There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Molecular self-assembly is the spontaneous association of molecules under equilibrium conditions into stable, structurally well-defined aggregates joined by noncovalent bonds. Molecular self-assembly is ubiquitous in biological systems and underlies the formation of a wide variety of complex biological structures. Understanding self-assembly and the associated noncovalent interactions that connect complementary interacting molecular surfaces in biological aggregates is a central concern in structural biochemistry. Self-assembly is also emerging as a new strategy in chemical synthesis, with the potential of generating nonbiological structures with dimensions of 1 to 10(2) nanometers (with molecular weights of 10(4) to 10(10) daltons). Structures in the upper part of this range of sizes are presently inaccessible through chemical synthesis, and the ability to prepare them would open a route to structures comparable in size (and perhaps complementary in function) to those that can be prepared by microlithography and other techniques of microfabrication.

Molecular self-assembly and nanochemistry: A chemical strategy for the synthesis of nanostructures

The halogen bond occurs when there is evidence of a net attractive interaction between an electrophilic region associated with a halogen atom in a molecular entity and a nucleophilic region in another, or the same, molecular entity. In this fairly extensive review, after a brief history of the interaction, we will provide the reader with a snapshot of where the research on the halogen bond is now, and, perhaps, where it is going. The specific advantages brought up by a design based on the use of the halogen bond will be demonstrated in quite different fields spanning from material sciences to biomolecular recognition and drug design.

The Halogen Bond

Water pollution is a global problem threatening the entire biosphere and affecting the life of many millions of people around the world. Not only is water pollution one of the foremost global risk factors for illness, diseases and death, but it also contributes to the continuous reduction of the available drinkable water worldwide. Delivering valuable solutions, which are easy to implement and affordable, often remains a challenge. Here we review the current state-of-the-art of available technologies for water purification and discuss their field of application for heavy metal ion removal, as heavy metal ions are the most harmful and widespread contaminants. We consider each technology in the context of sustainability, a largely neglected key factor, which may actually play a pivotal role in the implementation of each technology in real applications, and we introduce a compact index, the Ranking Efficiency Product (REP), to evaluate the efficiency and ease of implementation of the various technologies in this broader perspective. Emerging technologies, for which a detailed quantitative analysis and assessment is not yet possible according to this methodology, either due to scarcity or inhomogeneity of data, are discussed in the final part of the manuscript.

Sustainable technologies for water purification from heavy metals: review and analysis

Foods make up some of the most complex examples of soft condensed matter (SCM) with which we interact daily. Their complexity arises from several factors: the intricacy of components, the different aggregation states in which foods are encountered, and the multitude of relevant characteristic time and length scales. Because foodstuffs are governed by the rules of SCM physics but with all the complications related to real systems, the experimental and theoretical approaches of SCM physics have deepened our comprehension of their nature and behaviour, but many questions remain. In this review we discuss the current understanding of food science, by considering established SCM methods as well as emerging techniques and theoretical approaches. With their complexity, heterogeneity and multitude of states, foods provide SCM physics with a challenge of remarkable importance.

Understanding foods as soft materials

Self-assembled peptide and protein amyloid nanostructures have traditionally been considered only as pathological aggregates implicated in human neurodegenerative diseases. In more recent times, these nanostructures have found interesting applications as advanced materials in biomedicine, tissue engineering, renewable energy, environmental science, nanotechnology and material science, to name only a few fields. In all these applications, the final function depends on: (i) the specific mechanisms of protein aggregation, (ii) the hierarchical structure of the protein and peptide amyloids from the atomistic to mesoscopic length scales and (iii) the physical properties of the amyloids in the context of their surrounding environment (biological or artificial). In this review, we will discuss recent progress made in the field of functional and artificial amyloids and highlight connections between protein/peptide folding, unfolding and aggregation mechanisms, with the resulting amyloid structure and functionality. We also highlight current advances in the design and synthesis of amyloid-based biological and functional materials and identify new potential fields in which amyloid-based structures promise new breakthroughs.

/pdf/self-assembling-peptide-and-protein-amyloids-from-structure-3a2o3zyuoj.pdf

Self-assembling peptide and protein amyloids: from structure to tailored function in nanotechnology

The aggregation of proteins is central to many aspects of daily life, including food processing, blood coagulation, eye cataract formation disease and prion-related neurodegenerative infections(1-5). However, the physical mechanisms responsible for amyloidosis-the irreversible fibril formation of various proteins that is linked to disorders such as Alzheimer's, Creutzfeldt-Jakob and Huntington's diseases-have not yet been fully elucidated(6-9). Here, we show that different stages of amyloid aggregation can be examined by performing a statistical polymer physics analysis of single-molecule atomic force microscopy images of heat-denatured beta-lactoglobulin fibrils. The atomic force microscopy analysis, supported by theoretical arguments, reveals that the fibrils have a multistranded helical shape with twisted ribbon-like structures. Our results also indicate a possible general model for amyloid fibril assembly and illustrate the potential of this approach for investigating fibrillar systems.

/pdf/understanding-amyloid-aggregation-by-statistical-analysis-of-4pmbr699qb.pdf

Understanding amyloid aggregation by statistical analysis of atomic force microscopy images

The aggregation of proteins is of fundamental relevance in a number of daily phenomena, as important and diverse as blood coagulation, medical diseases, or cooking an egg in the kitchen. Colloidal food systems, in particular, are examples that have great significance for protein aggregation, not only for their importance and implications, which touches on everyday life, but also because they allow the limits of the colloidal science analogy to be tested in a much broader window of conditions, such as pH, ionic strength, concentration and temperature. Thus, studying the aggregation and self-assembly of proteins in foods challenges our understanding of these complex systems from both the molecular and statistical physics perspectives. Last but not least, food offers a unique playground to study the aggregation of proteins in three, two and one dimensions, that is to say, in the bulk, at air/water and oil/water interfaces and in protein fibrillation phenomena. In this review we will tackle this very ambitious task in order to discuss the current understanding of protein aggregation in the framework of foods, which is possibly one of the broadest contexts, yet is of tremendous daily relevance.

http://iopscience.iop.org/article/10.1088/0034-4885/76/4/046601/pdf

Raffaele Mezzenga

Papers

Sustainable technologies for water purification from heavy metals: review and analysis

Understanding foods as soft materials

Self-assembling peptide and protein amyloids: from structure to tailored function in nanotechnology

Understanding amyloid aggregation by statistical analysis of atomic force microscopy images

The self-assembly, aggregation and phase transitions of food protein systems in one, two and three dimensions