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Coarse-graining of fully atomistic molecular dynamics simulations is a long-standing goal in order to allow the description of processes occurring on biologically relevant timescales. For example, the prediction of pathways, rates and rate-limiting steps in protein-ligand unbinding is crucial for modern drug discovery. To achieve the enhanced sampling, we perform dissipation-corrected targeted molecular dynamics simulations, which yield free energy and friction profiles of molecular processes under consideration. Subsequently, we use these fields to perform temperature-boosted Langevin simulations which account for the desired kinetics occurring on multisecond timescales and beyond. Adopting the dissociation of solvated sodium chloride, trypsin-benzamidine and Hsp90-inhibitor protein-ligand complexes as test problems, we reproduce rates from molecular dynamics simulation and experiments within a factor of 2–20, and dissociation constants within a factor of 1–4. Analysis of friction profiles reveals that binding and unbinding dynamics are mediated by changes of the surrounding hydration shells in all investigated systems. Protein-ligand unbinding processes are out of reach for atomistic simulations due to time-scale involved. Here the authors demonstrate an approach relying on dissipation-corrected targeted molecular dynamics that enables to provide binding and unbinding rates with a speed-up of several orders of magnitude.

Given nonstationary data from molecular dynamics simulations, a Markovian Langevin model is constructed that aims to reproduce the time evolution of the underlying process. While at equilibrium the free energy landscape is sampled, nonequilibrium processes can be associated with a biased energy landscape, which accounts for finite sampling effects and external driving. Extending the data-driven Langevin equation (dLE) approach [Phys.\\ Rev.\\ Lett.\\ 115, 050602 (2015)] to the modeling of nonequilibrium processes, an efficient way to calculate multidimensional Langevin fields is outlined. The dLE is shown to correctly account for various nonequilibrium processes, including the enforced dissociation of sodium chloride in water, the pressure-jump induced nucleation of a liquid of hard spheres, and the conformational dynamics of a helical peptide sampled from nonstationary short trajectories.

Coarse-graining of fully atomistic molecular dynamics simulations is a long-standing goal in order to allow the description of processes occurring on biologically relevant timescales. For example, the prediction of pathways, rates and rate-limiting steps in protein-ligand unbinding is crucial for modern drug discovery. To achieve the enhanced sampling, we first perform dissipation-corrected targeted molecular dynamics simulations, which yield free energy and friction profiles of the molecular process under consideration. In a second step, we use these fields to perform temperature-boosted Langevin simulations which account for the desired molecular kinetics occurring on multisecond timescales and beyond. Adopting the dissociation of solvated sodium chloride as well as trypsin-benzamidine and Hsp90-inhibitor protein-ligand complexes as test problems, we are able to reproduce rates from molecular dynamics simulation and experiments within a factor of 2-20, and dissociation constants within a factor of 1-4. Analysis of the friction profiles reveals that binding and unbinding dynamics are mediated by changes of the surrounding hydration shells in all investigated systems.

With growing complexity and criticality of automated driving functions in road traffic and their operational design domains (ODD), there is increasing demand for covering significant proportions of development, validation, and verification in virtual environments and through simulation models. If, however, simulations are meant not only to augment real-world experiments, but to replace them, quantitative approaches are required that measure to what degree and under which preconditions simulation models adequately represent reality, and thus, using their results accordingly. Especially in R&D areas related to the safety impact of the \"open world\", there is a significant shortage of real-world data to parameterize and/or validate simulations - especially with respect to the behavior of human traffic participants, whom automated driving functions will meet in mixed traffic. We present an approach to systematically acquire data in public traffic by heterogeneous means, transform it into a unified representation, and use it to automatically parameterize traffic behavior models for use in data-driven virtual validation of automated driving functions.

Allosteric communication between distant protein sites represents a key mechanism of biomolecular regulation and signal transduction. Compared to other processes such as protein folding, however, the dynamical evolution of allosteric transitions is still not well understood. As example of allosteric coupling between distant protein regions, we consider the global open-closed motion of the two domains of T4 lysozyme, which is triggered by local motions in the hinge region. Combining extensive molecular dynamics simulations with machine learning of contact features, we identify a network of interresidue distances that move in a concerted manner. The cooperative process originates from a cogwheel-like motion of the hydrophobic core in the hinge region, which constitutes a flexible transmission network. Through rigid contacts and the protein backbone, the small local changes of the hydrophobic core are passed on to the distant terminal domains and lead to the emergence of a rare global conformational transition. As in an Ising-type model, the cooperativity of the allosteric transition can be explained via the interaction of local fluctuations. Competing Interest Statement The authors have declared no competing interest.

With growing complexity and responsibility of automated driving functions in road traffic and growing scope of their operational design domains, there is increasing demand for covering significant parts of development, validation, and verification via virtual environments and simulation models. If, however, simulations are meant not only to augment real-world experiments, but to replace them, quantitative approaches are required that measure to what degree and under which preconditions simulation models adequately represent reality, and thus allow their usage for virtual testing of driving functions. Especially in research and development areas related to the safety impacts of the \"open world\", there is a significant shortage of real-world data to parametrize and/or validate simulations - especially with respect to the behavior of human traffic participants, whom automated vehicles will meet in mixed traffic. This paper presents the intermediate results of the German AVEAS research project (www.aveas.org) which aims at developing methods and metrics for the harmonized, systematic, and scalable acquisition of real-world data for virtual verification and validation of advanced driver assistance systems and automated driving, and establishing an online database following the FAIR principles.

The evolutionary origins of the hypoxia-sensitive cells that trigger amniote respiratory reflexes – carotid body glomus cells, and ‘pulmonary neuroendocrine cells’ (PNECs) - are obscure. Homology has been proposed between glomus cells, which are neural crest-derived, and the hypoxia-sensitive ‘neuroepithelial cells’ (NECs) of fish gills, whose embryonic origin is unknown. NECs have also been likened to PNECs, which differentiate in situ within lung airway epithelia. Using genetic lineage-tracing and neural crest-deficient mutants in zebrafish, and physical fate-mapping in frog and lamprey, we find that NECs are not neural crest-derived, but endoderm-derived, like PNECs, whose endodermal origin we confirm. We discover neural crest-derived catecholaminergic cells associated with zebrafish pharyngeal arch blood vessels, and propose a new model for amniote hypoxia-sensitive cell evolution: endoderm-derived NECs were retained as PNECs, while the carotid body evolved via the aggregation of neural crest-derived catecholaminergic (chromaffin) cells already associated with blood vessels in anamniote pharyngeal arches. The carotid bodies are small glands found in either side of our neck, near the carotid artery. When the level of oxygen in our blood drops, specialized cells in the carotid bodies signal to the brain to increase our heart rate and make us breathe more rapidly and deeply. As a result, more oxygen is delivered to our cells. Fish have similar oxygen-sensitive cells in their gills, known as neuroepithelial cells, that detect changes in the oxygen levels in the surrounding water and their blood. It has been suggested that after our vertebrate (back-boned animal) ancestors moved onto land, the neuroepithelial cells in their gills eventually evolved to form the carotid bodies. Knowing whether this is true would allow researchers to better understand how our ancestors were able to adapt to an obligate air-breathing lifestyle on land. If the carotid body did evolve from ancestral neuroepithelial cells, we would expect that they would both develop from the same kind of cells in the embryo. Carotid body cells develop from a group of cells called neural crest cells, which give rise to many tissues, including nerve cells. Hockman et al. have now investigated whether neuroepithelial cells also develop from neural crest cells. Hockman et al. labelled the neural crest cells in the embryos of zebrafish, frogs and lampreys using techniques such as injecting the cells with fluorescent dye or genetically modifying the cells to make fluorescent proteins. Unexpectedly, the neuroepithelial cells that developed in the gills of these embryos did not contain these fluorescent labels, meaning that they did not develop from the neural crest cells. The patterns of gene activity found in the developing neuroepithelial cells were also different from those in the carotid body. Further investigation revealed that neuroepithelial cells develop from the lining of the mouth and gills and may be related to a similar population of oxygen-sensitive cells found in the lungs. Overall, it appears that the carotid body did not evolve from ancestral neuroepithelial cells. However, Hockman et al. did find some cells near blood vessels in the gills of zebrafish that had developed from neural crest cells. Equivalent cells in our ancestors could therefore be the cells that evolved into carotid bodies. A first test of this theory will be to determine whether or not these cells are oxygen-sensitive.

We map human artery and vein endothelial cell (EC) differentiation from pluripotent stem cells, and employ this roadmap to discover new mechanisms of vascular development (vein differentiation) and disease (viral infection). We discovered vein development unfolds in two steps driven by opposing signals: VEGF differentiates mesoderm into \"pre-vein\" ECs, but surprisingly, VEGF/ERK inhibition subsequently specifies vein ECs. Pre-vein ECs co-expressed certain arterial ( SOX17 ) and venous ( APLNR ) markers, harbored poised chromatin at future venous genes, but completed venous differentiation only upon VEGF inhibition. Intersectional lineage tracing revealed that early Sox17 + Aplnr + ECs also formed veins in vivo . Next, we compared how Ebola, Andes, and Nipah viruses infect artery and vein ECs under biosafety-level-4 containment. Each virus distinctly affected ECs. Interestingly, artery and vein ECs also responded divergently to the same virus, thus revealing that developmentally-specified cell identity impacts viral infection. Collectively, this arteriovenous differentiation roadmap illuminates vascular development and disease.We map human artery and vein endothelial cell (EC) differentiation from pluripotent stem cells, and employ this roadmap to discover new mechanisms of vascular development (vein differentiation) and disease (viral infection). We discovered vein development unfolds in two steps driven by opposing signals: VEGF differentiates mesoderm into \"pre-vein\" ECs, but surprisingly, VEGF/ERK inhibition subsequently specifies vein ECs. Pre-vein ECs co-expressed certain arterial ( SOX17 ) and venous ( APLNR ) markers, harbored poised chromatin at future venous genes, but completed venous differentiation only upon VEGF inhibition. Intersectional lineage tracing revealed that early Sox17 + Aplnr + ECs also formed veins in vivo . Next, we compared how Ebola, Andes, and Nipah viruses infect artery and vein ECs under biosafety-level-4 containment. Each virus distinctly affected ECs. Interestingly, artery and vein ECs also responded divergently to the same virus, thus revealing that developmentally-specified cell identity impacts viral infection. Collectively, this arteriovenous differentiation roadmap illuminates vascular development and disease.

Despite substantial insight into mechanisms underlying arterial blood vessel development, multiple aspects of vein development remain elusive, including vein-determining extracellular signals and cell-fate trajectories . One might expect arteries and veins to arise simultaneously during development, as both are needed for a functional circulatory system. Nevertheless, arteries often precede veins , as exemplified by the first intraembryonic blood vessels . Here we present a model of vein differentiation that answers longstanding questions in the field. By reconstituting human vein endothelial cell (EC) differentiation from mesoderm , we discovered that vein development unfolds in two steps driven by opposing signals. First, VEGF is necessary to differentiate mesoderm into \"pre-vein\" ECs-a newly-defined intermediate state-and to endow endothelial identity. Second, once cells have acquired pre-vein EC identity, VEGF/ERK inhibition is necessary to specify vein ECs. Pre-vein ECs co-expressed certain arterial (SOX17) and venous (APLNR) markers and harbored poised chromatin at future venous genes. However, VEGF/ERK inhibition was necessary to activate poised venous genes (e.g., ), and for pre-vein ECs to complete venous differentiation. Intersectional lineage tracing supported a pre-vein intermediate step : early Sox17+ Aplnr+ ECs also formed veins in mouse embryos. We leveraged this developmental knowledge for disease modeling by differentiating human pluripotent stem cells into artery and vein ECs, and comparing their responses to Ebola and Andes viruses under biosafety-level-4 containment. Artery and vein ECs responded divergently to the same virus, thus revealing that developmentally specified cell identity impacts viral infection. Taken together, we propose a two-step model for vein development wherein VEGF first differentiates mesoderm into pre-vein ECs, but subsequent VEGF/ERK inhibition generates vein ECs. VEGF activation is thought to be broadly essential for vascular development , and thus our discovery that VEGF/ERK inhibition specifies vein identity has potential implications for understanding current therapies that either activate or inhibit VEGF signaling .

Extracellular signals and cell-fate trajectories during vein development remain elusive, despite trailblazing insights into artery development. Here we exploit human pluripotent stem cell differentiation and mouse embryology to present a model that answers longstanding questions: vein endothelial cell (EC) differentiation unfolds in two steps driven by opposing extracellular signals. First, VEGF differentiates mesoderm into “primed” ECs, newly-defined progenitors that co-express certain arterial (SOX17) and venous (APLNR) markers. Second, primed ECs execute vein differentiation upon VEGF/ERK inhibition; however, upon VEGF activation they can instead form artery ECs. The arteriovenous plasticity of primed ECs was supported by intersectional lineage tracing. Future venous genes including NR2F2 harbor poised chromatin in primed ECs, but are only transcribed upon VEGF/ERK inhibition. SOXF transcription factors, including SOX17, confer primed ECs with vein differentiation competence. Collectively, this two-step vein differentiation model—entailing primed EC intermediates and VEGF/ERK inhibition to trigger vein differentiation—has implications for VEGF-modulating therapies.