丝氨酸蛋白酶中催化三元组内氢键的作用

为了探究丝氨酸蛋白酶催化效率的来源,本文分别研究了丝氨酸酶催化水解多肽CI2、MCTI-A和六肽(SUB)的过程中催化三元组内的氢键所起的作用. 首先采用QM/MM-MD方法计算了在酶-底物复合物和过渡态下组氨酸和天冬氨酸之间质子转移的自由能曲线. 结果表明低能垒氢键仅在CI2酰化反应的过渡态区域形成,而在MCTI-A和SUB酰化反应中均是正常氢键. 与MCTI-A相比,CI2和SUB体系中氢键强度在过渡态时显著增强,因此相应的酰化反应能垒明显降低. 过渡态区域形成的低能垒氢键显然有助于加速酰化反应,同时研究也表明正常氢键也有可能降低能垒. 氢键降低能垒的关键则在于过渡态下氢键强度的增加程度,而不是其是否生成了低能垒氢键. 本文为研究催化三元组间的氢键在丝氨酸蛋白酶中的作用提供了新思路,并有助于理解丝氨酸蛋白酶中催化三元组的催化机制.     

长链脂肪酸影响胆红素-人血清蛋白复合物的激发态分化

胆红素与人血清白蛋白结合后会发生光异构和光诱导环化反应,其中后一反应将最终形成一种名为光红素的产物,这些光诱导化学反应是临床上治疗新生儿黄疸的基本原理. 据前人研究报道,长链脂肪酸的加入有利于光红素的生成,但其背后的机理,特别是其激发态动力学尚不明确. 本文利用飞秒瞬态吸收和飞秒荧光转换技术,探究了棕榈酸对胆红素在血清蛋白中的光化学反应的影响. 研究表明,随着棕榈酸的加入,光激发后的胆红素更倾向于通过4 ps的衰减通道返回热基态,而不是通过固有的超快激发态衰减途径(小于1 ps). 这一效应促进了热基态的胆红素发生由Z-Z到E-Z构型的异构化,从而提高了光红素的产率. 这是首次利用飞秒时间分辨光谱技术对长链脂肪酸在光疗过程中的作用进行表征,其结果可为相关临床研究提供有利的信息.     

基于接触数引导的迭代多组独立分子动力学模拟实现配体-蛋白质结合与解离过程

配体的结合与解离过程在蛋白质实现其生物学功能方面非常关键,因此对这些高度动态过程的研究变得非常重要. 尽管已有实验方法可以确定蛋白质-配体复合物的三维结构,但一般仅可获得静态图片. 随着计算机算力的快速提高以及算法的优化,分子动力学模拟在探索配体的结合与解离过程方面具有诸多优势. 然而,当系统变得足够大时,分子动力学模拟的时间和空间尺度成为了巨大的挑战. 本工作提出了一种研究配体-蛋白质结合与解离的增强采样工具,它基于配体和蛋白质之间形成的接触数来引导迭代多组独立分子动力学模拟. 在腺苷酸激酶的模拟结果中,观测到配体的结合和解离过程,而使用传统分子动力学模拟在同一时间尺度下则无法实现这一过程.     

气体-表面相互作用中动量和能量分量间转化机制的分子动力学研究

气体分子与壁面之间的相互作用是影响稀薄气体流动状态的主要因素,但是由于其物理上的复杂性和微观性,这一过程的机理并没有得到充分揭示.本文利用分子束法对Ar分子在金属Pt表面的碰撞过程进行了分子动力学模拟,并探究了入射速度、角度和壁面粗糙度对动量、能量转化机制的影响.结果表明,当气体分子以5o的极角入射时,分子的法向速度分量占主导因素,在与壁面发生碰撞之后,分子的切向和法向动量都会损失,法向动能会向切向转移,并且当分子速度不低于2.0时,切向和法向动能的比值会稳定在一个很小的区间,而粗糙度对动量和能量转化的影响不明显.与小角度入射时不同,当气体分子以75o的极角与金属表面碰撞时,粗糙度的影响就不能再被忽略了.大极角入射的气体分子在光滑壁面散射之后,其运动规律基本符合Maxwell所假设的镜面反射,动量和能量分量的变化都不明显.而粗糙度的引入则会促进气体分子切向动量和能量向法向转移,并且会使分子总能量的损失更加显著.     

Why Do Big Data and Machine Learning Entail the Fractional Dynamics?

Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks.     

Matrix Product State Simulations of Non-Equilibrium Steady States and Transient Heat Flows in the Two-Bath Spin-Boson Model at Finite Temperatures

Simulating the non-perturbative and non-Markovian dynamics of open quantum systems is a very challenging many body problem, due to the need to evolve both the system and its environments on an equal footing. Tensor network and matrix product states (MPS) have emerged as powerful tools for open system models, but the numerical resources required to treat finite-temperature environments grow extremely rapidly and limit their applications. In this study we use time-dependent variational evolution of MPS to explore the striking theory of Tamascelli et al. (Phys. Rev. Lett. 2019, 123, 090402.) that shows how finite-temperature open dynamics can be obtained from zero temperature, i.e., pure wave function, simulations. Using this approach, we produce a benchmark dataset for the dynamics of the Ohmic spin-boson model across a wide range of coupling strengths and temperatures, and also present a detailed analysis of the numerical costs of simulating non-equilibrium steady states, such as those emerging from the non-perturbative coupling of a qubit to baths at different temperatures. Despite ever-growing resource requirements, we find that converged non-perturbative results can be obtained, and we discuss a number of recent ideas and numerical techniques that should allow wide application of MPS to complex open quantum systems.     

Transient Dynamics in the Random Growth and Reset Model

A mean-field type model with random growth and reset terms is considered. The stationary distributions resulting from the corresponding master equation are relatively easy to obtain; however, for practical applications one also needs to know the convergence to stationarity. The present work contributes to this direction, studying the transient dynamics in the discrete version of the model by two different approaches. The first method is based on mathematical induction by the recursive integration of the coupled differential equations for the discrete states. The second method transforms the coupled ordinary differential equation system into a partial differential equation for the generating function. We derive analytical results for some important, practically interesting cases and discuss the obtained results for the transient dynamics.     

Spectral Properties of Effective Dynamics from Conditional Expectations

The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffusion processes, a general procedure to find effective equations is the conditioning approach. In this paper, we are interested in the spectrum of the generator of the resulting effective dynamics, and how it compares to the spectrum of the full generator. We prove a new relative error bound in terms of the eigenfunction approximation error for reversible systems. We also present numerical examples indicating that, if Kramers–Moyal (KM) type approximations are used to compute the spectrum of the reduced generator, it seems largely insensitive to the time window used for the KM estimators. We analyze the implications of these observations for systems driven by underdamped Langevin dynamics, and show how meaningful effective dynamics can be defined in this setting.     

Experimental study of bubble dynamics in the neighbourhood of a vertical incomplete boundary

The bubbles have been widely used in biomedical field, military and chemical industry. The liquid jet generated by the bubble collapse through an orifice is utilized in needle-free injections and inkjet printing. In this paper we devised synchronized triggering equipment, experimentally investigated the mechanism in the interaction of an electric-spark generated a single bubble and a vertical wall with an air-back opening. Detailed observations were recorded and described for bubble oscillation, migration, jetting, as well as the high-speed water spike penetrating through the opening. The results revealed that there was a critical value of the bubble-wall distance, below which the bubble was directed away from the incomplete boundary, while the bubble may tear from the middle for larger distance. As the distance varied, we studied the volume of the water that rushed through the opening, the velocity at the tip of the water spike, and the center of the bubble as well as the migration of the bubble boundary. This work reveals that the high-speed water spike caused by the bubble may be a potential threat to the structures, specifically for cases with a small opening size and short bubble-boundary distance.     

Simulation and experiment of the cooling effect of trapped ion by pulsed laser

We investigate the process of pulsed laser cooling using a self-constructed molecular dynamics simulation(MDSimulation) program. We simulate the Doppler cooling process and pulsed laser Doppler cooling process of a single ~(40)Ca~+ ion, and the comparison with the experimental results shows that this self-constructed MD-Simulation program works well in the weak laser intensity situation. Furthermore, we analyze the pulsed laser Doppler cooling process of a single ~(27)Al~+ ion. This program can be used to analyze the molecular dynamic process of various situations of Doppler cooling in an ion trap, which could give predictions and experimental guidance.