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

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.

We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.

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The Amber biomolecular simulation programs

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecu- lar simulation program. It has been developed over the last three decades with a primary focus on molecules of bio- logical interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estima- tors, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numer- ous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

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CHARMM: the biomolecular simulation program.

The surface of a molecule determines much of its chemical and physical property, and is of great interest and importance. In this Letter, we introduce the concept of molecular multiresolution surfaces as a new paradigm of multiscale biological modeling. Molecular multiresolution surfaces contain not only a family of molecular surfaces, corresponding to different probe radii, but also the solvent accessible surface and van der Waals surface as limiting cases. All the proposed surfaces are generated by a novel approach, the diffusion map of continuum solvent over the van der Waals surface of a molecule. A new local spectral evolution kernel is introduced for the numerical integration of the diffusion equation in a single time step.

Molecular multiresolution surfaces

Influenza fusion peptide is critical for mediating the fusion of viral and host cell membranes during viral entry. The interaction of monomeric influenza fusion peptide with membranes is studied with replica exchange molecular dynamics simulations using a new implicit membrane model to effectively reach microsecond to millisecond time scales. The conformational sampling of the fusion peptide was studied as a function of different N- and C-termini, including an experimental construct with an additional C-terminal tag, as well as a function of protonation of acidic residues. It is found that the influenza fusion peptide mostly adopts helical structures with a pronounced kink at residues 11—13 with both N-terminal and C-terminal helices oriented mostly parallel to the membrane surface. A charged C-terminus and the presence of a charge C-terminal tag significantly alters the conformational sampling of the fusion peptide and results in more diverse conformational ensembles that include obliquely inserted N-terminal peptide structures. Protonation of acidic residues also affects the conformational sampling, however, based on pK a shift estimates the overall effect of pH = 5 on the conformational sampling of the influenza fusion peptide appears to be only minor.

Conformational Sampling of Influenza Fusion Peptide in Membrane Bilayers as a Function of Termini and Protonation States

Implicit models of membrane environments offer computational advantages in simulations of membrane-interacting proteins and peptides. Such methods are especially useful for studies of long time scale processes, such as folding and aggregation, or very large complexes that are otherwise intractable with explicit lipid environments. Implicit models replace explicit solute-solvent interactions with a mean-field approach. In the most physical models, continuum dielectric electrostatics is combined with empirical formulations for the nonpolar components of the free energy of solvation. The practical use of a number of implicit membrane models ranging from the empirical IMM1 method to generalized Born-based methods with two-dielectric and multidielectric representations of biological membrane characteristics is presented.

Implicit membrane models for membrane protein simulation.

Functional divergence between duplicate transcription factors (TFs) has been linked to critical events in the evolution of land plants and can result from changes in patterns of expression, binding site divergence, and/or interactions with other proteins. Although plant TFs tend to be retained post polyploidization, many are lost within tens to hundreds of million years. Thus, it can be hypothesized that some TFs in plant genomes are in the process of becoming pseudogenes. Here, we use a pair of salt tolerance-conferring transcription factors, DWARF AND DELAYED FLOWERING1 (DDF1) and DDF2, that duplicated through paleopolyploidy 50 to 65 million years ago, as examples to illustrate potential mechanisms leading to duplicate retention and loss. We found that the expression patterns of Arabidopsis thaliana (At)DDF1 and AtDDF2 have diverged in a highly asymmetric manner, and AtDDF2 has lost most inferred ancestral stress responses. Consistent with promoter disablement, the AtDDF2 promoter has fewer predicted cis-elements and a methylated repetitive element. Through comparisons of AtDDF1, AtDDF2, and their Arabidopsis lyrata orthologs, we identified significant differences in binding affinities and binding site preference. In particular, an AtDDF2-specific substitution within the DNA-binding domain significantly reduces binding affinity. Cross-species analyses indicate that both AtDDF1 and AtDDF2 are under selective constraint, but among A. thaliana accessions, AtDDF2 has a higher level of nonsynonymous nucleotide diversity compared with AtDDF1. This may be the result of selection in different environments or may point toward the possibility of ongoing functional decay despite retention for millions of years after gene duplication.

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Michael Feig

Papers

Molecular multiresolution surfaces

Conformational Sampling of Influenza Fusion Peptide in Membrane Bilayers as a Function of Termini and Protonation States

Implicit membrane models for membrane protein simulation.

Molecular Evidence for Functional Divergence and Decay of a Transcription Factor Derived from Whole-Genome Duplication in Arabidopsis thaliana

Large scale distributed data repository: design of a molecular dynamics trajectory database