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

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.

Combined quantum-mechanics/molecular-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomolecular systems. Quantum-mechanical (QM) methods are required for describing chemical reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based molecular mechanics (MM) methods. Thus to model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region (e.g., substrates and co-factors in an enzymatic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.

QM/MM Methods for Biomolecular Systems

With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology.

https://www.wellbeingintlstudiesrepository.org/cgi/viewcontent.cgi?article=1109&context=acwp_arte

Toxicity testing in the 21st century: a vision and a strategy

The Brønsted–Evans–Polanyi relation and the volcano curve in heterogeneous catalysis

The Brønsted-Evans-Polanyi relation and the volcano plot for ammonia synthesis over transition metal catalysts

Dihydrofolate reductase (DHFR) catalyzes the reduction of dihydrofolate to tetrahydrofolate. The catalytic rate in this system has been found to be significantly affected by mutations far from the site of chemical activity in the enzyme [Rajagopalan, P. T. R, Lutz, S., and Benkovic, S. J. (2002) Biochemistry 41, 12618-12628]. On the basis of extensive computer simulations for wild-type DHFR from Escherichia coli and four mutants (G121S, G121V, M42F, and M42F/G121S), we show that key parameters for catalysis are changed. The parameters we study are relative populations of different conformations sampled and hydrogen bonds. We find that the mutations result in long-range structural perturbations, rationalizing the effects that the mutations have on the kinetics of the enzyme. Such perturbations also provide a rationalization for the reported nonadditivity effect for double mutations. We finally examine the role a structural perturbation will have on the hydride transfer step. On the basis of our new findings, we discuss the role of coupled motions between distant regions in the enzyme, which previously was reported by Radkiewicz and Brooks.

Correlated motion and the effect of distal mutations in dihydrofolate reductase

Density functional theory (DFT) calculations of reaction paths and energies for the industrial and the biological catalytic ammonia synthesis processes are compared. The industrial catalyst is modeled by a ruthenium surface, while the active part of the enzyme is modeled by a MoFe6S9 complex. In contrast to the biological process, the industrial process requires high temperatures and pressures to proceed, and an explanation of this important difference is discussed. The possibility of a metal surface catalyzed process running at low temperatures and pressures is addressed, and DFT calculations have been carried out to evaluate its feasibility. The calculations suggest that it might be possible to catalytically produce ammonia from molecular nitrogen at low temperatures and pressures, in particular if energy is fed into the process electrochemically.

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Ammonia synthesis at low temperatures

We discuss problems related to in silico studies of enzymes and show that accurate and converged free energy changes for complex chemical reactions can be computed if a method based on a thermodynamic cycle is employed. The method combines the sampling speed of molecular mechanics with the accuracy of a high-level quantum mechanics method. We use the method to compute the free energy barrier for a methyl transfer reaction catalyzed by the enzyme catechol O-methyltransferase at the level of density functional theory. The surrounding protein and solvent are found to have a profound effect on the reaction, and we show that energies can be extrapolated easily from one basis set and exchange-correlation functional to another. Using this procedure we calculate a barrier of 69 kJ/mol, in excellent agreement with the experimental value of 75 kJ/mol.

Quantum mechanical free energy barrier for an enzymatic reaction

We recently described a method to compute accurate quantum mechanical free energies [Rod, T. H.; Ryde, U. Phys. Rev. Lett. 2005, 94, 138302]. The method, which we term quantum mechanical thermodynamic cycle perturbation (QTCP), employs a molecular mechanics force field to sample phase space and, subsequently, a thermodynamic cycle to estimate QM/MM free energy changes. Here, we discuss the methodology in detail and test an approach based on a different thermodynamic cycle. We also show that a new way of treating hydrogen link atoms makes the free energy changes converge faster and that extrapolation to higher accuracy can be performed. We finally discuss the quantum mechanical free energy (QM/MM-FE) method in the framework of the QTCP method. All methods considered are applied to the methylation of catecholate catalyzed by catechol O-methyltransferase. We compute the free energy barrier for the reaction by computing free energy changes in steps between fixed QM regions along a predetermined reaction pathway. Using the QTCP approach, an extrapolated activation free energy of 69 kJ/mol for the forward reaction and 90 kJ/mol for the reverse reaction are obtained at the level of the B3LYP functional and the 6-311++G(2d,2p) basis set. The value for the forward reaction is in excellent agreement with the experimental value of 75 kJ/mol. Results based on the QM/MM-FE method differ by less than 10 kJ/mol from those values, indicating that QM/MM-FE may be a fairly accurate and cheap alternative to calculate QM/MM free energy changes. Moreover, the results are compared to barriers obtained with a fixed molecular mechanics environment as well as with structures optimized in a vacuum. All the computed free energy barriers are well converged. A major approximation in the current implementation of the QTCP method is that the QM region is fixed. The approximation leads to well-converged free energy barriers, which has been a problem in similar studies.

Thomas H. Rod

Papers

The Brønsted-Evans-Polanyi relation and the volcano plot for ammonia synthesis over transition metal catalysts

Correlated motion and the effect of distal mutations in dihydrofolate reductase

Ammonia synthesis at low temperatures

Quantum mechanical free energy barrier for an enzymatic reaction

Accurate QM/MM free energy calculations of enzyme reactions: Methylation by catechol O-methyltransferase