FRET Dyes Significantly Affect SAXS Intensities of Proteins

Structural analyses in biophysics aim at revealing a relationship between a molecule's dynamic structure and its physiological function. Förster resonance energy transfer (FRET) and small‐angle X‐ray scattering (SAXS) are complementary experimental approaches to this. Their concomitant application in combined studies has recently opened a lively debate on how to interpret FRET measurements in the light of SAXS data with the popular example of the radius of gyration, commonly derived from both FRET and SAXS. There still is a lack of understanding in how to mutually relate and interpret quantities equally obtained from FRET or SAXS, and to what extent FRET dyes affect SAXS intensities in combined applications. In the present work, we examine the interplay of FRET and SAXS from a computational simulation perspective. Molecular simulations are a valuable complement to experimental approaches and supply instructive information on dynamics. As FRET depends not only on the mutual separation but also on the relative orientations, the dynamics, and therefore also the shapes of the dyes, we utilize a novel method for simulating FRET‐dye‐labeled proteins to investigate these aspects in atomic detail. We perform structure‐based simulations of four different proteins with and without dyes in both folded and unfolded conformations. In‐silico derived radii of gyration are different with and without dyes and depend on the chosen dye pair. The dyes apparently influence the dynamics of unfolded systems. We find that FRET dyes attached to a protein have a significant impact on theoretical SAXS intensities calculated from simulated structures, especially for small proteins. Radii of gyration from FRET and SAXS deviate systematically, which points to further underlying mechanisms beyond prevalent explanation approaches

Structure-based model for light-harvesting properties of nucleic acid nanostructures

Programmed self-assembly of DNA enables the rational design of megadalton-scale macromolecular assemblies with sub-nanometer scale precision. These assemblies can be programmed to serve as structural scaffolds for secondary chromophore molecules with light-harvesting properties. Like in natural systems, the local and global spatial organization of these synthetic scaffolded chromophore systems plays a crucial role in their emergent excitonic and optical properties. Previously, we introduced a computational model to predict the large-scale 3D solution structure and flexibility of nucleic acid nanostructures programmed using the principle of scaffolded DNA origami. Here, we use Förster resonance energy transfer theory to simulate the temporal dynamics of dye excitation and energy transfer accounting both for overall DNA nanostructure architecture as well as atomic-level DNA and dye chemical structure and composition. Results are used to calculate emergent optical properties including effective absorption cross-section, absorption and emission spectra and total power transferred to a biomimetic reaction center in an existing seven-helix double stranded DNA-based antenna. This structure-based computational framework enables the efficient in silico evaluation of nucleic acid nanostructures for diverse light-harvesting and photonic applications.United States. Office of Naval Research (ONR N000141210621)United States. Army Research Office (ARO MURI W911NF1210420

Simulation vs. Reality: A Comparison of In Silico Distance Predictions with DEER and FRET Measurements

Site specific incorporation of molecular probes such as fluorescent- and nitroxide spin-labels into biomolecules, and subsequent analysis by Förster resonance energy transfer (FRET) and double electron-electron resonance (DEER) can elucidate the distance and distance-changes between the probes. However, the probes have an intrinsic conformational flexibility due to the linker by which they are conjugated to the biomolecule. This property minimizes the influence of the label side chain on the structure of the target molecule, but complicates the direct correlation of the experimental inter-label distances with the macromolecular structure or changes thereof. Simulation methods that account for the conformational flexibility and orientation of the probe(s) can be helpful in overcoming this problem. We performed distance measurements using FRET and DEER and explored different simulation techniques to predict inter-label distances using the Rpo4/7 stalk module of the M. jannaschii RNA polymerase. This is a suitable model system because it is rigid and a high-resolution X-ray structure is available. The conformations of the fluorescent labels and nitroxide spin labels on Rpo4/7 were modeled using in vacuo molecular dynamics simulations (MD) and a stochastic Monte Carlo sampling approach. For the nitroxide probes we also performed MD simulations with explicit water and carried out a rotamer library analysis. Our results show that the Monte Carlo simulations are in better agreement with experiments than the MD simulations and the rotamer library approach results in plausible distance predictions. Because the latter is the least computationally demanding of the methods we have explored, and is readily available to many researchers, it prevails as the method of choice for the interpretation of DEER distance distributions

Simulation and Analysis of Protein-Fluorophore Systems for Comparison with Fluorescence Spectroscopy Data

Proteine sind die Grundbausteine des Lebens auf molekularer Ebene und wichtig für viele biologische Funktionen wie den Transport von Molekülen, Zellbewegungen oder die Katalyse von chemischen Reaktionen. So transportiert das Protein Hämoglobin beispielsweise den Sauerstoff im menschlichen Blut. Störungen der Proteinfunktionen können schwere degenerative Krankheiten wie zum Beispiel die Parkinson-, Huntington- oder Alzheimer-Krankheit verursachen. Das Verständnis von Proteinfunktionen, ihrer Struktur und Dynamik ist daher ein wichtiges Forschungsgebiet in Biologie, Pharmakologie und Medizin. Da Proteine aufgrund ihrer geringen Größe nicht mit Lichtmikroskopie beobachtet werden können, verwendet man stattdessen indirekte Methoden. Eine dieser Methoden macht sich den Förster-Resonanzenergietransfer (FRET) zunutze, um damit Proteindynamik und andere molekulare Prozesse in vitro und in vivo zu untersuchen. Die Methode wird außerdem auch in Biosensoren zur Messung der Konzentrationen von kleinen Biomolekülen wie zum Beispiel Glukose eingesetzt. Die dabei verwendeten Systeme aus Proteinen und Fluorophoren unterliegen physikalischen Prozessen wie Molekulardynamik und Photophysik. Da man diese Mechanismen nicht direkt beobachten kann, ist die Funktionsweise vieler Systeme noch nicht vollständig verstanden. Molekulare Simulationen können diese experimentellen Messungen ergänzen. Sie ermöglichen einen Einblick in molekulare Systeme und ihre Funktion auf atomarer Ebene. Die bisherigen Modellierungsmethoden für Protein-Fluorophor-Systeme sind größtenteils Näherungen, die nur für spezielle Anwendungen verwendbar sind oder zu rechenaufwändig um alle relevanten Bewegungen zu modellieren. Diese Arbeit stellt eine neue Methode für die Simulation der Dynamik in Protein-Fluorophor-Systemen vor. Sie basiert auf recheneffizienten vereinfachten Molekulardynamiksimulationen. Mit nur wenigen Parametern bietet die Methode eine realistische Beschreibung des Systems, die quantitativ mit Experimenten übereinstimmt. Sie ermöglicht den direkten Vergleich von Simulationen mit experimentellen Daten und somit eine bessere Planung und Interpretation von Experimenten. Gleichzeitig liefert sie Informationen über die zugrundeliegende Dynamik der Systeme. Diese Arbeit präsentiert ein systematisches Simulationsprotokoll für die Modellierung von Protein-Fluorophor-Systemen in silico, welches für die Erforschung von vielen biologisch relevanten Anwendungen verwendet werden kann. Sie zeigt wie Experimente und Simulationen einander ergänzen, um neue Einblicke in Dynamik und Funktion von Biomolekülen zu erhalten

Deriving Protein Structures Efficiently by Integrating Experimental Data into Biomolecular Simulations

Proteine sind molekulare Nanomaschinen in biologischen Zellen. Sie sind wesentliche Bausteine aller bekannten Lebensformen, von Einzellern bis hin zu Menschen, und erfüllen vielfältige Funktionen, wie beispielsweise den Sauerstofftransport im Blut oder als Bestandteil von Haaren. Störungen ihrer physiologischen Funktion können jedoch schwere degenerative Krankheiten wie Alzheimer und Parkinson verursachen. Die Entwicklung wirksamer Therapien für solche Proteinfehlfaltungserkrankungen erfordert ein tiefgreifendes Verständnis der molekularen Struktur und Dynamik von Proteinen. Da Proteine aufgrund ihrer lichtmikroskopisch nicht mehr auflösbaren Größe nur indirekt beobachtet werden können, sind experimentelle Strukturdaten meist uneindeutig. Dieses Problem lässt sich in silico mittels physikalischer Modellierung biomolekularer Dynamik lösen. In diesem Feld haben sich datengestützte Molekulardynamiksimulationen als neues Paradigma für das Zusammenfügen der einzelnen Datenbausteine zu einem schlüssigen Gesamtbild der enkodierten Proteinstruktur etabliert. Die Strukturdaten werden dabei als integraler Bestandteil in ein physikbasiertes Modell eingebunden. In dieser Arbeit untersuche ich, wie sogenannte strukturbasierte Modelle verwendet werden können, um mehrdeutige Strukturdaten zu komplementieren und die enthaltenen Informationen zu extrahieren. Diese Modelle liefern eine effiziente Beschreibung der aus der evolutionär optimierten nativen Struktur eines Proteins resultierenden Dynamik. Mithilfe meiner systematischen Simulationsmethode XSBM können biologische Kleinwinkelröntgenstreudaten mit möglichst geringem Rechenaufwand als physikalische Proteinstrukturen interpretiert werden. Die Funktionalität solcher datengestützten Methoden hängt stark von den verwendeten Simulationsparametern ab. Eine große Herausforderung besteht darin, experimentelle Informationen und theoretisches Wissen in geeigneter Weise relativ zueinander zu gewichten. In dieser Arbeit zeige ich, wie die entsprechenden Simulationsparameterräume mit Computational-Intelligence-Verfahren effizient erkundet und funktionale Parameter ausgewählt werden können, um die Leistungsfähigkeit komplexer physikbasierter Simulationstechniken zu optimieren. Ich präsentiere FLAPS, eine datengetriebene metaheuristische Optimierungsmethode zur vollautomatischen, reproduzierbaren Parametersuche für biomolekulare Simulationen. FLAPS ist ein adaptiver partikelschwarmbasierter Algorithmus inspiriert vom Verhalten natürlicher Vogel- und Fischschwärme, der das Problem der relativen Gewichtung verschiedener Kriterien in der multivariaten Optimierung generell lösen kann. Neben massiven Fortschritten in der Verwendung von künstlichen Intelligenzen zur Proteinstrukturvorhersage ermöglichen leistungsoptimierte datengestützte Simulationen detaillierte Einblicke in die komplexe Beziehung von biomolekularer Struktur, Dynamik und Funktion. Solche computergestützten Methoden können Zusammenhänge zwischen den einzelnen Puzzleteilen experimenteller Strukturinformationen herstellen und so unser Verständnis von Proteinen als den Grundbausteinen des Lebens vertiefen

A new twist on PIFE: photoisomerisation-related fluorescence enhancement

PIFE was first used as an acronym for protein-induced fluorescence enhancement, which refers to the increase in fluorescence observed upon the interaction of a fluorophore, such as a cyanine, with a protein. This fluorescence enhancement is due to changes in the rate of cis/trans photoisomerisation. It is clear now that this mechanism is generally applicable to interactions with any biomolecule and, in this review, we propose that PIFE is thereby renamed according to its fundamental working principle as photoisomerisation-related fluorescence enhancement, keeping the PIFE acronym intact. We discuss the photochemistry of cyanine fluorophores, the mechanism of PIFE, its advantages and limitations, and recent approaches to turn PIFE into a quantitative assay. We provide an overview of its current applications to different biomolecules and discuss potential future uses, including the study of protein-protein interactions, protein-ligand interactions and conformational changes in biomolecules.Comment: No Comment

Protein dynamics in the reductive activation of a B12-containing enzyme

B12-dependent proteins are involved in methyl transfer reactions ranging from the biosynthesis of methionine in humans to the formation of acetyl-CoA in anaerobic bacteria. During their catalytic cycle, they undergo large conformational changes to interact with various proteins. Recently, the crystal structure of the B12-containing corrinoid iron–sulfur protein (CoFeSP) in complex with its reductive activator (RACo) was determined, providing a first glimpse of how energy is transduced in the ATP-dependent reductive activation of corrinoid-containing methyltransferases. The thermodynamically uphill electron transfer from RACo to CoFeSP is accompanied by large movements of the cofactor-binding domains of CoFeSP. To refine the structure-based mechanism, we analyzed the conformational change of the B12-binding domain of CoFeSP by pulsed electron–electron double resonance and Förster resonance energy transfer spectroscopy. We show that the site-specific labels on the flexible B12-binding domain and the small subunit of CoFeSP move within 11 Å in the RACo:CoFeSP complex, consistent with the recent crystal structures. By analyzing the transient kinetics of formation and dissociation of the RACo:CoFeSP complex, we determined values of 0.75 μM–1 s–1 and 0.33 s–1 for rate constants kon and koff, respectively. Our results indicate that the large movement observed in crystals also occurs in solution and that neither the formation of the protein encounter complex nor the large movement of the B12-binding domain is rate-limiting for the ATP-dependent reductive activation of CoFeSP by RACo

Simulation of FRET dyes allows quantitative comparison against experimental data

Fully understanding biomolecular function requires detailed insight into the systems’ structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function

Single-Molecule FRET Guided Modeling of RNA Structure and Dynamics

Dynamics are central to the function of biomolecules. In the field of RNA, riboswitches are a prime example where regulatory function is encoded by structural transitions. In this work, we used single-molecule fluorescence spectroscopy together with molecular simulations to probe such onformational dynamics. The first part of this thesis reviews established and novel labeling approaches to site-specifically tag nucleic acids with fluorescent markers for Förster resonance energy transfer (FRET) applications. We characterize bioconjugated dyes in terms of their photophysics and introduce computational tools that help in selecting informative distance coordinates. Biologically active RNA molecules are composed of recurrent, well conserved modules connecting secondary and tertiary structure. Their systematic annotation over several decades led to the notion that RNA folding can be understood by the thermodynamics and kinetics of the constituting building blocks. Here, we chose a long-range tertiary contact reaching from the core of a group II intron to its anking 50-exon. The structure of the isolated contact was previously solved by NMR and allowed us to link chemical features of the ribose backbone and metal ion coordination with dissociation rates measured by single-molecule FRET. We speculate that kinetic heterogeneity in exon recognition has important implications on ribozyme catalysis. Finally, we turn to a coenzyme B12 riboswitch whose mechanism has remained elusive owing to its structural complexity. Based on the consensus sequence and fragments of other cobalamin riboswitches we built a homology model of the E. coli btuB RNA and probed its dynamics by single-molecule FRET. We found a Mg2+ dependent conformational equilibrium which is thought to coordinate folding of the metabolite binding aptamer with the peripheral expression platform

The Trimeric Major Capsid Protein of Mavirus is stabilized by its Interlocked N-termini Enabling Core Flexibility for Capsid Assembly

Icosahedral viral capsids assemble with high fidelity from a large number of identical buildings blocks. The mechanisms that enable individual capsid proteins to form stable oligomeric units (capsomers) while affording structural adaptability required for further assembly into capsids are mostly unknown. Understanding these mechanisms requires knowledge of the capsomers’ dynamics, especially for viruses where no additional helper proteins are needed during capsid assembly like for the Mavirus virophage that despite its complexity (triangulation number T = 27) can assemble from its major capsid protein (MCP) alone. This protein forms the basic building block of the capsid namely a trimer (MCP$_{3}$) of double-jelly roll protomers with highly intertwined N-terminal arms of each protomer wrapping around the other two at the base of the capsomer, secured by a clasp that is formed by part of the C-terminus. Probing the dynamics of the capsomer with HDX mass spectrometry we observed differences in conformational flexibility between functional elements of the MCP trimer. While the N-terminal arm and clasp regions show above average deuterium incorporation, the two jelly-roll units in each protomer also differ in their structural plasticity, which might be needed for efficient assembly. Assessing the role of the N-terminal arm in maintaining capsomer stability showed that its detachment is required for capsomer dissociation, constituting a barrier towards capsomer monomerisation. Surprisingly, capsomer dissociation was irreversible since it was followed by a global structural rearrangement of the protomers as indicated by computational studies showing a rearrangement of the N-terminus blocking part of the capsomer forming interface