Integration of software tools for integrative modeling of biomolecular systems.

Integrative modeling computes a model based on varied types of input information, be it from experiments or prior models. Often, a type of input information will be best handled by a specific modeling software package. In such a case, we desire to integrate our integrative modeling software package, Integrative Modeling Platform (IMP), with software specialized to the computational demands of the modeling problem at hand. After several attempts, however, we have concluded that even in collaboration with the software's developers, integration is either impractical or impossible. The reasons for the intractability of integration include software incompatibilities, differing modeling logic, the costs of collaboration, and academic incentives. In the integrative modeling software ecosystem, several large modeling packages exist with often redundant tools. We reason, therefore, that the other development groups have similarly concluded that the benefit of integration does not justify the cost. As a result, modelers are often restricted to the set of tools within a single software package. The inability to integrate tools from distinct software negatively impacts the quality of the models and the efficiency of the modeling. As the complexity of modeling problems grows, we seek to galvanize developers and modelers to consider the long-term benefit that software interoperability yields. In this article, we formulate a demonstrative set of software standards for implementing a model search using tools from independent software packages and discuss our efforts to integrate IMP and the crystallography suite Phenix within the Bayesian modeling framework.

Unraveling multi-state molecular dynamics in single-molecule FRET experiments. II. Quantitative analysis of multi-state kinetic networks.

Single-molecule Förster Resonance Energy Transfer (smFRET) experiments are ideally suited to resolve the structural dynamics of biomolecules. A significant challenge to date is capturing and quantifying the exchange between multiple conformational states, mainly when these dynamics occur on the sub-millisecond timescale. Many methods for quantitative analysis are challenged if more than two states are involved, and the appropriate choice of the number of states in the kinetic network is difficult. An additional complication arises if dynamically active molecules coexist with pseudo-static molecules in similar conformational states with undistinguishable Förster Resonance Energy Transfer (FRET) efficiencies. To address these problems, we developed a quantitative integrative analysis framework that combines the information from FRET-lines that relate average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms, fluorescence decays obtained by time-correlated single-photon-counting, photon distribution analysis of the intensities, and fluorescence correlation spectroscopy. Individually, these methodologies provide ambiguous results for the characterization of dynamics in complex kinetic networks. However, the global analysis approach enables accurate determination of the number of states, their kinetic connectivity, the transition rate constants, and species fractions. To challenge the potential of smFRET experiments for studying multi-state kinetic networks, we apply our integrative framework using a set of synthetic data for three-state systems with different kinetic connectivity and exchange rates. Our methodology paves the way toward an integrated analysis of multiparameter smFRET experiments that spans all dimensions of the experimental data. Finally, we propose a workflow for the analysis and show examples that demonstrate the usefulness of this toolkit for dynamic structural biology.

Unraveling multi-state molecular dynamics in single-molecule FRET experiments. I. Theory of FRET-lines.

Conformational dynamics of biomolecules are of fundamental importance for their function. Single-molecule studies of Förster Resonance Energy Transfer (smFRET) between a tethered donor and acceptor dye pair are a powerful tool to investigate the structure and dynamics of labeled molecules. However, capturing and quantifying conformational dynamics in intensity-based smFRET experiments remains challenging when the dynamics occur on the sub-millisecond timescale. The method of multiparameter fluorescence detection addresses this challenge by simultaneously registering fluorescence intensities and lifetimes of the donor and acceptor. Together, two FRET observables, the donor fluorescence lifetime τD and the intensity-based FRET efficiency E, inform on the width of the FRET efficiency distribution as a characteristic fingerprint for conformational dynamics. We present a general framework for analyzing dynamics that relates average fluorescence lifetimes and intensities in two-dimensional burst frequency histograms. We present parametric relations of these observables for interpreting the location of FRET populations in E-τD diagrams, called FRET-lines. To facilitate the analysis of complex exchange equilibria, FRET-lines serve as reference curves for a graphical interpretation of experimental data to (i) identify conformational states, (ii) resolve their dynamic connectivity, (iii) compare different kinetic models, and (iv) infer polymer properties of unfolded or intrinsically disordered proteins. For a simplified graphical analysis of complex kinetic networks, we derive a moment-based representation of the experimental data that decouples the motion of the fluorescence labels from the conformational dynamics of the biomolecule. Importantly, FRET-lines facilitate exploring complex dynamic models via easily computed experimental observables. We provide extensive computational tools to facilitate applying FRET-lines.

Triphosphate induced dimerization of human guanylate binding protein 1 involves association of the C-terminal helices: a joint double electron-electron resonance and FRET study.

Human guanylate binding protein 1 (hGBP1) is a member of the dynamin superfamily of large GTPases. During GTP hydrolysis, the protein undergoes structural changes leading to self-assembly. Previous studies have suggested dimerization of the protein by means of its large GTPase (LG) domain and significant conformational changes in helical regions near the LG domain and at its C-terminus. We used site-directed labeling and a combination of pulsed electron paramagnetic resonance and time-resolved fluorescence spectroscopy for structural investigations on hGBP1 dimerization and conformational changes of its C-terminal helix α13. Consistent distance measurements by double electron-electron resonance (DEER, also named pulse double electron resonance = PELDOR) spectroscopy and Förster resonance energy transfer (FRET) measurements using model-free analysis approaches revealed a close interaction of the two α13 helices in the hGBP1 dimer formed upon binding of the nonhydrolyzable nucleoside triphosphate derivate GppNHp. In molecular dynamics (MD) simulations, these two helices form a stable dimer in solution. Our data show that dimer formation of hGBP1 involves multiple spatially distant regions of the protein, namely, the N-terminal LG domain and the C-terminal helices α13. The contacts formed between the two α13 helices and the resulting juxtaposition are expected to be a key step for the physiological membrane localization of hGBP1 through the farnesyl groups attached to the end of α13.

Resolution of Maximum Entropy Method-Derived Posterior Conformational Ensembles of a Flexible System Probed by FRET and Molecular Dynamics Simulations.

Maximum entropy methods (MEMs) determine posterior distributions by combining experimental data with prior information. MEMs are frequently used to reconstruct conformational ensembles of molecular systems for experimental information and initial molecular ensembles. We performed time-resolved Förster resonance energy transfer (FRET) experiments to probe the interdye distance distributions of the lipase-specific foldase Lif in the apo state, which likely has highly flexible, disordered, and/or ordered structural elements. Distance distributions estimated from ensembles of molecular dynamics (MD) simulations serve as prior information, and FRET experiments, analyzed within a Bayesian framework to recover distance distributions, are used for optimization. We tested priors obtained by MD with different force fields (FFs) tailored to ordered (FF99SB, FF14SB, and FF19SB) and disordered proteins (IDPSFF and FF99SBdisp). We obtained five substantially different posterior ensembles. As in our FRET experiments the noise is characterized by photon counting statistics, for a validated dye model, MEM can quantify consistencies between experiment and prior or posterior ensembles. However, posterior populations of conformations are uncorrelated to structural similarities for individual structures selected from different prior ensembles. Therefore, we assessed MEM simulating varying priors in synthetic experiments with known target ensembles. We found that (i) the prior and experimental information must be carefully balanced for optimal posterior ensembles to minimize perturbations of populations by overfitting and (ii) only ensemble-integrated quantities like inter-residue distance distributions or density maps can be reliably obtained but not ensembles of atomistic structures. This is because MEM optimizes ensembles but not individual structures. This result for a highly flexible system suggests that structurally varying priors calculated from varying prior ensembles, e.g., generated with different FFs, may serve as an ad hoc estimate for MEM reconstruction robustness.

Diffusion of nanoparticles in a biofilm.

In order to evaluate the risk of engineered nanomaterials in the natural environment, one must determine their mobility, among other factors. Such determinations are difficult given that natural systems are heterogeneous and biofilms are ubiquitous in soils and waters. The interaction and diffusion of several model nanoparticles (dextrans, fluorescent microspheres, Ag nanoparticles) were studied in situ using confocal microscopy and fluorescence correlation spectroscopy in a biofilm composed of Pseudomonas fluorescens. For the most part, relative self-diffusion coefficients decreased exponentially with the square of the radius of the nanoparticle. The precise growth conditions of the biofilm resulted in a variable density of both exopolymers and microbes, which was also shown to be an important parameter controlling the diffusion of the nanoparticles. Finally, the charge of the nanoparticles appeared to be important; for a dense bacterial biofilm, a greater than predicted decrease in the self-diffusion coefficient was observed for the negatively charged nano Ag.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices.

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

Automated and optimally FRET-assisted structural modeling.

FRET experiments can provide state-specific structural information of complex dynamic biomolecular assemblies. However, to overcome the sparsity of FRET experiments, they need to be combined with computer simulations. We introduce a program suite with (i) an automated design tool for FRET experiments, which determines how many and which FRET pairs should be used to minimize the uncertainty and maximize the accuracy of an integrative structure, (ii) an efficient approach for FRET-assisted coarse-grained structural modeling, and all-atom molecular dynamics simulations-based refinement, and (iii) a quantitative quality estimate for judging the accuracy of FRET-derived structures as opposed to precision. We benchmark our tools against simulated and experimental data of proteins with multiple conformational states and demonstrate an accuracy of ~3 Å RMSDCα against X-ray structures for sets of 15 to 23 FRET pairs. Free and open-source software for the introduced workflow is available at https://github.com/Fluorescence-Tools . A web server for FRET-assisted structural modeling of proteins is available at http://nmsim.de .

Resolving dynamics and function of transient states in single enzyme molecules.

We use a hybrid fluorescence spectroscopic toolkit to monitor T4 Lysozyme (T4L) in action by unraveling the kinetic and dynamic interplay of the conformational states. In particular, by combining single-molecule and ensemble multiparameter fluorescence detection, EPR spectroscopy, mutagenesis, and FRET-positioning and screening, and other biochemical and biophysical tools, we characterize three short-lived conformational states over the ns-ms timescale. The use of 33 FRET-derived distance sets, to screen available T4L structures, reveal that T4L in solution mainly adopts the known open and closed states in exchange at 4 µs. A newly found minor state, undisclosed by, at present, more than 500 crystal structures of T4L and sampled at 230 µs, may be actively involved in the product release step in catalysis. The presented fluorescence spectroscopic toolkit will likely accelerate the development of dynamic structural biology by identifying transient conformational states that are highly abundant in biology and critical in enzymatic reactions.

Combining Graphical and Analytical Methods with Molecular Simulations To Analyze Time-Resolved FRET Measurements of Labeled Macromolecules Accurately.

Förster resonance energy transfer (FRET) measurements from a donor, D, to an acceptor, A, fluorophore are frequently used in vitro and in live cells to reveal information on the structure and dynamics of DA labeled macromolecules. Accurate descriptions of FRET measurements by molecular models are complicated because the fluorophores are usually coupled to the macromolecule via flexible long linkers allowing for diffusional exchange between multiple states with different fluorescence properties caused by distinct environmental quenching, dye mobilities, and variable DA distances. It is often assumed for the analysis of fluorescence intensity decays that DA distances and D quenching are uncorrelated (homogeneous quenching by FRET) and that the exchange between distinct fluorophore states is slow (quasistatic). This allows us to introduce the FRET-induced donor decay, εD(t), a function solely depending on the species fraction distribution of the rate constants of energy transfer by FRET, for a convenient joint analysis of fluorescence decays of FRET and reference samples by integrated graphical and analytical procedures. Additionally, we developed a simulation toolkit to model dye diffusion, fluorescence quenching by the protein surface, and FRET. A benchmark study with simulated fluorescence decays of 500 protein structures demonstrates that the quasistatic homogeneous model works very well and recovers for single conformations the average DA distances with an accuracy of < 2%. For more complex cases, where proteins adopt multiple conformations with significantly different dye environments (heterogeneous case), we introduce a general analysis framework and evaluate its power in resolving heterogeneities in DA distances. The developed fast simulation methods, relying on Brownian dynamics of a coarse-grained dye in its sterically accessible volume, allow us to incorporate structural information in the decay analysis for heterogeneous cases by relating dye states with protein conformations to pave the way for fluorescence and FRET-based dynamic structural biology. Finally, we present theories and simulations to assess the accuracy and precision of steady-state and time-resolved FRET measurements in resolving DA distances on the single-molecule and ensemble level and provide a rigorous framework for estimating approximation, systematic, and statistical errors.

Guanylate binding proteins directly attack Toxoplasma gondii via supramolecular complexes.

GBPs are essential for immunity against intracellular pathogens, especially for Toxoplasma gondii control. Here, the molecular interactions of murine GBPs (mGBP1/2/3/5/6), homo- and hetero-multimerization properties of mGBP2 and its function in parasite killing were investigated by mutational, Multiparameter Fluorescence Image Spectroscopy, and live cell microscopy methodologies. Control of T. gondii replication by mGBP2 requires GTP hydrolysis and isoprenylation thus, enabling reversible oligomerization in vesicle-like structures. mGBP2 undergoes structural transitions between monomeric, dimeric and oligomeric states visualized by quantitative FRET analysis. mGBPs reside in at least two discrete subcellular reservoirs and attack the parasitophorous vacuole membrane (PVM) as orchestrated, supramolecular complexes forming large, densely packed multimers comprising up to several thousand monomers. This dramatic mGBP enrichment results in the loss of PVM integrity, followed by a direct assault of mGBP2 upon the plasma membrane of the parasite. These discoveries provide vital dynamic and molecular perceptions into cell-autonomous immunity.