A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins

Membrane proteins constitute a large portion of the human proteome and perform a variety of important functions as membrane receptors, transport proteins, enzymes, signaling proteins, and more. The computational studies of membrane proteins are usually much more complicated than those of globular proteins. Here we propose a new continuum model for Poisson-Boltzmann calculations of membrane channel proteins. Major improvements over the existing continuum slab model are as follows: 1) The location and thickness of the slab model are fine-tuned based on explicit-solvent MD simulations. 2) The highly different accessibility in the membrane and water regions are addressed with a two-step, two-probe grid labeling procedure, and 3) The water pores/channels are automatically identified. The new continuum membrane model is optimized (by adjusting the membrane probe, as well as the slab thickness and center) to best reproduce the distributions of buried water molecules in the membrane region as sampled in explicit water simulations. Our optimization also shows that the widely adopted water probe of 1.4 {\AA} for globular proteins is a very reasonable default value for membrane protein simulations. It gives an overall minimum number of inconsistencies between the continuum and explicit representations of water distributions in membrane channel proteins, at least in the water accessible pore/channel regions that we focus on. Finally, we validate the new membrane model by carrying out binding affinity calculations for a potassium channel, and we observe a good agreement with experiment results.Comment: 40 pages, 6 figures, 5 table

Attosecond time-resolved streaked photoelectron spectroscopy of transition-metal nanospheres

Citation: Li, J. X., Saydanzad, E., & Thumm, U. (2017). Attosecond time-resolved streaked photoelectron spectroscopy of transition-metal nanospheres. Physical Review A, 95(4), 11. doi:10.1103/PhysRevA.95.043423Streaked photoemission from nanostructured surfaces and nanoparticles by attosecond extreme ultraviolet pulses into an infrared (IR) or visible streaking pulse allows for sub-fs-resolution of the plasmonically enhanced streaking-pulse electric field. It thus holds promise for the time-resolved imaging of the dielectric response in and plasmonic fields near nanostructures. After calculating the plasmonic field induced by IR and visible streaking pulses in 10-to 200-nm diameter Au, Ag, and Cu nanospheres, we numerically simulated streaked photoelectron spectra within a quantum-mechanical model. Our spectra show significant oscillation-amplitude enhancements and phase shifts relative to calculations that neglect the induced plasmonic field. We trace these observable effects to the distinct dielectric properties of the three investigated metals, demonstrating the applicability of streaking spectroscopy to the element-specific investigation of induced time-dependent electric fields near nanoparticle surfaces

A Policy-Guided Imitation Approach for Offline Reinforcement Learning

Offline reinforcement learning (RL) methods can generally be categorized into two types: RL-based and Imitation-based. RL-based methods could in principle enjoy out-of-distribution generalization but suffer from erroneous off-policy evaluation. Imitation-based methods avoid off-policy evaluation but are too conservative to surpass the dataset. In this study, we propose an alternative approach, inheriting the training stability of imitation-style methods while still allowing logical out-of-distribution generalization. We decompose the conventional reward-maximizing policy in offline RL into a guide-policy and an execute-policy. During training, the guide-poicy and execute-policy are learned using only data from the dataset, in a supervised and decoupled manner. During evaluation, the guide-policy guides the execute-policy by telling where it should go so that the reward can be maximized, serving as the \textit{Prophet}. By doing so, our algorithm allows \textit{state-compositionality} from the dataset, rather than \textit{action-compositionality} conducted in prior imitation-style methods. We dumb this new approach Policy-guided Offline RL (\texttt{POR}). \texttt{POR} demonstrates the state-of-the-art performance on D4RL, a standard benchmark for offline RL. We also highlight the benefits of \texttt{POR} in terms of improving with supplementary suboptimal data and easily adapting to new tasks by only changing the guide-poicy.Comment: Oral @ NeurIPS 2022, code at https://github.com/ryanxhr/PO

Retrieving plasmonic near-field information: A quantum-mechanical model for streaking photoelectron spectroscopy of gold nanospheres

Citation: Li, J. X., Saydanzad, E., & Thumm, U. (2016). Retrieving plasmonic near-field information: A quantum-mechanical model for streaking photoelectron spectroscopy of gold nanospheres. Physical Review A, 94(5), 5. doi:10.1103/PhysRevA.94.051401Streaked photoemission from nanostructures is characterized by size-and material-dependent nanometer-scale variations of the induced nanoplasmonic response to the electronic field of the streaking pulse and thus holds promise of allowing photoelectron imaging with both subfemtosecond temporal and nanometer spatial resolution. In order to scrutinize the driven collective electronic dynamics in 10-200-nm-diameter gold nanospheres, we calculated the plasmonic field induced by streaking pulses in the infrared and visible spectral range and developed a quantum-mechanical model for streaked photoemission by extreme ultraviolet pulses. Our simulated photoelectron spectra reveal a significant amplitude enhancement and phase shift of the photoelectron streaking trace relative to calculations that exclude the induced plasmonic field. Both are most pronounced for streaking pulses tuned to the plasmon frequency and retrace the plasmonic electromagnetic field enhancement and phase shift near the nanosphere surface

The Method of Moving spheres on Hyperbolic Space and Symmetry of Solutions to a Class of PDEs

The classification of solutions of semilinear partial differential equations, as well as the classification of critical points of the corresponding functionals, have wide applications in the study of partial differential equations and differential geometry. The classical moving plane method and the moving sphere method on $\mathbb{R}^n$ provide an effective approach to capturing the symmetry of solutions. As far as we know, the moving sphere method has yet to be developed on the hyperbolic space $\mathbb{H}^n$. In the present paper, we focus on the following equation \begin{equation*} P_k u = f(u) \end{equation*} on hyperbolic spaces $\mathbb{H}^n$, where $P_k$ denotes the GJMS operators on $\mathbb{H}^n$ and $f : \mathbb{R} \to \mathbb{R}$ satisfies certain growth conditions. We develop a moving sphere approach for integral equations on $\mathbb{H}^n$, to obtain the symmetry property as well as a characterization result towards positive solutions. Our methods also rely on Helgason-Fourier analysis and Hardy-Littlewood-Sobolev inequalities on hyperbolic spaces together with a Kelvin transform we introduce on $\mathbb{H}^n$ in this paper.Comment: Some references are added and typos fixe

Inspection Plan for Dependent Multi-Characteristic Components with Multi-Classifications

In this research, a mathematical model is developed for inspecting multicharacteristic components with multi-classifications in a multistage production system. The characteristics’ defective rates are statistically dependent. The output of the model is an optimized inspection plan. The plan minimizes the total cost per accepted component. A heuristic algorithm is proposed in solving the problem with optimized solutions. The developed model and proposed heuristic algorithm are demonstrated using an example from a medical equipment manufacturing system. The data used in the example are realistic but hypothetical. The model can be modified for solving similar problems in other applications