatz verwendet um den Mechanismus des recovery stroke'' zu verstehen. Der recovery stroke'' ist einer der fundamentalen Prozesse bei der Muskelkontraktion in lebenen Organismen. Waehrend des recovery stroke'' wird der Myosin Motor fuer den naechsten Kraftschlag vorbereited indem der Myosin-Kopf um 60 degree relativ zur Konverter-Domaene und dem Hebelarm gedreht wird. Der Drehpunkt ist mit der Bindetasche, in der die ATP Hydrolyse stattfindet, durch die sogenannte Relais-Helix verbunden. Waehrend des "recovery stroke" finden eine eine Reihe von strukturellen Aenderungen laengs dieser Helix statt. In der vorliegenden Arbeit wird der Kopplungsmechanismus zwischen der ATP Hydrolyse und der Drehbewegung mit Hilfe eines Minimum-Energie Pfades (MEP) simuliert. Der MEP verbindet die Roentgenkristallographischen End-Zustaende des Prozesses durch eine Kette von geometrieoptimierten intermediren Strukturen. Der "recovery stroke" beruht auf der Bildung zweier Wasserstoffbrueckenbindungen durch die "switch-2" Schleife, in Korrelation mit der Bewegung zweier Helices welche die Konverter-Domaene halten: der Relais-Helix und der SH1-Helix. Der MEP zeigt dass dieser Prozess aus zwei Phasen besteht. In der ersten Phase bildet sich eine Wasserstoffbrueckenbindung zwischen Gly457 am N-terminalen Ende der Relais-Helix und dem gamma-Phosphat des ATP, was eine Kipp-Bewegung der Relais-Helix zur Folge hat. Die zweite Phase wird durch die Bildung einer Wasserstoffbrueckenbindung zwischen der "switch-2" Schleife und Ser181 der P-Schleife initiiert. Dadurch wird eine weitere Schleifeaehnlich einem Keil gegen das N-terminale Ende der SH1-Helix geschoben, wodurch letztere parallel zur Relais-Helix verschoben wird. Die Kippbewegung der ersten Phase bewirkt eine Drehung der Konverter-Domäne um 30 degree, wahrend die Verschiebung der SH1-Helix eine Drehung um weitere 40 degree zur Folge hat. Der hier vorgeschlagene Kopplungsmechanismus ist konsistent mit verfuegbaren Mutations-Experimenten und erklaert zum ersten Mal die Rolle der hochgradig Sequenz-konservierten Schleife, die hier "Keil"-Schleife genannt wird. In einem weiteren Teil der Arbeit werden Molekulardynamik-Simulationen von Myosin II des Organismus Dictyostelium Discoideum in beiden End-Zustaenden des "recovery stroke" mit verschiedenen Nukleotid-Zustaenden (ATP, ADP.Pi, ADP) durchgefuehrt. Diese Simulationen zeigen dass die Seitenkette von Asn475 (welche die erste Phase des "recovery stroke" initiiert") sich durch die ATP-Hydrolyse von "switch-2" wegbewegt und eine Wasserstoffbrueckenbindung mit Tyr573 auf der Keilschleife bildet. Diese Abhaengigkeit vom Nukleotid-Zustand wird erklaert durch eine kleine Verschiebung des abgespaltenen beta-Phosphats hin zu Gly457 welches seinerseits Asn475 verschiebt. Die Sensitivitaet bezueglich des Nukleotid-Zustandes ist wichtig fuer (i) die Vermeidung einer unproduktiven Umkehrung des "recovery strokes" waehrend des ADP.Pi Zustandes, und (ii) die Entkopplung der Relais-Helix vom "switch-2", wodurch erreicht wird, dass der Kraftschlag nach der initialen Bindung an Aktin ausgelast wird, wobei Gly457 von "switch-2" weiterhin mit dem Pi interagiert,welches bekanntermass en erst nach der Bindung an Aktin freigelassen wird. Es wird beobachtet dass die katalytisch wichtige Salzbruecke zwischen Arg238 (in "switch-1") und Glu459 (in "switch-2"), welche die Bindetasche and der Hydrolysestelle bedeckt, durch die Bindung von ATP an die Struktur vor dem "recovery stroke" schnell gebildet wird. Diese Salzbrucke bleibt auch nach dem "recovery stroke" stabil, was darauf hindeuted dass sie die Rolle hat die ATP Bindetasche durch "induced fit" zu formen

Knockdown of Amyloid Precursor Protein in Zebrafish Causes Defects in Motor Axon Outgrowth

Amyloid precursor protein (APP) plays a pivotal role in Alzheimer’s disease (AD) pathogenesis, but its normal physiological functions are less clear. Combined deletion of the APP and APP-like protein 2 (APLP2) genes in mice results in post-natal lethality, suggesting that APP performs an essential, if redundant, function during embryogenesis. We previously showed that injection of antisense morpholino to reduce APP levels in zebrafish embryos caused convergent-extension defects. Here we report that a reduction in APP levels causes defective axonal outgrowth of facial branchiomotor and spinal motor neurons, which involves disorganized axonal cytoskeletal elements. The defective outgrowth is caused in a cell-autonomous manner and both extracellular and intracellular domains of human APP are required to rescue the defective phenotype. Interestingly, wild-type human APP rescues the defective phenotype but APPswe mutation, which causes familial AD, does not. Our results show that the zebrafish model provides a powerful system to delineate APP functions in vivo and to study the biological effects of APP mutations

Automating the search of molecular motor templates by evolutionary methods

The first author is supported by a FPU grant (AP2007-03704) from the Ministerio de Educación of the Spanish Government, and has been supported by the BioEmergences project (code 28892) of the Sixth Framework Programme of the European Union. Our research group has been partially supported by the local government (Junta de Andalucía) through a grant for the GENEX project (P09-TIC-5123).Biological molecular motors are nanoscale devices capable of transforming chemical energy into mechanical work, which are being researched in many scientific disciplines. From a computational point of view, the characteristics and dynamics of these motors are studied at multiple time scales, ranging from very detailed and complex molecular dynamics simulations spanning a few microseconds, to extremely simple and coarse-grained theoretical models of their working cycles. However, this research is performed only in the (relatively few) instances known from molecular biology. In this work, results from elastic network analysis and behaviour-finding methods are applied to explore a subset of the configuration space of template molecular structures that are able to transform chemical energy into directed movement, for a fixed instance of working cycle. While using methods based on elastic networks limits the scope of our results, it enables the implementation of computationally lightweight methods, in a way that evolutionary search techniques can be applied to discover novel molecular motor templates. The results show that molecular motion can be attained from a variety of structural configurations, when a functional working cycle is provided. Additionally, these methods enable a new computational way to test hypotheses about molecular motors

Increased Secreted Amyloid Precursor Protein-α (sAPPα) in Severe Autism: Proposal of a Specific, Anabolic Pathway and Putative Biomarker

Autism is a neurodevelopmental disorder characterized by deficits in verbal communication, social interactions, and the presence of repetitive, stereotyped and compulsive behaviors. Excessive early brain growth is found commonly in some patients and may contribute to disease phenotype. Reports of increased levels of brain-derived neurotrophic factor (BDNF) and other neurotrophic-like factors in autistic neonates suggest that enhanced anabolic activity in CNS mediates this overgrowth effect. We have shown previously that in a subset of patients with severe autism and aggression, plasma levels of the secreted amyloid-β (Aβ) precursor protein-alpha form (sAPPα) were significantly elevated relative to controls and patients with mild-to-moderate autism. Here we further tested the hypothesis that levels of sAPPα and sAPPβ (proteolytic cleavage products of APP by α- and β-secretase, respectively) are deranged in autism and may contribute to an anabolic environment leading to brain overgrowth. We measured plasma levels of sAPPα, sAPPβ, Aβ peptides and BDNF by corresponding ELISA in a well characterized set of subjects. We included for analysis 18 control, 6 mild-to-moderate, and 15 severely autistic patient plasma samples. We have observed that sAPPα levels are increased and BDNF levels decreased in the plasma of patients with severe autism as compared to controls. Further, we show that Aβ1-40, Aβ1-42, and sAPPβ levels are significantly decreased in the plasma of patients with severe autism. These findings do not extend to patients with mild-to-moderate autism, providing a biochemical correlate of phenotypic severity. Taken together, this study provides evidence that sAPPα levels are generally elevated in severe autism and suggests that these patients may have aberrant non-amyloidogenic processing of APP

Free Energy Simulations of a GTPase: GTP and GDP Binding to Archaeal Initiation Factor 2

International audienceArchaeal initiation factor 2 (aIF2) is a protein involved in the initiation of protein biosynthesis. In its GTP-bound, "ON" conformation, aIF2 binds an initiator tRNA and carries it to the ribosome. In its GDP-bound, "OFF" conformation, it dissociates from tRNA. To understand the specific binding of GTP and GDP and its dependence on the ON or OFF conformational state of aIF2, molecular dynamics free energy simulations (MDFE) are a tool of choice. However, the validity of the computed free energies depends on the simulation model, including the force field and the boundary conditions, and on the extent of conformational sampling in the simulations. aIF2 and other GTPases present specific difficulties; in particular, the nucleotide ligand coordinates a divalent Mg(2+) ion, which can polarize the electronic distribution of its environment. Thus, a force field with an explicit treatment of electronic polarizability could be necessary, rather than a simpler, fixed charge force field. Here, we begin by comparing a fixed charge force field to quantum chemical calculations and experiment for Mg(2+):phosphate binding in solution, with the force field giving large errors. Next, we consider GTP and GDP bound to aIF2 and we compare two fixed charge force fields to the recent, polarizable, AMOEBA force field, extended here in a simple, approximate manner to include GTP. We focus on a quantity that approximates the free energy to change GTP into GDP. Despite the errors seen for Mg(2+):phosphate binding in solution, we observe a substantial cancellation of errors when we compare the free energy change in the protein to that in solution, or when we compare the protein ON and OFF states. Finally, we have used the fixed charge force field to perform MDFE simulations and alchemically transform GTP into GDP in the protein and in solution. With a total of about 200 ns of molecular dynamics, we obtain good convergence and a reasonable statistical uncertainty, comparable to the force field uncertainty, and somewhat lower than the predicted GTP/GDP binding free energy differences. The sign and magnitudes of the differences can thus be interpreted at a semiquantitative level, and are found to be consistent with the experimental binding preferences of ON- and OFF-aIF2

A Discriminative Ramachandran Potential of Mean Force Aimed at Minimizing Secondary Structure Bias

We introduce PMF*, a novel Potential of Mean Force (PMF) for the Ramachandran Φ/Ψ-dihedral plot of the 20 standard amino acids and assess its relevance to the conformation of polypeptides by scoring structures in the Protein Data Bank and decoy datasets. The new energy function is a linear combination of the conventional, unreferenced PMF and the ΔPMF relative to the free energy of all amino acids in the parameterization set of structures, effectively removing their respective biases towards α-helix and β-strand. It is shown that low-resolution crystal structures, NMR structures, and theoretical models have on average significantly higher energies than high-resolution crystal structures; also PMF* is more discriminative for structure quality than the individual PMF and ΔPMF energy functions. PMF* may be well suited for use as a restraint energy term in the refinement of experimental structures and theoretical models

Ternary Heterostructures Based on BaTiO3/MoO3/Ag for Highly Efficient and Reusable Photocatalytic Applications

Abstract This work shows the fabrication of an efficient ternary heterostructure photocatalyst by integrating ferroelectric BaTiO3 (BTO) as the bottom layer, semiconductor MoO3 as the middle layer and plasmonic silver nanoparticles (Ag NPs) as the top layer, respectively. The BaTiO3/MoO3/Ag (BMA) heterostructure exhibits a higher photodegradation and photocatalytic efficiency of 100% for rhodamine B (RhB) dye under a UV–Visible light illumination of 60 min when compared with its binary heterostructure counterparts BaTiO3/Ag (BA) and MoO3/Ag (MA). The increased photocatalytic activity in BMA heterostructure is attributed to its enhanced interfacial electric field due to the electric double layer formation at BTO‐MoO3 and MoO3‐Ag interfaces. The higher blueshift in the surface plasmon resonance (SPR) peak observed for the BMA heterostructure clearly indicates an increased electron transfer toward the top Ag NPs layer under optical illumination. The higher resistive switching (RS) ratio, the increased difference in voltage minima, and the improved photocurrent generation, as evident from the I–V characteristics, illustrate the enhanced charge carrier generation and separation in BMA heterostructure. A smaller arc radius observed for the Nyquist plot of BMA heterostructure clearly showcases its increased interfacial charge transfer (CT). The CT mechanism and reusability of the BMA heterostructure are also studied

Pyroelectric nanogenerators in energy technology

[Excerpt] International crisis such as global warming, environmental pollution, and e-waste significantly increased the demand of electronic devices powered by renewable and sustainable energy sources [1, 2]. It is known that batteries are key renewable energy sources for powering electronic systems, which suffer from drawbacks like environmental issues, limited life-time, weight, and periodic maintenance or replacement [3]. Therefore, energy harvesting from the most reliable sources such as green energy (solar, wind, biomass, and hydrogen) and mechanical energy (water flow, mechani cal vibrations, and human motions) are inevitable. In our daily life, different forms of energies like thermal, mechanical, and photovoltaic are scattered around or wasted. Thus, commercialization of wasted energy into electrical energy has become imperative to build a clean and sustainable world [4, 5]. Moreover, thermal energy exists everywhere in the form of sun light, wind, human body, etc. [6–8]. For instance, our human body is an indispensable source of thermal energy, and we are simply wasting it without knowing the importance. However, harvesting of electrical energy from thermal energy requires a thermal fluctuation or temperature gradient. For instance, the human respiration and locomotion create fluctuations in the thermal energy and can be converted into electrical energy [7, 8]. The process of generating electrical energy using the temperature gradient is known as pyroelectric effect or pyroelectricity [8]. Besides, the pyroelectric materials can gener ate electrical energy from the temperature fluctuations induced due to small-scale physical changes. These pyroelectric materials that can generate electrical energy using small physical-change induced thermal fluctuation are known as pyroelectric nanogenerators (PENGs). Converting such a feasible energy source to electrical energy using PENGs under ambient conditions is of great impor tance for long-term self-powered energy systems. Figure 9.1 illustrates the schematic representation of various applications of PENGs. [...

Atomically detailed simulation of the recovery stroke in myosin by Milestoning

Myosin II is a molecular motor that converts chemical to mechanical energy and enables muscle operations. After a power stroke, a recovery transition completes the cycle and returns the molecular motor to its prestroke state. Atomically detailed simulations in the framework of the Milestoning theory are used to calculate kinetics and mechanisms of the recovery stroke. Milestoning divides the process into transitions between hyper-surfaces (Milestones) along a reaction coordinate. Decorrelation of dynamics between sequential Milestones is assumed, which speeds up the atomically detailed simulations by a factor of millions. Two hundred trajectories of myosin with explicit water solvation are used to sample transitions between sequential pairs of Milestones. Collective motions of hundreds of atoms are described at atomic resolution and at the millisecond time scale. The experimentally measured transition time of about a millisecond is in good agreement with the computed time. The simulations support a sequential mechanism. In the first step the P-loop and switch 2 close on the ATP and in the second step the mechanical relaxation is induced via the relay and the SH1 helices. We propose that the entropy of switch 2 helps to drive the power stroke. Secondary structure elements are progressing through a small number of discrete states in a network of activated transitions and are assisted by side chain flips between rotameric states. The few-state sequential mechanism is likely to enhance the efficiency of the relaxation reducing the probability of off-pathway intermediates