Computational design of proteins with novel structure and functions

Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence–structure–function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein–protein interactions. Challenges and future prospects of this field are also discussed.     

Coevolution of strategy and structure in complex networks with dynamical linking

We introduce a model in which individuals differ in the rate at which they seek new interactions with others, making rational decisions modeled as general symmetric two-player games. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. We provide analytic results for the limiting cases where linking dynamics is much faster than evolutionary dynamics and vice versa, and show how the individual capacity of forming new links or severing inconvenient ones maps into the problem of strategy evolution in a well-mixed population under a different game. For intermediate ranges, we investigate numerically the detailed interplay determined by these two time scales and show that the scope of validity of the analytical results extends to a much wider ratio of time scales than expected.     

Amplitudes for astrophysicists: known knowns

The use of quantum field theory to understand astrophysical phenomena is not new. However, for the most part, the methods used are those that have been developed decades ago. The intervening years have seen some remarkable developments in computational quantum field theoretic tools. In particle physics, this technology has facilitated calculations that, even ten years ago would have seemed laughably difficult. It is remarkable, then, that most of these new techniques have remained firmly within the domain of high energy physics. We would like to change this. As alluded to in the title, this paper is aimed at showcasing the use of modern on-shell methods in the context of astrophysics and cosmology. In this article, we use the old problem of the bending of light by a compact object as an anchor to pedagogically develop these new computational tools. Once developed, we then illustrate their power and utility with an application to the scattering of gravitational waves.     

分布式位移传感下的有源声学结构误差传感策略

有源声学结构是近年来提出的一种控制结构低频声辐射的有效方案,它是智能结构在噪声控制领域中的具体应用,而实现该结构的关键问题之一是近场误差传感。本文提出将分布式位移传感材料PVDF敷设于有源声学结构初、次级板表面,用有限个PVDF、对测量辐射声功率实现有源声学结构的近场误差传感。论文首先建立了有源声学结构理论模型,然后基于声辐射模态概念和PVDF传感模型,推导了PVDF形状系数理论公式,最后用一系列的计算机仿真实例给出了初、次级板PVDF形状及有源控制效果,证明所提出的方案是有效的。     

Error sensing strategy for active acoustic structure based on distributed displacement sensors

The nearfield error sensing approach, which is one of the key problems encountered in the implementation of active acoustic structure, is investigated theoretically. The basic idea involves a limited number of PVDF film pairs be boned to the surface of the primary panel and secondary panels for measuring the total radiated sound power. In this paper, first, a theoretical model associated with the active acoustic structure is established. Second, the formulae for the shape coefficient of the PVDF pairs are derived based on the acoustic radiation modes and a PVDF sensing model. Finally, a number of computer simulations are performed and the shape of the PVDF pairs and corresponding reduction in the radiated sound power are calculated. The results demonstrate the feasibility of the proposed nearfield error sensing strategy.     

Assignment of EPR transitions in a manganese-containing lipoxygenase and prediction of local structure

A new variant of lipoxygenases, one containing manganese instead of iron, is characterized by electron paramagnetic resonance (EPR) at two frequencies. In the manganous state (S(e) = 5/2), maganese lipoxygenase (MnLO) yields very broad X-band (9.2 GHz) EPR signals, extending over about 800 mT. In contrast, at W-band (94 GHz), the signal is much simplified, consisting of nested transitions centered near the free electron g-value. Computer simulation has been employed to derive estimates of the zero-field splittings for MnLO, with data from these two EPR frequencies. The general features of both X- and W-band spectra are fit, first, by simulations with S(e) = 5/2, but no nuclear hyperfine splitting. The simulations are then refined by inclusion of the hyperfine splitting. On the basis of the simulations, the ranges of zero-field splitting parameters are D = +0.07 to +0.10 cm(-1), and E/D = 0.13 to 0.23. Comparison of the value of D for MnLO with that of other manganese-containing proteins suggests that MnLO has three N-ligands to the metal center and O-ligands in the remainder of 6 coordination positions. The coordination environment of MnLO is similar to that in iron lipoxygenases.     

基于社团结构的负载传输优化策略研究

研究表明网络社团结构特征对负载传输有影响,明显社团结构特征会降低网络的承载能力.由于最短路由策略在选择路由时有一定的随机性,本文提出了一种基于社团结构的负载传输策略,减少最短路由经过的社团数量,从而降低社团边缘节点的介数.实验结果显示,该策略在保证最短路由小世界特性的同时,提升了网络的承载能力,社团划分得越准确传输优化策略效果越显著. 关键词： 优化路由策略 社团结构 复杂网络 负载传输     

Evolving Networks with Nonlinear Assignment of Weight

We propose a weighted evolving network model in which the underlying topological structure is still driven by the degree according to the preferential attachment rule while the weight assigned to the newly established edges is dependent on the degree in a nonlinear form. By varying the parameter a that controls the function determining the assignment of weight, a wide variety of power-law behaviours of the total weight distributions as well as the diversity of the weight distributions of edges are displayed. Variation of correlation and heterogeneity in the network is illustrated as well.     

Integrating network structure and dynamic information for better routing strategy on scale-free networks

We study information packet routing processes on scale-free networks by mimicking the Internet traffic delivery strategies. We incorporate both the global network structure information and local queuing information in the dynamic processes. We propose several new routing strategies to guide the packet routing. The performance of the routing strategies is measured by the average transit time of the packets as well as their dependence on the traffic amount. We find that the routing strategies which integrate both global network structure information and local dynamic information perform much better than the traditional shortest-path routing protocol which takes into account only the global topological information. Moreover, from comparative studies of these routing strategies, we observe that some of our proposed methods can decrease the average transit time of packets but the performance is closely dependent on the total amount of traffic while some other proposed methods can have good performance independent of the total amount of traffic with hyper-excellent average transit time of packets. Also, numerical results show that our proposed methods integrating network structure information and local dynamic information can work much better than the methods recently proposed in [S. Sreenivasan, R. Cohen, E. López, Z. Toroczkai, H.E. Stanley, Phys. Rev. E 75 (2007) 036105, Zhi-Xi Wu, Gang Peng, Eric W.M. Wong, Kai-Hau Yeung, J. Stat. Mech. (2008) P11002.], which only considered network structure information.     

Statistical potentials for 3D structure evaluation:From proteins to RNAs

Structure evaluation is critical to in silico 3-dimensional structure predictions for biomacromolecules such as proteins and RNAs.For proteins,structure evaluation has been paid attention over three decades along with protein folding problem,and statistical potentials have been shown to be effective and efficient in protein structure prediction and evaluation.In recent two decades,RNA folding problem has attracted much attention and several statistical potentials have been developed for RNA structure evaluation,partially with the aid of the progress in protein structure prediction.In this review,we will firstly give a brief overview on the existing statistical potentials for protein structure evaluation.Afterwards,we will introduce the recently developed statistical potentials for RNA structure evaluation.Finally,we will emphasize the perspective on developing new statistical potentials for RNAs in the near future.     

Can the structure of proteins be calculated?

In contrast to soluble proteins, membrane proteins offer the possibility, to predict their secondary structure with some reliability. Based on such predictions a set of initial conformation can be constructed on which molecular dynamics simulations are performed in order to find the most stable state. The important point is that all those degrees of freedom which change slowly in time must be varied artificially in the set of initial conformations. This procedure is demonstrated for the membrane protein bacteriorhodopsin.Dedicated to Professor W. Brenig on the occasion of his 60th birthday     

Test of cold denaturation mechanism for proteins as a function of water's structure

At low temperatures and high pressures (ranging from approximately 200 up to 700 MPa), some proteins become thermodynamically unstable by means of a phenomenon know as cold denaturation. A microscopic understanding of the mechanisms leading to cold denaturation is very difficult to develop, due in part to the complexity of the protein–solvent interactions. A possible proposal to explain the cold denaturation of proteins based on a relation between hydrophobicity and the loss of the local low-density water structure at high pressures is explained in detail. In the present paper, this mechanism is tested for the first time by means of full atom numerical simulations. In good agreement with the proposal, cold denaturation resulting in the unfolded state has been found at the high-density liquid (HDL) state of water, at which the amount of open tetragonal hydrogen bonds decreases at cooling.     

General methods for modified projective synchronization of hyperchaotic systems with known or unknown parameters

This work is concerned with the general methods for modified projective synchronization of hyperchaotic systems. A systematic method of active control is developed to synchronize two hyperchaotic systems with known parameters. Moreover, by combining the adaptive control and linear feedback methods, general sufficient conditions for the modified projective synchronization of identical or different chaotic systems with fully unknown or partially unknown parameters are presented. Meanwhile, the speed of parameters identification can be regulated by adjusting adaptive gain matrix. Numerical simulations verify the effectiveness of the proposed methods.     

Efficient quantum secure communication with a publicly known key

This paper presents a simple way for an eavesdropper to eavesdrop freely the secret message in the experimental realization of quantum communication protocol proposed by Beige et al （2002 Acta Phys. Pol. A 101 357）. Moreover, it introduces an efficient quantum secure communication protocol based on a publicly known key with decoy photons and two biased bases by modifying the original protocol. The total efficiency of this new protocol is double that of the original one. With a low noise quantum channel, this protocol can be used for transmitting a secret message. At present, this protocol is good for generating a private key efficiently,     

Glasslike structure of globular proteins and the boson peak

Vibrational spectra of proteins and topologically disordered solids display a common anomaly at low frequencies, known as boson peak. We show that such feature in globular proteins can be deciphered in terms of an energy landscape picture, as it is for glassy systems. Exploiting the tools of Euclidean random matrix theory, we clarify the physical origin of such anomaly in terms of a mechanical instability of the system. As a natural explanation, we argue that such instability is relevant for proteins in order for their molecular functions to be optimally rooted in their structures.     

Optimized routing strategy for complex network with multiple priorities

Different loads in the network require distinct Qo S standard, while present routing strategies for complex networks ignored this fact. To solve this problem, we designed a routing strategy RS-MP with multiple priorities by which packets are classified into privileged-packets and common-packets. In RS-MP, privileged-packets route by the Shortest Path Algorithm, and do not need to queue up. Common-packets' routes are determined by a new factor BJmax of the network. The BJmax stands for the largest betweenness centrality. By minimizing BJmax, the throughout capacity of the network can be maximized. The simulation results show that RS-MP can guarantee privileged-packets with the shortest path length and smallest delay, and maximized throughout capacity for common packets in the no-congestion state.     

Parameter estimation in dynamic Casimir force measurements with known periodicity

It is important to have an accurate estimate of the unknown parameters such as the separation distance between interacting materials in Casimir force measurements. Current methods tend to produce large estimation errors. In this Letter, we present a novel method based on an adaptive control approach to estimate the unknown parameters using large amplitude dynamic Casimir measurements at separation distances of below 1 μm where both electrostatic force and Casimir force are significant. The estimate is proved to be accurate and the effectiveness of our method is demonstrated via a numerical example.