PaperPlayer biorxiv biophysics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.10.289546v1?rss=1

Authors: Ganichkin, O., Vancraenenbroeck, R., Rosenblum, G., Hofmann, H., Mikhailov, A. S., Daumke, O., Noel, J. K.

Abstract:

The mechano-chemical GTPase dynamin assembles on membrane necks of clathrin-coated vesicles into helical oligomers that constrict and eventually cleave the necks in a GTP-dependent way. It remains not clear whether dynamin achieves this via molecular motor activity and, if so, by what mechanism. Here, we used ensemble kinetics, single-molecule FRET and molecular dynamics simulations to characterize dynamin's GTPase cycle and determine the powerstroke strength. The results were incorporated into a coarse-grained structural model of dynamin filaments on realistic membrane templates. Working asynchronously, dynamin's motor modules were found to collectively constrict a membrane tube. Force is generated by motor dimers linking adjacent helical turns and constriction is accelerated by their strain-dependent dissociation. Consistent with experiments, less than a second is needed to constrict a membrane tube to the hemi-fission radius. Thus, a membrane remodeling mechanism relying on cooperation of molecular ratchet motors driven by GTP hydrolysis has been revealed.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.10.291948v1?rss=1

Authors: Wang, W., Hansmann, U. H. E.

Abstract:

ABSTRACT In systemic amyloidosis, Serum amyloid A (SAA) fibril deposits cause widespread damages to tissues and organs that eventually may lead to death. A therapeutically intervention therefore has either to dissolve these fibrils or inhibit their formation. However, only recently has the human SAA fibril structure be resolved at a resolution that is sufficient for development of drug candidates. Here, we use molecular dynamic simulations to probe the factors that modulate the stability of this fibril model. Our simulations suggest that fibril formation starts with the stacking of two misfolded monomers into metastable dimers, with the stacking depending on the N-terminal amyloidogenic regions of different chains forming anchors. The resulting dimers pack in a second step into a two-fold two-layer tetramer that is stable enough to nucleate fibril formation. The stability of the initial dimers is enhanced under acidic conditions by a strong salt bridge and side-chain hydrogen bond network in the C-terminal cavity (residues 23 - 51) but not affected by the presence of the disordered C-terminal tail.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.11.293639v1?rss=1

Authors: Purkait, D., Bandyopadhyay, D., Mishra, P. P.

Abstract:

Integration Host Factor (IHF) is a heterodimeric site-specific nucleoid-associated protein (NAP) well known for its DNA bending ability. The binding is mediated through the narrow minor grooves of the consensus sequence, involving van der-Waals interaction and hydrogen bonding. Although the DNA bend state of IHF has been captured by both X-ray Crystallography and Atomic Force Microscopy (AFM), the range of flexibility and degree of heterogeneity in terms of quantitative analysis of the nucleoprotein complex has largely remained unexplored. Here we have monitored and compared the trajectories of the conformational dynamics of a dsDNA upon binding of wild-type (wt) and single-chain (sc) IHF at millisecond resolution through single-molecule FRET (smFRET). Our findings reveal that the nucleoprotein complex exists in a Slacked-Dynamic state throughout the observation window where many of them have switched between multiple Wobbling States in the course of attainment of packaged form. A range of DNA Flexure Angles has been calculated that give us vital insights regarding the nucleoid organization and transcriptional regulation in prokaryotes. This study opens up an opportunity to improve the understanding of the functions of other nucleoid-associated proteins (NAPs) by complementing the previous detailed atomic-level structural analysis, which eventually will allow accessibility towards a better hypothesis.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.11.293266v1?rss=1

Authors: Khan, H. M., Guo, J., Duff, H. J., Tieleman, D. P., Noskov, S. Y.

Abstract:

The human ether-a-go-go-related gene (hERG) encodes the voltage gated potassium channel (KCNH2 or Kv11.1, commonly known as hERG). This channel plays a pivotal role in the stability of phase 3 repolarization of the cardiac action potential. Although a high-resolution cryo-EM structure is available for its depolarized (open) state, the structure surprisingly did not feature many functionally important interactions established by previous biochemical and electrophysiology experiments. Using Molecular Dynamics Flexible Fitting (MDFF), we refined the structure and recovered the missing functionally relevant salt bridges in hERG in its depolarized state. We also performed electrophysiology experiments to confirm the functional relevance of a novel salt bridge predicted by our refinement protocol. Our work shows how refinement of a high-resolution cryo-EM structure helps to bridge the existing gap between the structure and function in the voltage-sensing domain (VSD) of hERG.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.11.293258v1?rss=1

Authors: Rynkiewicz, P. X., Babbitt, G. A., Cui, F. X., Hudson, A. O., Lynch, M. L.

Abstract:

Comparative functional analysis of the binding interactions between various betacoronavirus strains and their potential human target proteins, such as ACE1, ACE2 and CD26, is critical to our future understanding and combating of COVID-19. Here, employing large replicate sets of GPU accelerated molecular dynamics simulations, we statistically compare atom fluctuations of the known human target proteins in both the presence and absence of different strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. We identify a common interaction site between the N-terminal helices of ACE2 and the viral RBD in all strains (hCoV-OC43, hCoV-HKU1, MERS-CoV, SARS-CoV1, and SARS-CoV-2) and a second more dynamically complex RBD interaction site involving the ACE2 amino acid sites K353, Q325, and a novel motif, AAQPFLL (386-392) in the more recent cross-species spillovers (i.e. absent in hCoV-OC43). We use computational mutagenesis to further confirm the functional relevance of these sites. We propose a "one touch/two touch" model of viral evolution potentially involved in functionally facilitating binding interactions in zoonotic spillovers. We also observe these two touch sites governing RBD binding activity in simulations on hybrid models of the suspected viral progenitor, batCoV-HKU4, interacting with both the human SARS target, ACE2, and the human MERS target, CD26. Lastly, we confirm that the presence of a common hypertension drug (lisinopril) within the target site of SARS-CoV-2 bound models of ACE1 and ACE2 acts to enhance the RBD interactions at the same key sites in our proposed model. In the near future, we recommend that our comparative computational analysis identifying these key viral RBD-ACE2 binding interactions be supplemented with comparative studies of site-directed mutagenesis in order to screen for current and future coronavirus strains at high risk of zoonotic transmission to humans.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.10.290932v1?rss=1

Authors: Kumar, A., Kumar, A., Kumar, P., Garg, N., Giri, R.

Abstract:

Nonstructural protein 1 (NSP1) of SARS-CoV-2 plays a key role in downregulation of RIG-I pathways and interacts with 40 S ribosome. Recently, the cryo-EM structure in complex with 40S ribosome is deciphered. However, the structure of full length NSP1 without any partner has not been studies. Also, the conformation of NSP1-C terminal region in isolation is not been studied. In this study, we have investigated the conformational dynamics of NSP1C-terminal region (NSP1-CTR; amino acids 130-180) in isolation and under different solvent environments. The NSP1-CTR is found to be intrinsically disordered in aqueous solution. Further, we used alpha helix inducer, trifluoroethanol, and found induction of alpha helical conformation using CD spectroscopy. Additionally, in the presence of SDS, NSP1-CTR is showing a conformational change from disordered to ordered, possibly gaining alpha helix in part. But in presence of neutral lipid DOPC, a slight change in conformation is observed. This implies the possible role of hydrophobic interaction and electrostatic interaction on the conformational changes of NSP1. The changes in structural conformation were further studied by fluorescence-based studies, which showed significant blue shift and fluorescence quenching in the presence of SDS and TFE. Lipid vesicles also showed fluorescence-based quenching. In agreement to these result, fluorescence lifetime and fluorescence anisotropy decay suggests a change in conformational dynamics. The zeta potential studies further validated that the conformational dynamics is mostly because of hydrophobic interaction. In last, these experimental studies were complemented through Molecular Dynamics (MD) simulation which have also shown a good correlation and testify our experiments. We believe that the intrinsically disordered nature of the NSP1-CTR will have implications in disorder based binding promiscuity with its interacting proteins.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.10.276980v1?rss=1

Authors: Ulicna, K., Vallardi, G., Charras, G., Lowe, A. R.

Abstract:

Single-cell methods are beginning to reveal the intrinsic heterogeneity in cell populations, which arises from the interplay or deterministic and stochastic processes. For example, the molecular mechanisms of cell cycle control are well characterised, yet the observed distribution of cell cycle durations in a population of cells is heterogenous. This variability may be governed either by stochastic processes, inherited in a deterministic fashion, or some combination of both. Previous studies have shown poor correlations within lineages when observing direct ancestral relationships but remain correlated with immediate relatives. However, assessing longer-range dependencies amid noisy data requires significantly more observations, and demands the development of automated procedures for lineage tree reconstruction. Here, we developed an open-source Python library, btrack, to facilitate retrieval of deep lineage information from live-cell imaging data. We acquired 3,500 hours of time-lapse microscopy data of epithelial cells in culture and used our software to extract 22,519 fully annotated single-cell trajectories. Benchmarking tests, including lineage tree reconstruction assessments, demonstrate that our approach yields high-fidelity results and achieves state-of-the-art performance without the requirement for manual curation of the tracker output data. To demonstrate the robustness of our supervision-free cell tracking pipeline, we retrieve cell cycle durations and their extended inter- and intra-generational family relationships, for up to eight generations, and up to fourth cousin relationships. The extracted lineage tree dataset represents approximately two orders of magnitude more data, and longer-range dependencies, than in previous studies of cell cycle heritability. Our results extend the range of observed correlations and suggest that strong heritable cell cycling is present. We envisage that our approach could be extended with additional live-cell reporters to provide a detailed quantitative characterisation of biochemical and mechanical origins to cycling heterogeneity in cell populations.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.09.290650v1?rss=1

Authors: Alimohamadi, H., Bell, M., Halpain, S., Rangamani, P.

Abstract:

Dendritic spines are small, bulbous protrusions along the dendrites of neurons and are sites of excitatory postsynaptic activity. The morphology of spines has been implicated in their function in synaptic plasticity and their shapes have been well-characterized, but the potential mechanics underlying their shape development and maintenance have not yet been fully understood. In this work, we explore the mechanical principles that could underlie specific shapes using a minimal biophysical model of membrane-actin interactions. Using this model, we first identify the possible force regimes that give rise to the classic spine shapes - stubby, filopodia, thin, and mushroom-shaped spines. We also use this model to investigate how the spine neck might be stabilized using periodic rings of actin or associated proteins. Finally, we use this model to predict that the cooperation between force generation and ring structures can regulate the energy landscape of spine shapes across a wide range of tensions. Thus, our study provides insights into how mechanical aspects of actin-mediated force generation and tension can play critical roles in spine shape maintenance.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.09.289876v1?rss=1

Authors: Munoz-Gil, G., Romero, C., Mateos, N., de Llobet Cucalon, L. I., Beato, M., Lewenstein, M., Garcia-Parajo, M. F., Torreno-Pina, J. A.

Abstract:

Phase separation is emerging as key principle in the spatiotemporal organization of living cells. Given its relevance in the regulation of numerous biological functions, including gene transcription and chromatin architecture, modeling biomolecular condensation is gaining interest. Yet, most models developed so far rely on specific descriptions and/or experimentally inaccessible properties. Here we propose a theoretical model, where phase separation is explained by means of interaction probabilities between particles. With minimum model requirements, particle condensates emerge above a critical interaction probability. We tested the model predictions with single molecule experiments of tunable transcription factor condensates in the nucleus of living cells. Phase separation, condensate sizes, diffusion behavior, and mobility parameters, quantified by data analysis and machine learning, are fully recapitulated by our model. Our combined theoretical and experimental approach provides a general framework to investigate the biophysical parameters controlling phase separation in living cells and in other soft matter-based interacting systems.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.09.09.289116v1?rss=1

Authors: Bitran, A., Jacobs, W. M., Shakhnovich, E.

Abstract:

Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions.Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a protein's folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation methods. Our algorithm, which is available online ,, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease.

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