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

/pdf/quantum-mechanical-continuum-solvation-models-3edv963g14.pdf

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.

/pdf/the-amber-biomolecular-simulation-programs-e2nyq1ef44.pdf

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.

Cellular environments are highly crowded with biological macromolecules resulting in frequent non-specific interactions. While the effect of such crowding on protein structure and dynamics has been studied extensively, very little is known how cellular crowding affects the conformational sampling of nucleic acids. The effect of protein crowding on the conformational preferences of DNA (deoxyribonucleic acid) is described from fully atomistic molecular dynamics simulations of systems containing a DNA dodecamer surrounded by protein crowders. From the simulations, it was found that DNA structures prefer to stay in B-like conformations in the presence of the crowders. The preference for B-like conformations results from non-specific interactions of crowder proteins with the DNA sugar-phosphate backbone. Moreover, the simulations suggest that the crowder interactions narrow the conformational sampling to canonical regions of the conformational space. The overall conclusion is that crowding effects may stabilize the canonical features of DNA that are most important for biological function. The results are complementary to a previous study of DNA in reduced dielectric environments where reduced dielectric environments alone led to a conformational shift towards A-DNA. Such a shift was not observed here suggested that the reduced dielectric response of cellular environments is counteracted by non-specific interactions with protein crowders under in vivo conditions.

/pdf/role-of-protein-interactions-in-stabilizing-canonical-dna-59pvo5m0q6.pdf

Role of protein interactions in stabilizing canonical DNA features in simulations of DNA in crowded environments

The inside of a cell is highly crowded with a large number of macromolecules together with solvents and metabolites. To know the molecular-level behaviour of biomolecules in such dense crowding environment, we constructed full atomistic model of the cytoplasm of bacteria, and performed massive all-atom molecular dynamics (MD) simulations. On the other hand, to analyse such big MD data, we need significant computational power and efficient calculation methodology. Here, we introduce what and how we analyse the biomolecule properties from the big trajectory data produced by cellular scale all-atom MD simulations.

https://robots.iopscience.iop.org/article/10.1088/1742-6596/1036/1/012009/pdf

High-Performance Data Analysis on the Big Trajectory Data of Cellular Scale All-atom Molecular Dynamics Simulations.

Biomolecular condensation, especially liquid-liquid phase separation, is an important physical process with relevance for a number of different aspects of biological functions. Key questions of what drives such condensation, especially in terms of molecular composition, can be addressed via computer simulations, but the development of computationally efficient, yet physically realistic models has been challenging. Here, the coarse-grained model COCOMO is introduced that balances the polymer behavior of peptides and RNA chains with their propensity to phase separate as a function of composition and concentration. COCOMO is a residue-based model that combines bonded terms with short- and long-range terms, including a Debye-Hückel solvation term. The model is highly predictive of experimental data on phase-separating model systems. It is also computationally efficient and can reach the spatial and temporal scales on which biomolecular condensation is observed with moderate computational resources.

Modeling concentration-dependent phase separation processes involving peptides and RNA via residue-based coarse-graining

The performance of models at different resolutions is compared in the context of an iterative protein structure refinement protocol. The models considered here consist of an all-atom model described with the CHARMM22 force field in combination with a distance-dependent dielectric implicit solvent approximation, a united-atom model described by the CHARMM19 force field in combination with the effective energy function 1 (EEF1) solvent model, the new intermediate coarse-grained model PRotein Intermediate MOdel (PRIMO), both with Generalized Born and distance-dependent dielectric solvent models, and the lattice-based coarse-grained Side CHain Only (SICHO) model. It is found that the CHARMM19 and SICHO models lead to initially rapid refinement for a set consisting of 11 targets from past critical assessment of protein structure prediction (CASP) competitions, but they are eventually outperformed by the CHARMM22 and PRIMO models in consistently reaching near-native conformations over the course of 100 refinement cycles.

Conformational Sampling in Structure Prediction and Refinement with Atomistic and Coarse-Grained Models

Intramembrane proteases of diverse signaling pathways use membrane-embedded active sites to cleave membrane-associated substrates. Interactions of intramembrane metalloproteases with modulators are poorly understood. Inhibition of Bacillus subtilis intramembrane metalloprotease SpoIVFB requires BofA and SpoIVFA, which transiently prevent cleavage of Pro-{sigma}K during endosporulation. Three conserved BofA residues (N48, N61, T64) in or near predicted transmembrane segment (TMS) 2 were found to be required for SpoIVFB inhibition. Disulfide cross-linking indicated that BofA TMS2 occupies the SpoIVFB active site region. BofA and SpoIVFA neither prevented SpoIVFB from interacting with Pro-{sigma}K in co-purification assays nor interfered with cross-linking between the C-terminal regions of Pro-{sigma}K and SpoIVFB. However, BofA and SpoIVFA did interfere with cross-linking between the N-terminal Proregion of Pro-{sigma}K and the SpoIVFB active site region and interdomain linker. A BofA variant lacking predicted TMS1, in combination with SpoIVFA, was less effective at interfering with some of the cross-links and slightly less effective at inhibiting cleavage of Pro-{sigma}K by SpoIVFB. A structural model was built of SpoIVFB in complex with BofA and parts of SpoIVFA and Pro-{sigma}K, using partial homology and constraints from cross-linking and co-evolutionary analyses. The model predicts that N48 in BofA TMS2 interacts with T64 (and possibly N61) of BofA to stabilize a membrane-embedded C-terminal region. SpoIVFA is predicted to bridge the BofA C-terminal region and SpoIVFB. Thus, the two inhibitory proteins block access of the Pro-{sigma}K N-terminal region to the SpoIVFB active site region. Our findings may inform efforts to develop selective inhibitors of intramembrane metalloproteases. SignificanceIntramembrane metalloproteases (IMMPs) function in numerous signaling processes that impact health. For example, IMMPs function in pathways regulating human cholesterol levels and bacterial pathogenesis. Knowledge of IMMP interactions with modulators could inform design of therapeutics, but structures of complexes have not been reported. We found that a transmembrane segment of BofA occupies the active site region to inhibit SpoIVFB, an IMMP crucial for endosporulation of Bacillus subtilis. Because endosporulation enhances persistence of related pathogenic bacteria, our structural model of SpoIVFB in complex with BofA and parts of its other inhibitory protein SpoIVFA and its substrate Pro-{sigma}K, may lead to strategies to control endosporulation. More broadly, insights from the SpoIVFB inhibition mechanism could guide efforts to develop inhibitors of other IMMPs.

/pdf/inhibitory-proteins-block-substrate-access-to-the-active-ad1noe3ax0.pdf

Michael Feig

Papers

Role of protein interactions in stabilizing canonical DNA features in simulations of DNA in crowded environments

High-Performance Data Analysis on the Big Trajectory Data of Cellular Scale All-atom Molecular Dynamics Simulations.

Modeling concentration-dependent phase separation processes involving peptides and RNA via residue-based coarse-graining

Conformational Sampling in Structure Prediction and Refinement with Atomistic and Coarse-Grained Models

Inhibitory Proteins Block Substrate Access to the Active Site of Bacillus subtilis Intramembrane Metalloprotease SpoIVFB