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

The previously developed particle mesh Ewald method is reformulated in terms of efficient B‐spline interpolation of the structure factors This reformulation allows a natural extension of the method to potentials of the form 1/rp with p≥1 Furthermore, efficient calculation of the virial tensor follows Use of B‐splines in place of Lagrange interpolation leads to analytic gradients as well as a significant improvement in the accuracy We demonstrate that arbitrary accuracy can be achieved, independent of system size N, at a cost that scales as N log(N) For biomolecular systems with many thousands of atoms this method permits the use of Ewald summation at a computational cost comparable to that of a simple truncation method of 10 A or less

A smooth particle mesh Ewald method

CHARMM (Chemistry at HARvard Macromolecular Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromolecular systems. The program can read or model build structures, energy minimize them by first- or second-derivative techniques, perform a normal mode or molecular dynamics simulation, and analyze the structural, equilibrium, and dynamic properties determined in these calculations. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.

CHARMM: A program for macromolecular energy, minimization, and dynamics calculations

6.2.2. Definition of Effective Properties 3064 6.3. Response Properties to Magnetic Fields 3066 6.3.1. Nuclear Shielding 3066 6.3.2. Indirect Spin−Spin Coupling 3067 6.3.3. EPR Parameters 3068 6.4. Properties of Chiral Systems 3069 6.4.1. Electronic Circular Dichroism (ECD) 3069 6.4.2. Optical Rotation (OR) 3069 6.4.3. VCD and VROA 3070 7. Continuum and Discrete Models 3071 7.1. Continuum Methods within MD and MC Simulations 3072

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Quantum mechanical continuum solvation models.

Solvation. a molecular dynamics study of a dipeptide in water

Erratum: Enhanced surface hydrophobicity by coupling of surface polarity and topography (Proceedings of the National Academy of Sciences of the United States of America (2009) 106 (15181-15185) DOI: 10.1073/pnas.0905468106)

Coarse-grained simulations of conjugated polymers have become a popular way of investigating the device physics of organic photovoltaics. While UV-Vis spectroscopy remains one of key experimental methods for the interrogation of these devices, a rigorous bridge between coarse-grained simulations and spectroscopy has never been established. Here we address this challenge by developing a method that predicts spectra of conjugated polymers directly from coarse-grained representations while avoiding ad-hoc procedures such as back-mapping from coarse-grained to atomistic representations followed by computing the spectra using standard quantum chemistry methods. Our approach is based on a generative deep learning model: the long-short-term memory recurrent neural network (LSTM-RNN) and it is suggested by the apparent similarity between natural languages and the mathematical structure of the perturbative expansions of the excited state energies due to small fluctuations of the polymer conformation. We use this model to demonstrate a dangerous discrepancy between the spectra obtained in the coarse-grained representation and after the back-mapping. This indicates that standard protocols may require additional fine-tuning in order to become reliable and that our model presents a novel tool uniquely suited for improving the back-mapping protocols and for including spectral data in the development of coarse-grained potentials.

Prediction of optical spectra of coarse-grained polymers as a sequence generation problem: the Recurrent Neural Networks solution

We investigate the thermal stability of helical hydrophobic oligomers using a three-dimensional, water-explicit lattice model and the Wang–Landau Monte Carlo method. The degree of oligomer helicity is controlled by the parameter emm < 0, which mimics monomer–monomer hydrogen bond interactions leading to the formation of helical turns in atomistic proteins. We vary |emm| between 0 and 4.5 kcal/mol and therefore investigate systems ranging from flexible homopolymers (i.e., those with no secondary structure) to helical oligomers that are stable over a broad range of temperatures. We find that systems with |emm| ≤ 2.0 kcal/mol exhibit a broad thermal unfolding transition at high temperature, leading to an ensemble of random coils. In contrast, the structure of conformations involved in a second, low-temperature, transition is strongly dependent on |emm|. Weakly helical oligomers are observed when |emm| ≤ 1.0 kcal/mol and exhibit a low-temperature, cold-unfolding-like transition to an ensemble of strongly wate...

Thermal stability of hydrophobic helical oligomers: a lattice simulation study in explicit water.

Computer simulation of quantum systems in solution are allowing the direct observation of electronic dynamics of solutes at a molecular level on the same timescale as that probed by ultrafast transient spectroscopy. Here, we describe some of our recent theoretical approaches to the analysis of electronic spectroscopy and relaxation dynamics in solution, and outline some of the recent results obtained for the experimentally probed cases of energetic excess electrons in liquid water and for an aqueous halide ion.

Peter J. Rossky

Papers

Solvation. a molecular dynamics study of a dipeptide in water

Erratum: Enhanced surface hydrophobicity by coupling of surface polarity and topography (Proceedings of the National Academy of Sciences of the United States of America (2009) 106 (15181-15185) DOI: 10.1073/pnas.0905468106)

Prediction of optical spectra of coarse-grained polymers as a sequence generation problem: the Recurrent Neural Networks solution

Thermal stability of hydrophobic helical oligomers: a lattice simulation study in explicit water.

Simulation of Electronic Spectroscopy and Relaxation in Aqueous Solution