Recent advances in single molecule fluorescence experiments and theory allow a direct comparison and improved interpretation of experiment and simulation. To this end, force fields for a larger number of dyes are required which are compatible with and can be integrated into existing biomolecular force fields. Here, we developed, characterized, and implemented AMBER-DYES, a modular fluorescent label force field, for a set of 22 fluorescent dyes and their linkers from the Alexa, Atto, and Cy families, which are in common use for single molecule spectroscopy experiments. The force field is compatible with the AMBER protein force fields and the GROMACS molecular dynamics simulation program. The high electronic polarizability of the delocalized π-electron orbitals, as found in many fluorescent dyes, poses a particular challenge to point charge based force fields such as AMBER. To quantify the charge fluctuations due to the electronic polarizability, we simulated the 22 dyes in explicit solvent and sampled the charge fluctuations using QM/MM simulations at the B3LYP/6-31G*//TIP3P level of theory. The analysis of the simulations enabled us to derive ensemble fitted RESP charges from the solvated charge distributions of multiple trajectories. We observed broad, single peaked charge distributions for the conjugated ring atoms with well-defined mean values. The charge fitting procedure was validated against published charges of the dyelike amino acid tryptophan, which showed good agreement with existing tryptophan parameters from the AMBER, CHARMM, and OPLS force field families. A principal component analysis of the charge fluctuations revealed that a small number of collective coordinates suffices to describe most of the in-plane dye polarizability. The AMBER-DYES force field allows the rapid preparation of all atom molecular dynamics simulations of fluorescent systems for state of the art multi microsecond trajectories.

There has been considerable debate on the existence of a low-barrier hydrogen bond (LBHB) in the photoactive yellow protein (PYP). The debate was initially triggered by the neutron diffraction study of Yamaguchi et al. ( Proc. Natl. Acad. Sci., U. S. A. , 2009 , 106 , 440 - 444 ) who suggested a model in which a neutral Arg52 residue triggers the formation of the LBHB in PYP. Here, we present an alternative model that is consistent within the error margins of the Yamaguchi structure factors. The model explains an increased hydrogen bond length without nuclear quantum effects and for a protonated Arg52. We tested both models by calculations under crystal, solution, and vacuum conditions. Contrary to the common assumption in the field, we found that a single PYP in vacuum does not provide an accurate description of the crystal conditions but instead introduces strong artifacts, which favor a LBHB and a large H NMR chemical shift. Our model of the crystal environment was found to stabilize the two Arg52 hydrogen bonds and crystal water positions for the protonated Arg52 residue in free MD simulations and predicted an Arg52 pK upshift with respect to PYP in solution. The crystal and solution environments resulted in almost identical H chemical shifts that agree with NMR solution data. We also calculated the effect of the Arg52 protonation state on the LBHB in 3D nuclear equilibrium density calculations. Only the charged crystal structure in vacuum supports a LBHB if Arg52 is neutral in PYP at the previously reported level of theory ( J. Am. Chem. Soc. , 2014 , 136 , 3542 - 3552 ). We attribute the anomalies in the interpretation of the neutron data to a shift of the potential minimum, which does not involve nuclear quantum effects and is transferable beyond the Yamaguchi structure.

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In the absence of a stable fold, transient secondary structure kinetics define the native state of the prototypical and pharmacologically relevant intrinsically disordered protein (IDP) α-Synuclein (aS). Here, we investigate kinetics preventing ordering and possibly pathogenic β-sheet aggregation. Interestingly, transient β-sheets form frequently at sub μs time scales precisely at the positions observed in aS amyloid fibrils. The formation kinetics competes with rapid secondary structure dissociation rates, thus explaining the low secondary structure content. The fast secondary structure dissociation times are very similar to the dynamics of tertiary structure rearrangements. These findings suggest that the fast dissociation kinetics slows down conformational selection processes for aS aggregation, which may be a general mechanism controlling the aggregation kinetics of IDPs.

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Automakers manage vast fleets of connected vehicles and face an ever-increasing demand for their sensor readings. This demand originates from many stakeholders, each potentially requiring different sensors from different vehicles. Currently, this demand remains largely unfulfilled due to a lack of systems that can handle such diverse demands efficiently. Vehicles are usually passive participants in data acquisition, each continuously reading and transmitting the same static set of sensors. However, in a multi-tenant setup with diverse data demands, each vehicle potentially needs to provide different data instead. We present a system that performs such vehicle-specific minimization of data acquisition by mapping individual data demands to individual vehicles. We collect personal data only after prior consent and fulfill the requirements of the GDPR. Non-personal data can be collected by directly addressing individual vehicles. The system consists of a software component natively integrated with a major automaker’s vehicle platform and a cloud platform brokering access to acquired data. Sensor readings are either provided via near real-time streaming or as recorded trip files that provide specific consistency guarantees. A performance evaluation with over 200,000 simulated vehicles has shown that our system can increase server capacity on-demand and process streaming data within 269 ms on average during peak load. The resulting architecture can be used by other automakers or operators of large sensor networks. Native vehicle integration is not mandatory; the architecture can also be used with retrofitted hardware such as OBD readers.

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