Machine Learning Approaches for Metalloproteins

Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.     

The Use of the Statistical Entropy in Some New Approaches for the Description of Biosystems

Some problems of describing biological systems with the use of entropy as a measure of the complexity of these systems are considered. Entropy is studied both for the organism as a whole and for its parts down to the molecular level. Correlation of actions of various parts of the whole organism, intercellular interactions and control, as well as cooperativity on the microlevel lead to a more complex structure and lower statistical entropy. For a multicellular organism, entropy is much lower than entropy for the same mass of a colony of unicellular organisms. Cooperativity always reduces the entropy of the system; a simple example of ligand binding to a macromolecule carrying two reaction centers shows how entropy is consistent with the ambiguity of the result in the Bernoulli test scheme. Particular attention is paid to the qualitative and quantitative relationship between the entropy of the system and the cooperativity of ligand binding to macromolecules. A kinetic model of metabolism. corresponding to Schrödinger’s concept of the maintenance biosystems by “negentropy feeding”, is proposed. This model allows calculating the nonequilibrium local entropy and comparing it with the local equilibrium entropy inherent in non-living matter.     

Optimization of Biocompatibility for a Hydrophilic Biological Molecule Encapsulation System

Despite considerable advances in recent years, challenges in delivery and storage of biological drugs persist and may delay or prohibit their clinical application. Though nanoparticle-based approaches for small molecule drug encapsulation are mature, encapsulation of proteins remains problematic due to destabilization of the protein. Reverse micelles composed of decylmonoacyl glycerol (10MAG) and lauryldimethylamino-N-oxide (LDAO) in low-viscosity alkanes have been shown to preserve the structure and stability of a wide range of biological macromolecules. Here, we present a first step on developing this system as a future platform for storage and delivery of biological drugs by replacing the non-biocompatible alkane solvent with solvents currently used in small molecule delivery systems. Using a novel screening approach, we performed a comprehensive evaluation of the 10MAG/LDAO system using two preparation methods across seven biocompatible solvents with analysis of toxicity and encapsulation efficiency for each solvent. By using an inexpensive hydrophilic small molecule to test a wide range of conditions, we identify optimal solvent properties for further development. We validate the predictions from this screen with preliminary protein encapsulation tests. The insight provided lays the foundation for further development of this system toward long-term room-temperature storage of biologics or toward water-in-oil-in-water biologic delivery systems.     

Hes1调控 AKT-MDM2-p53-PTEN通路的一种物理机制

基于Hill动力学与Michaelis-Menten方程,建立理论模型研究发状分裂相关增强子1(hairy and enhancer of split 1,Hes1)调控蛋白激酶B (Protein Kinase B,AKT)-鼠双微体2 (Murine Double Minute2,MDM2)-抗癌基因p53(p53)-第10号染色体缺失的磷酸酶及张力蛋白同源的基因(Phosphatase and tensin homolog deleted on chromosome ten,PTEN)通路的一种物理机制.研究发现,Hes1通过与PTEN结合抑制PTEN表达,并调控AKT信号.表明了Hes1蛋白的合成,以及Hes1与PTEN相互作用调控AKTMDM2-p53-PTEN通路信号,将会有效地控制细胞结果 . Hes1作为AKT-MDM2-p53-PTEN信号通路中上游调节的重要因素,还可以在一定程度上通过影响p53蛋白功能,改变p53对肿瘤的抑制性.理论结果可用于预测Notch通路信号异常诱导的致癌性,并进一步揭示了Notch信号通路影响细胞AKT-MDM2-p53-PTEN通路的激活...     

2.45GHz ECR 强流等离子体源核心部件设计与实验研究

电子回旋共振(Electron Cyclotron Resonance,ECR)等离子体源能产生高电荷态离子、高流强的单电荷态离子,提供稳定的束流和良好的重复性.核心部件的设计对ECR等离子体源是至关重要的,磁场对等离子体的生成和分布有直接影响,良好的磁场可以提高等离子体的性能和效率.采用有限元分析方法对ECR等离子体源磁场进行分析与设计,得到了满足设计需求与目标的磁场位形,通过高斯计对设计的永磁环轴向磁场精确测量,发现磁场仿真结果与实验结果吻合比较好,只是轴向磁场最大值及对应位置上有点偏差.通过集成实验,研究核心部件对离子源引出束流强度的影响,引出束流稳定且强度达到7 m A.     

新的光散射体系测定蛋白质的研究

以1,6-己二胺二吖啶为荧光探针,建立了一种新的蛋白质共振散射检测体系。实验考察了该吖啶荧光探针的共振散射特征光谱、散射反应稳定性,研究了缓冲介质pH、探针浓度等参数对测定蛋白质的影响。结果表明,当pH 8.9时,1,6-己二胺二吖啶染料的散射波长为470 nm;加入BSA,反应约9 min后,体系光散射强度达到最大并维持稳定,2 h内无明显变化。当1,6-己二胺二吖啶探针(浓度1.00×10-4mol·L-1)用量为3.00 mL时,蛋白质与1,6-己二胺二吖啶的光散射增强作用显著,共振散射强度随着BSA的增加而明显增强,光散射强度与蛋白质浓度成良好线性关系,线性浓度范围为1.00～5.00 μg·mL-1,检测限(3σ/K)为0.085 μg·mL-1。测定了血清样品,浓度为2.00～4.00 μg·mL-1,回收率为98.0%～101.7%,测定偏差小于1.7％。     

Helical solitons in vector modified Korteweg–de Vries equations

We study existence of helical solitons in the vector modified Korteweg–de Vries (mKdV) equations, one of which is integrable, whereas another one is non-integrable. The latter one describes nonlinear waves in various physical systems, including plasma and chains of particles connected by elastic springs. By using the dynamical system methods such as the blow-up near singular points and the construction of invariant manifolds, we construct helical solitons by the efficient shooting method. The helical solitons arise as the result of co-dimension one bifurcation and exist along a curve in the velocity-frequency parameter plane. Examples of helical solitons are constructed numerically for the non-integrable equation and compared with exact solutions in the integrable vector mKdV equation. The stability of helical solitons with respect to small perturbations is confirmed by direct numerical simulations.     

First nucleation steps during deposition of SiO2 thin films by plasma enhanced chemical vapour deposition

The initial nucleation stages during deposition of SiO₂ by remote plasma enhanced chemical vapour deposition (PECVD) have been monitored by XPS inelastic peak shape analysis. Experiments have been carried out on two substrates, a flat ZrO₂ thin film and a silicon wafer with a native silicon oxide layer on its surface. For the two substrates it is found that PECVD SiO₂ grows in the form of islands. When the SiO₂ particles reach heights close to 10 nm they coalesce and cover completely the substrate surface. The particle formation mechanism has been confirmed by TEM observation of the particles grown on silicon substrates. The kinetic Monte Carlo simulation of the nucleation and growth of the SiO₂ particles has shown that formation of islands is favoured under PECVD conditions because the plasma species may reach the substrate surface according to off-perpendicular directions. The average energy of these species is the main parameter used to describe their angular distribution function, while the reactivity of the surface is another key parameter used in the simulations.     

Exciton states and interband optical transitions in wurtzite InGaN/GaN quantum dot nanowire heterostructures

Within the framework of the effective-mass approximation, the exciton states and interband optical transitions in In_xGa_1−xN/GaN strained quantum dot (QD) nanowire heterostructures are investigated using a variational method, in which the important built-in electric field (BEF) effects, dielectric-constant mismatch and three-dimensional confinement of the electron and hole in In_xGa_1−xN QDs are considered. We find that the strong BEF gives rise to an obvious reduction of the effective band gap of QDs and leads to a remarkable electron-hole spatial separation. The BEF, QD height and radius, and dielectric mismatch effects have a significant influence on exciton binding energy, electron interband optical transitions, and the exciton oscillator strength.