PaperPlayer biorxiv biophysics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.217794v1?rss=1

Authors: Vant, J. W., Sarkar, D., Fiorin, G., Skeel, R. D., Vermaas, J. V., Singharoy, A.

Abstract:

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the 3-dimensional electron density of a protein, as it would be deter- mined by cryo-EM or X-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density- driven molecular dynamics methodologies that determine only the best map-model fits, our work uses the recently developed Multi-Map methodology to monitor concerted move- ments within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along reaction coordinates derived from electron densities can serve to induce conformational transitions between known intermediates. The simulated pathways appear reversible, with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution (~5 [A]) density information coupled to comparatively large structural transitions. Practical considerations for generating transitions with multiple intermediate atomic density distributions are also discussed.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.218917v1?rss=1

Authors: Norn, C., Wicky, B. I. M., Juergens, D., Liu, S., Kim, D., Koepnick, B., Anishchenko, I., Foldit Players,, Baker, D., Ovchinnikov, S.

Abstract:

The protein design problem is to identify an amino acid sequence which folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the lowest energy conformation is that structure. As this calculation involves not only all possible amino acid sequences but also all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest energy conformation for the designed sequence, and discarding the in many cases large fraction of designed sequences for which this is not the case. Here we show that by backpropagating gradients through the trRosetta structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures, and in one calculation explicitly design amino acid sequences predicted to fold into the desired structure and not any other. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by landscape optimization to the standard fixed backbone sequence design methodology in Rosetta, and show that the results of the former, but not the latter, are sensitive to the presence of competing low-lying states. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low resolution trRosetta model serves to disfavor alternative states, and the high resolution Rosetta model, to create a deep energy minimum at the design target structure.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.218784v1?rss=1

Authors: Sztain, T., Amaro, R. E., McCammon, J. A.

Abstract:

The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site and assed their druggability. These pockets can aid in virtual screening efforts to identify a protease inhibitor for the treatment of COVID-19.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.22.215970v1?rss=1

Authors: Chung, J. K., Huang, W. Y. C., Carbone, C. B., Nocka, L. M., Parikh, A. N., Vale, R., Groves, J. T.

Abstract:

Lipid miscibility phase separation has long been considered to be a central element of cell membrane organization. More recently, protein condensation phase transitions, into three-dimensional droplets or in two-dimensional lattices on membrane surfaces, have emerged as another important organizational principle within cells. Here, we reconstitute the LAT:Grb2:SOS protein condensation on the surface of giant unilamellar vesicles capable of undergoing lipid phase separations. Our results indicate that assembly of the protein condensate on the membrane surface can drive lipid phase separation. This phase transition occurs isothermally and is governed by tyrosine phosphorylation on LAT. Furthermore, we observe that the induced lipid phase separation drives localization of the SOS substrate, K-Ras, into the LAT:Grb2:SOS protein condensate.

Statement of SignificanceProtein condensation phase transitions are emerging as an important organizing principles in cells. One such condensate plays a key role in T cell receptor signaling. Immediately after receptor activation, multivalent phosphorylation of the adaptor protein LAT at the plasma membrane leads to networked assembly of a number of signaling proteins into a two-dimensional condensate on the membrane surface. In this study, we demonstrate that LAT condensates in reconstituted vesicles are sufficient to drive lipid phase separation. This lipid reorganization drives another key downstream signaling molecule, Ras, into the LAT condensates. These results show that the LAT condensation phase transition, which is actively controlled by phosphorylation reactions, extends its influence to control lipid phase separation in the underlying membrane.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.22.216317v1?rss=1

Authors: Ma, N., Lee, S., Vaidehi, N.

Abstract:

Although multiple components of the cell membrane modulate the stability and activation of G protein coupled receptors (GPCRs), the activation mechanism comes from detergent studies, since it is challenging to study activation in multi-component lipid bilayer. Using the multi-scale molecular dynamics simulations(50s), our comparative study between cell membrane and detergents shows that: the changes in inter-residue distances, known as activation microswitches, show an ensemble of states in the extent of activation in cell membrane. We forward a rheostat model of GPCR activation rather than a binary switch model. Phosphatidylinositol bisphosphate (PIP2) and calcium ions, through a tug of war, maintain a balance between the GPCR stability and activity in cell membrane. Due to the lack of receptor stiffening effects by PIP2, detergents promote more transitions among conformational states than cell membrane. These findings connect the chemistry of cell membrane lipids to receptor activity useful to design detergents mimicking cell membrane.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.217125v1?rss=1

Authors: Sauer, M., Helmerich, D. A., Beliu, G.

Abstract:

The degree of labeling (DOL) of antibodies has so far been optimized for high brightness and specific and efficient binding. The influence of the DOL on the blinking performance of antibodies used in direct stochastic optical reconstruction microscopy (dSTORM) has so far attained limited attention. Here, we investigated the spectroscopic characteristics of IgG antibodies labeled at DOLs of 1.1- 8.3 with Alexa Fluor 647 (Al647) at the ensemble and single-molecule level. Multiple-Al647-labeled antibodies showed weak and strong quenching interactions in aqueous buffer but could all be used for dSTORM imaging with spatial resolutions of [~] 20 nm independent of the DOL. Photon antibunching experiments in aqueous buffer demonstrate that the emission of multiple-Al647-labeled antibodies switches from classical to non-classical light in photoswitching buffer. We developed a model that explains the observed blinking of multiple-labeled antibodies and can be used advantageously to develop improved fluorescent probes for dSTORM experiments.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.23.211979v1?rss=1

Authors: Barberi, L., Livolant, F., Leforestier, A., Lenz, M.

Abstract:

In viruses and cells, DNA is closely packed and tightly curved thanks to polyvalent cations inducing an effective attraction between its negatively charged filaments. Our understanding of this effective attraction remains very incomplete, partly because experimental data is limited to bulk measurements on large samples of mostly uncurved DNA helices. Here we use cryo electron microscopy to shed light on the interaction between highly curved helices. We find that the spacing between DNA helices in spermine-induced DNA toroidal condensates depends on their location within the torus, consistent with a mathematical model based on the competition between electrostatic interactions and the bending rigidity of DNA. We use our model to infer the characteristics of the interaction potential, and find that its equilibrium spacing strongly depends on the curvature of the filaments. In addition, the interaction is much softer than previously reported in bulk samples using different salt conditions. Beyond viruses and cells, our characterization of the interactions governing DNA-based dense structures could help develop robust designs in DNA nanotechnologies.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.20.212688v1?rss=1

Authors: Tavakoli, M., Jazani, S., Sgouralis, I., Heo, W., Ishii, K., Tahara, T., Presse, S.

Abstract:

Lifetimes of chemical species is typically estimated, on a pixel-by-pixel basis by either fitting time correlated single photon counting (TCSPC) histograms or, more recently, through phasor analysis from time-resolved photon arrivals. While both methods yield lifetimes in a computationally efficient manner, they have limitations. First, both TCSPC and phasor analysis set the number of chemical species by hand before lifetimes can be determined. Yet the number of species itself is encoded in photon arrival times and need not be set by hand a priori. Next, even to determine lifetimes under the assumption of a known number of species, both methods rely on heavy data post-processing of the signal thereby requiring large amounts of data to retrieve lifetimes. As a result, the sample is exposed to orders of magnitude more light than is required and the ability to resolve fast processes is compromised. Here we propose a direct photo-by-photon analysis of data drawn from pulsed excitation experiments to infer, simultaneously and self-consistently, the number of species and their associated lifetimes from as little as a few thousand photons for two species. We do so by leveraging new mathematical tools within the Bayesian nonparametric (BNP) paradigm that we have previously exploited in the analysis of single photon arrivals from single spot confocal microscopy. We benchmark our method on simulated as well as experimental data for one, two, three, and four species with data sets from both immobilized and freely diffusing molecules.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.21.214445v1?rss=1

Authors: Losakul, R., Tobar, D. E., Pimenov, A., Gutierrez, A., Schipper, R., Jehle, W. A., Postma, H. W. C.

Abstract:

Nanopores are an established paradigm in genome sequencing technology, with remarkable advances still being made today. All efforts continually address the challenges associated with rapid, accurate, high-throughput, and low cost detection, particularly with long-read length DNA. We report on the in situ melting and unzipping of long, high molecular weight DNA. At varying salt concentration, we directly compare the translocation conductance and speeds between SiN and graphene nanopores at sub-10 nm pore diameters. We observe the force-induced unzipping of dsDNA at higher salt concentrations than previously reported in literature. We observe free running translocation without secondary structures of ssDNA that is an order of magnitude longer than reported before. We hypothesize that the frayed single strands at the molecules end get captured with a higher likelihood than both ends together. In understanding this phenomena for long-read lengths, we continue to address the challenges revolving around future generations of sequencing technology.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.07.21.215111v1?rss=1

Authors: Soule, P., Illien, F., Kulifaj, S., Joliot, A., Gourier, C., Sagan, S., Cribier, S., Rodriguez, N.

Abstract:

Penetratin is a Cell Penetrating Peptide able to cross the cell plasma membrane possibly bound to a cargo molecule to be delivered into the cell. The mechanism of its entry is poorly known. A key to a molecular description of this mechanism is to identify the partners of Penetratin at the cell surface during its adhesion and internalization. We used the Biomembrane Force Probe to identify the partners during the first second of adhesion of Penetratin on the cell plasma membrane. We evidenced that heparan sulfates are the first partners after contact as well as unknown partners hidden by sialic acids. Experiments of binding of Penetratin on vesicles bearing charged or sulfated lipids showed no adhesion pointing that a negatively charged partner is not enough and there is a specificity for certain chemical groups bearing the charges. A model of the measured forces of interaction enabled to determine the adhesion energy of a Penetratin with heparan sulfates on a cell to be in the range 18 to 22 kBT.

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