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Results for “Biophysics”

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bioRxiv2017

On The Use Of The Experimentally Determined Enzyme Inhibition Constant As A Measure Of Absolute Binding Affinity

Defined as a state function representing an inhibitors absolute affinity for its target enzyme, the experimentally determined enzyme inhibition constant (Ki) is widely used to rank order binding affinities of different inhibitors for a common enzyme or different enzymes for a common inhibitor and to benchmark computational approaches to predicting binding affinity. Herein, we report that adsorption of bis(7)-tacrine to the glass container surface increased its Ki against Electrophorus electricus acetylcholinesterase (eeAChE) to 3.2 {+/-} 0.1 nM (n = 5) compared to 2.9 {+/-} 0.4 pM (n = 5) that was determined using plastic containers with other assay conditions kept the same. We also report that, due to binding or \"adsorption\" of bis(7)-tacrine to the inactive eeAChE, the bis(7)-tacrine Ki increased from 2.9 {+/-} 0.4 pM (n = 5) to 734 {+/-} 70 pM (n = 5) as the specific eeAChE activity decreased from 342 U/mg to 26 U/mg while other assay conditions were kept the same. These results caution against using Kis to rank order binding potencies, define selectivity, or benchmark computational methods without knowing detailed assay conditions.\n\nAbbreviations

biophysics↗

bioRxiv2017

Mesoscopic Model For DNA G-Quadruplex Unfolding

Genomes contain rare guanine-rich sequences capable of assembling into four-stranded helical structures, termed G-quadruplexes, with potential roles in gene regulation and chromosome stability. Their mechanical unfolding has only been reported to date by all-atom simulations, which cannot dissect the major physical interactions responsible for their cohesion. Here, we propose a mesoscopic model to describe both the mechanical and thermal stability of DNA G-quadruplexes, where each nucleotide of the structure, as well as each central cation located at the inner channel, is mapped onto a single bead. In this framework we are able to simulate loading rates similar to the experimental ones, which are not reachable in simulations with atomistic resolution. In this regard, we present single-molecule force-induced unfolding experiments by a high-resolution optical tweezers on a DNA telomeric sequence capable of forming a G-quadruplex conformation. Fitting the parameters of the model to the experiments we find a correct prediction of the rupture-force kinetics and a good agreement with previous near equilibrium measurements. Since G-quadruplex unfolding dynamics is halfway in complexity between secondary nucleic acids and tertiary protein structures, our model entails a nanoscale paradigm for non-equilibrium processes in the cell.

biophysics↗

bioRxiv2017

Detection Of Human Disease Conditions By Single-Cell Morpho-Rheological Phenotyping Of Whole Blood

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of whole blood, without labeling, enrichment or separation, at rates of 1,000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in whole blood and adds a functional dimension to conventional blood analysis.

biophysics↗

bioRxiv2017

Modeling the Mechanism of CLN025Beta-Hairpin Formation

Beta-hairpins are a substructure found in proteins that can lend insight into more complex systems. Furthermore, the folding of beta-hairpins is a valuable test case for benchmarking experimental and theoretical methods. Here, we simulate the folding of CLN025, a miniprotein with a beta-hairpin structure, at its experimental melting temperature using a range of state-of-the-art protein force fields. We construct Markov state models in order to examine the thermodynamics, kinetics, mechanism, and rate-determining step of folding. Mechanistically, we find the folding process is rate-limited by the formation of the turn region hydrogen bonds, which occurs following the downhill hydrophobic collapse of the extended denatured protein. These results are presented in the context of established and contradictory theories of the beta-hairpin folding process. Furthermore, our analysis suggests that the AMBER-FB15 force field, at this temperature, best describes the characteristics of the full experimental CLN025 conformational ensemble, while the AMBER ff99SB-ILDN and CHARMM22* force fields display a tendency to overstabilize the native state.

biophysics↗

bioRxiv2017

Bacterial Communication And Relevance Of Quantum Theory

The recent findings confirm that bacteria communicate each other through chemical and electrical signals. Bacteria use chemical signaling molecules which are called as quorum sensing molecules(QSMs) or autoinducers. Moreover, the ion channels in bacteria conduct a long-range electrical signaling within biofilm communities through propagated waves of potassium ions and biofilms attracts other bacterial species too. Both communication process are used by bacteria to make their own survival strategies. In this article, we model this bacterial communication mechanism by complex Ginzburg- Landau equation and discuss the formation of patterns depending on kinematic viscosity associated with internal noise. Again, the potassium wave propagation is described by the non-linear Schrodinger equation in a dissipative environment. By adding perturbation to non-linear Schrodinger equation one arrives at Complex Ginzburg-Landau equation. In this paper we emphasize that at the cellular level(bacteria) we use Complex Ginzburg - Landau equation as a perturbed Nonlinear Schrodinger equation to understand the bacterial communication as well as pattern formation in Biofilms for certain range of kinematic viscosity which can be tested in laboratory experiment. Here, the perturbation is due to the existence of non thermal fluctuations associated to the finite size of the bacteria. It sheds new light on the relevance of quantum formalism in understanding the cell to cell communication.

biophysics↗

bioRxiv2017

Compartmental and spatial rule-based modeling with Virtual cell (VCell)

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule- based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation (ODE) and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the novel rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations (PDE) deterministic solvers or the Smoldyn stochastic simulator.

biophysics↗

bioRxiv2017

qSR: A software for quantitative analysis of single molecule and super-resolution data

Single-molecule based super-resolution microscopy (Betzig et al., 2006; Hess et al., 2006; Rust et al., 2006) provides insight into the spatiotemporal organization and dynamics of biomolecules at the length scale of ten to hundreds of nanometers, which is most relevant to protein clustering in a broad range of cellular processes. A series of quantitative analysis approaches have been developed to infer the characteristic size of protein clustering via pair correlation analysis (Sengupta et al., 2013; Sengupta et al., 2011; Veatch et al., 2012) or to merge multiple blinking localizations from single fluorophores (Annibale et al., 2011), to identify clusters based on density of detections (Ester, 1996), and to measure temporal dynamics of protein clustering in living cells (Cho et al., 2016a; ...

biophysics↗

bioRxiv2017

A Bayesian computational approach to explore the optimal duration of a cell proliferation assay

Cell proliferation assays are routinely used to explore how a low density monolayer of cells grows with time. For a typical cell line with a doubling time of 12 hours (or longer), a standard cell proliferation assay conducted over 24 hours provides excellent information about the low-density exponential growth rate, but limited information about crowding effects that occur at higher densities. To explore how we can best detect and quantify crowding effects, we present a suite of in silico proliferation assays where cells proliferate according to a generalised logistic growth model. Using approximate Bayesian computation we show that data from a standard cell proliferation assay cannot reliably distinguish between classical logistic growth and more general non-logistic growth models. We then explore, and quantify, the trade-off between increasing the duration of the experiment and the associated decrease in uncertainty in the crowding mechanism.

biophysics↗

bioRxiv2017

eIF4A is stimulated by the pre-initiation complex and enhances recruitment of mRNAs regardless of structural complexity

eIF4A is a DEAD-box RNA-dependent ATPase thought to unwind RNA secondary structure in the 5'-untranslated regions (UTRs) of mRNAs to promote their recruitment to the eukaryotic translation pre-initiation complex (PIC). We show that eIF4As ATPase activity is markedly stimulated in the presence of the PIC, independently of eIF4E*eIF4G, but dependent on subunits i and g of the heteromeric eIF3 complex. Surprisingly, eIF4A accelerated the rate of recruitment of all mRNAs tested, regardless of their degree of structural complexity. Structures in the 5'-UTR and 3' of the start codon synergistically inhibit mRNA recruitment in a manner relieved by eIF4A, indicating that the factor does not act solely to melt hairpins in 5'-UTRs. Our findings that eIF4A functionally interacts with the PIC and plays important roles beyond unwinding 5-UTR structure is consistent with a recent proposal that eIF4A modulates the conformation of the 40S ribosomal subunit to promote mRNA recruitment.

biophysics↗

bioRxiv2017

Near-Atomic Resolution Structure Determination in Over-Focus with Volta Phase Plate by Cs-corrected Cryo-EM

Volta phase plate (VPP) is a recently developed transmission electron microscope (TEM) apparatus that can significantly enhance the image contrast of biological samples in cryo-electron microscopy (cryo-EM) therefore impose the possibility to solve structures of relatively small macromolecules at high resolution. In this work, we performed theoretical analysis and found that using phase plate on objective lens spherical aberration (Cs)-corrected TEM may gain some interesting optical properties, including the over-focus imaging of macromolecules. We subsequently evaluated the imaging strategy of frozen-hydrated apo-ferritin with VPP on a Cs-corrected TEM and obtained the structure of apo-ferritin at near atomic resolution from both under- and over-focused dataset, illustrating the feasibility and new potential of combining VPP with Cs-corrected TEM for high resolution cryo-EM.\n\nHighlightsThe successful combination of volta phase plate and Cs-corrector in single particle cryo-EM.\n\nNear-atomic structure determined from over-focused images by cryo-EM. VPP-Cs-corrector coupled EM provides interesting optical properties.\n\nIn BriefWe took the unique advantage of the optical system by combining the volta phase plate and Cs-corrector in a modern TEM to collect high resolution micrographs of frozen-hydrated apo-ferritin in over-focus imaging conditions and determined the structure of apo-ferritin at 3.0 Angstrom resolution.

biophysics↗

bioRxiv2017

A First Order Phase Transition Underlies the Formation of Sub-Diffractive Protein Aggregates in Mammalian Cells

Failure in protein quality control can often lead to protein aggregation, yet in neuro-degenerative diseases, by the time aggregates can be seen, the cells have advanced well into the disease pathology. Here, we develop a quantitative imaging approach to study the protein aggregation process in living mammalian cells with unprecedented spatio-temporal resolution. We find that sub-diffractive precursor aggregates may form even in untreated cells, and their size distribution is exactly as predicted for a system undergoing a first order phase transition. Practically, this implies that as soon as aggregates reach a critical size (Rc = 162 {+/-} 4 nm untreated cells), they will spontaneously grow into large inclusions. Our data suggest that a previously uncharacterized, RuvBL1 dependent mechanism clears aggregates above the critical size. Our study unveils the existence of sub-diffractive aggregates in living cells; and the strong agreement between cellular data and a nucleation theory, based on first order phase transition, provides insight into regulatory steps in the early stages of aggregate formation in vivo.

biophysics↗

bioRxiv2017

Sperm chemotaxis is driven by the slope of the chemoattractant concentration field

Spermatozoa of marine invertebrates are attracted to their conspecific female gamete by diffusive molecules, called chemoattractants, released from the egg investments in a process known as chemotaxis. The information from the egg chemoattractant concentration field is decoded into intracellular Ca2+ concentration ([Ca2+]i) changes that regulate the internal motors that shape the flagellum as it beats. By studying sea urchin species-specific differences in sperm chemoattractant-receptor characteristics we show that receptor density constrains the steepness of the chemoattractant concentration gradient detectable by spermatozoa. Through analyzing different chemoattractant gradient forms, we demonstrate for the first time that Strongylocentrotus purpuratus sperm are chemotactic and this response is consistent with frequency entrainment of two coupled physiological oscillators: i) the stimulus function and ii) the [Ca2+]i changes. We demonstrate that the slope of the chemoattractant gradients provides the coupling force between both oscillators, arising as a fundamental requirement for sperm chemotaxis.

biophysics↗

bioRxiv2017

Real-time detection of condensin-driven DNA compaction reveals a multistep binding mechanism

Condensin, a conserved member of the SMC protein family of ring-shaped multi-subunit protein complexes, is essential for structuring and compacting chromosomes. Despite its key role, its molecular mechanism has remained largely unknown. Here, we employ single-molecule magnetic tweezers to measure, in real-time, the compaction of individual DNA molecules by the budding yeast condensin complex. We show that compaction proceeds in large (~200nm) steps, driving DNA molecules into a fully condensed state against forces of up to 2pN. Compaction can be reversed by applying high forces or adding buffer of high ionic strength. While condensin can stably bind DNA in the absence of ATP, ATP hydrolysis by the SMC subunits is required for rendering the association salt-insensitive and for subsequent compaction. Our results indicate that the condensin reaction cycle involves two distinct steps, where condensin first binds DNA through electrostatic interactions before using ATP hydrolysis to encircle the DNA topologically within its ring structure, which initiates DNA compaction. The finding that both binding modes are essential for its DNA compaction activity has important implications for understanding the mechanism of chromosome compaction.

biophysics↗

bioRxiv2017

Predicting DNA Hybridization Kinetics from Sequence

Hybridization is a key molecular process in biology and biotechnology, but to date there is no predictive model for accurately determining hybridization rate constants based on sequence information. To approach this problem systematically, we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (subsequences of the CYCS and VEGF genes) at temperatures ranging from 28 {degrees}C to 55 {degrees}C. Next, we rationally designed 38 features computable based on sequence, each feature individually correlated with hybridization kinetics. These features are used in our implementation of a weighted neighbor voting (WNV) algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants (a.k.a. labeled instances). Automated feature selection and weighting optimization resulted in a final 6-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 2 with {approx}74% accuracy and within a factor of 3 with {approx}92% accuracy, based on leave-one-out cross-validation. Predictive understanding of hybridization kinetics allows more efficient design of nucleic acid probes, for example in allowing sparse hybrid-capture panels to more quickly and economically enrich desired regions from genomic DNA.

biophysics↗

bioRxiv2017

Hemodynamic forces can be accurately measured in vivo with optical tweezers

Force sensing and generation at the tissular and cellular scale is central to many biological events. There is a growing interest in modern cell biology for methods enabling force measurements in vivo. Optical trapping allows non-invasive probing of pico-Newton forces and thus emerged as a promising mean for assessing biomechanics in vivo. Nevertheless, the main obstacles rely in the accurate determination of the trap stiffness in heterogeneous living organisms, at any position where the trap is used. A proper calibration of the trap stiffness is thus required for performing accurate and reliable force measurements in vivo. Here, we introduce a method that overcomes these difficulties by accurately measuring hemodynamic profiles in order to calibrate the trap stiffness. Doing so, and using numerical methods to assess the accuracy of the experimental data, we measured flow profiles and drag forces imposed to trapped red blood cells of living zebrafish embryos. Using treatments enabling blood flow tuning, we demonstrated that such method is powerful in measuring hemodynamic forces in vivo with high accuracy and confidence. Altogether, this study demonstrates the power of optical tweezing in measuring low range hemodynamic forces in vivo and offers an unprecedented tool in both cell and developmental biology.

biophysics↗

bioRxiv2017

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

The drug design data resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of FXR inhibitors with a semi-automated alchemical free energy calculations workflow featuring the FESetup and SOMD tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature SARs only, and comparable or slightly inferior, to the best submissions from other groups.

biophysics↗

bioRxiv2017

Triazavirine supramolecular complexes as modifiers of the peptide oligomeric structure

In this study we present molecular dynamics simulations of the antiviral drug triazavirine, that affects formation of amyloid-like fibrils of the model peptide (SI). According to our simulations, triazavirine is able to form linear supramolecular structures which can act as shields and prevent interactions between SI monomers. This model, as validated by simulations, provides an adequate explanation of triazavirines mechanism of action as it pertains to SI peptide fibril formation.

biophysics↗

bioRxiv2017

Out-of-equilibrium statistical dynamics of spatial pattern generating cellular automata

How living systems generate order from disorder is a fundamental question1-5. Metrics and ideas from physical systems have elucidated order-generating collective dynamics of mechanical, motile, and electrical living systems such as bird flocks and neuronal networks6-8. But suitable metrics and principles remain elusive for many networks of cells such as tissues that collectively generate spatial patterns via chemical signals, genetic circuits, and dynamics representable by cellular automata1,9-11. Here we reveal such principles through a statistical mechanics-type framework for cellular automata dynamics in which cells with ubiquitous genetic circuits generate spatial patterns by switching on and off each others genes with diffusing signalling molecules. Lattices of cells behave as particles stochastically rolling down a pseudo-energy landscape - defined by a spin glass-like Hamiltonian - that is shaped by \"macrostate\" functions and genetic circuits. Decreasing the pseudo-energy increases the spatial patterns orderliness. A new kinetic trapping mechanism - \"pathway trapping\" - yields metastable spatial patterns by preventing minimization of the particles pseudo-energy. Noise in cellular automata reduces the trapping, thus further increases the spatial order. We generalize our framework to lattices with multiple types of cells and signals. Our work shows that establishing statistical mechanics of computational algorithms can reveal collective dynamics of signal-processing in biological and physical networks.

biophysics↗