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

Microfabricated integrated circuits revolutionized computation by vastly reducing the space, labor, and time required for calculations. Microfluidic systems hold similar promise for the large-scale automation of chemistry and biology, suggesting the possibility of numerous experiments performed rapidly and in parallel, while consuming little reagent. While it is too early to tell whether such a vision will be realized, significant progress has been achieved, and various applications of significant scientific and practical interest have been developed. Here a review of the physics of small volumes (nanoliters) of fluids is presented, as parametrized by a series of dimensionless numbers expressing the relative importance of various physical phenomena. Specifically, this review explores the Reynolds number Re, addressing inertial effects; the Peclet number Pe, which concerns convective and diffusive transport; the capillary number Ca expressing the importance of interfacial tension; the Deborah, Weissenberg, and elasticity numbers De, Wi, and El, describing elastic effects due to deformable microstructural elements like polymers; the Grashof and Rayleigh numbers Gr and Ra, describing density-driven flows; and the Knudsen number, describing the importance of noncontinuum molecular effects. Furthermore, the long-range nature of viscous flows and the small device dimensions inherent in microfluidics mean that the influence of boundaries is typically significant. A variety of strategies have been developed to manipulate fluids by exploiting boundary effects; among these are electrokinetic effects, acoustic streaming, and fluid-structure interactions. The goal is to describe the physics behind the rich variety of fluid phenomena occurring on the nanoliter scale using simple scaling arguments, with the hopes of developing an intuitive sense for this occasionally counterintuitive world.

/pdf/microfluidics-fluid-physics-at-the-nanoliter-scale-4bpahtd8qa.pdf

Microfluidics: Fluid physics at the nanoliter scale

http://experimentationlab.berkeley.edu/sites/default/files/AFMImages/butt_AFM.pdf

Force measurements with the atomic force microscope: Technique, interpretation and applications

https://science.sciencemag.org/content/sci/265/5178/1599.full.pdf

Entropic elasticity of lambda-phage DNA

Essentially all the biological functions of DNA depend on site-specific DNA-binding proteins finding their targets, and therefore 'searching' through megabases of non-target DNA. In this article, we review current understanding of how this sequence searching is done. We review how simple diffusion through solution may be unable to account for the rapid rates of association observed in experiments on some model systems, primarily the Lac repressor. We then present a simplified version of the 'facilitated diffusion' model of Berg, Winter and von Hippel, showing how non-specific DNA-protein interactions may account for accelerated targeting, by permitting the protein to sample many binding sites per DNA encounter. We discuss the 1-dimensional 'sliding' motion of protein along non-specific DNA, often proposed to be the mechanism of this multiple site sampling, and we discuss the role of short-range diffusive 'hopping' motions. We then derive the optimal range of sliding for a few physical situations, including simple models of chromosomes in vivo, showing that a sliding range of approximately 100 bp before dissociation optimizes targeting in vivo. Going beyond first-order binding kinetics, we discuss how processivity, the interaction of a protein with two or more targets on the same DNA, can reveal the extent of sliding and we review recent experiments studying processivity using the restriction enzyme EcoRV. Finally, we discuss how single molecule techniques might be used to study the dynamics of DNA site-specific targeting of proteins.

/pdf/how-do-site-specific-dna-binding-proteins-find-their-targets-3fyuckbumx.pdf

How do site‐specific DNA‐binding proteins find their targets?

Interphase chromosomes undergo constrained diffusional motion in living cells.

The long chromosomal DNAs of cells are organized into loop domains much larger in size than individual DNA-binding enzymes, presenting the question of how formation of such structures is controlled. We present a model for generation of defined chromosomal loops, based on molecular machines consisting of two coupled and oppositely directed motile elements which extrude loops from the double helix along which they translocate, while excluding one another sterically. If these machines do not dissociate from DNA (infinite processivity), a disordered, exponential steady-state distribution of small loops is obtained. However, if dissociation and rebinding of the machines occurs at a finite rate (finite processivity), the steady state qualitatively changes to a highly ordered ‘stacked’ configuration with suppressed fluctuations, organizing a single large, stable loop domain anchored by several machines. The size of the resulting domain can be simply regulated by boundary elements, which halt the progress of the extrusion machines. Possible realizations of these types of molecular machines are discussed, with a major focus on structural maintenance of chromosome complexes and also with discussion of type I restriction enzymes. This mechanism could explain the geometrically uniform folding of eukaryote mitotic chromosomes, through extrusion of pre-programmed loops and concomitant chromosome compaction.

/pdf/self-organization-of-domain-structures-by-dna-loop-extruding-4o4yr0zm4t.pdf

Self-organization of domain structures by DNA-loop-extruding enzymes

The conformation of long supercoiled DNA loops under near physiological conditions has been the subject of a long series of laboratory and Monte Carlo experiments, and impressive agreement between theory and experiment has been achieved [1–2]. A closed unnicked DNA loop has fixed linking number: this constraint leads to a competition between twisting and bending (writhing) elastic energy which drives plectonemic supercoiling. However, entropy, as manifest through a fluctuation induced repulsive force, overwhelms this elastic effect for fractional linking number perturbations ∣σ∣ 0.02, plectonemic supercoils are stable, but thermal fluctuations continue to play an important role, competing with bending and twisting elastic energy to set the superhelical radius. We have constructed an analytic theory for this effect that agrees well with experiment [3], using methods from polymer statistical mechanics.

John F. Marko

Papers

Entropic elasticity of lambda-phage DNA

How do site‐specific DNA‐binding proteins find their targets?

Interphase chromosomes undergo constrained diffusional motion in living cells.

Self-organization of domain structures by DNA-loop-extruding enzymes

Statistical mechanics of supercoiled DNA