Lee G. Pedersen

Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems

An N⋅log(N) method for evaluating electrostatic energies and forces of large periodic systems is presented. The method is based on interpolation of the reciprocal space Ewald sums and evaluation of the resulting convolutions using fast Fourier transforms. Timings and accuracies are presented for three large crystalline ionic systems.

A smooth particle mesh Ewald method

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.

New tricks for modelers from the crystallography toolkit: the particle mesh Ewald algorithm and its use in nucleic acid simulations

We thank the North Carolina Supercomputing Center, the Pittsburgh Supercomputing Center and the National Cancer Institute Supercomputing Center for access to resources. LGP thanks the National Institutes of Health for HL-06350 and the National Institute of Environmental Health Sciences (NIEHS) for access to their facilities.

The effect of long‐range electrostatic interactions in simulations of macromolecular crystals: A comparison of the Ewald and truncated list methods

Simulations of the HIV‐1 protease unit cell using a 9 A cutoff, 9/18 A ‘‘twin‐range’’ cutoff, and full Ewald sums have been carried out to 300 ps. The results indicate that long‐range electrostatic interactions are essential for proper representation of the HIV‐1 protease crystal structure. The 9 A simulation did not converge in 300 ps. Inclusion of a 9/18 A ‘‘twin‐range’’ cutoff showed significant improvement. Simulation using the Ewald summation convention gave the best overall agreement with x‐ray crystallographic data, and showed the least internal differences in the time average structures of the asymmetric units. The Ewald simulation represents an efficient implementation of the Particle Mesh Ewald method [Darden et al., J. Chem. Phys. 98, 10 089 (1993)], and illustrates the importance of including long‐range electrostatic forces in large macromolecular systems.

Crystal structure of estrogen sulphotransferase.

The structure of estrogen sulphotransferase has been solved in the presence of inactive cofactor PAP and substrate 17β-estradiol. This structure reveals structural similarities between cytosolic sulphotransf erases and nucleotide kinases.

Gene assessment and sample classification for gene expression data using a genetic algorithm/k-nearest neighbor method.

Recent tools that analyze microarray expression data have exploited correlation-based approaches such as clustering analysis. We describe a new method for assessing the importance of genes for sample classification based on expression data. Our approach combines a genetic algorithm (GA) and the k-nearest neighbor (KNN) method to identify genes that jointly can discriminate between two types of samples (e.g. normal vs. tumor). First, many such subsets of differentially expressed genes are obtained independently using the GA. Then, the overall frequency with which genes were selected is used to deduce the relative importance of genes for sample classification. Sample heterogeneity is accommodated; that is, the method should be robust against the existence of distinct subtypes. We applied GA / KNN to expression data from normal versus tumor tissue from human colon. Two distinct clusters were observed when the 50 most frequently selected genes were used to classify all of the samples in the data sets stu died and the majority of samples were classified correctly. Identification of a set of differentially expressed genes could aid in tumor diagnosis and could also serve to identify disease subtypes that may benefit from distinct clinical approaches to treatment.

Towards accurate solvation dynamics of divalent cations in water using the polarizable amoeba force field: From energetics to structure

Molecular dynamics simulations were performed using a modified amoeba force field to determine hydration and dynamical properties of the divalent cations Ca2+ and Mg2+. The extension of amoeba to divalent cations required the introduction of a cation specific parametrization. To accomplish this, the Thole polarization damping model parametrization was modified based on the ab initio polarization energy computed by a constrained space orbital variation energy decomposition scheme. Excellent agreement has been found with condensed phase experimental results using parameters derived from gas phase ab initio calculations. Additionally, we have observed that the coordination of the calcium cation is influenced by the size of the periodic water box, a recurrent issue in first principles molecular dynamics studies.

Dephosphorylation of Threonine 38 Is Required for Nuclear Translocation and Activation of Human Xenobiotic Receptor CAR (NR1I3)

Upon activation by therapeutics, the nuclear xenobiotic/ constitutive active/androstane receptor (CAR) regulates various liver functions ranging from drug metabolism and excretion to energy metabolism. CAR can also be a risk factor for developing liver diseases such as hepatocellular carcinoma. Here we have characterized the conserved threonine 38 of human CAR as the primary residue that regulates nuclear translocation and activation of CAR. Protein kinase C phosphorylates threonine 38 located on the α-helix spanning from residues 29–42 that constitutes a part of the first zinc finger and continues into the region between the zinc fingers. Molecular dynamics study has revealed that this phosphorylation may destabilize this helix, thereby inactivating CAR binding to DNA as well as sequestering it in the cytoplasm. We have found, in fact, that helix-stabilizing mutations reversed the effects of phosphorylation. Immunohistochemical study using an anti-phospho-threonine 38 peptide antibody has, in fact, demonstrated that the classic CAR activator phenobarbital dephosphorylates the corresponding threonine 48 of mouse CAR in the cytoplasm of mouse liver and translocates CAR into the nucleus. These results define CAR as a cell signal-regulated constitutive active nuclear receptor. These results also provide phosphorylation/dephosphorylation of the threonine as the primary drug target for CAR activation.

Phenobarbital Indirectly Activates the Constitutive Active Androstane Receptor (CAR) by Inhibition of Epidermal Growth Factor Receptor Signaling

The epidermal growth factor receptor is an unexpected target of the barbiturate phenobarbital. Antagonistic Activation Phenobarbital stimulates the transcription of genes in the liver that encode drug metabolism enzymes by indirectly stimulating the constitutive active androstane receptor (CAR). Mutoh et al. identified epidermal growth factor receptor (EGFR) as a cell surface binding target of phenobarbital. Phenobarbital bound to EGFR and blocked the binding of the ligand EGF, thereby preventing the activation of EGFR. This inhibition of EGFR promoted the activation of CAR. Molecular simulation predicted that phenobarbital and EGF share binding sites on EGFR. Together, the findings indicate that phenobarbital stimulates the nuclear activity of CAR by inhibiting the activity of EGFR at the cell surface. Phenobarbital is a central nervous system depressant that also indirectly activates nuclear receptor constitutive active androstane receptor (CAR), which promotes drug and energy metabolism, as well as cell growth (and death), in the liver. We found that phenobarbital activated CAR by inhibiting epidermal growth factor receptor (EGFR) signaling. Phenobarbital bound to EGFR and potently inhibited the binding of EGF, which prevented the activation of EGFR. This abrogation of EGFR signaling induced the dephosphorylation of receptor for activated C kinase 1 (RACK1) at Tyr52, which then promoted the dephosphorylation of CAR at Thr38 by the catalytic core subunit of protein phosphatase 2A. The findings demonstrated that the phenobarbital-induced mechanism of CAR dephosphorylation and activation is mediated through its direct interaction with and inhibition of EGFR.

An Atomic Model for the Pleated β-Sheet Structure of Aβ Amyloid Protofilaments

Abstract Synchrotron x-ray studies on amyloid fibrils have suggested that the stacked pleated β -sheets are twisted so that a repeating unit of 24 β -strands forms a helical turn around the fibril axis (Sunde et al., 1997. J. Mol. Biol . 273:729–739). Based on this morphological study, we have constructed an atomic model for the twisted pleated β -sheet of human A β amyloid protofilament. In the model, 48 monomers of A β 12–42 stack (four per layer) to form a helical turn of β -sheet. Each monomer is in an antiparallel β -sheet conformation with a turn located at residues 25–28. Residues 17–21 and 31–36 form a hydrophobic core along the fibril axis. The hydrophobic core should play a critical role in initializing A β aggregation and in stabilizing the aggregates. The model was tested using molecular dynamics simulations in explicit aqueous solution, with the particle mesh Ewald (PME) method employed to accommodate long-range electrostatic forces. Based on the molecular dynamics simulations, we hypothesize that an isolated protofilament, if it exists, may not be twisted, as it appears to be when in the fibril environment. The twisted nature of the protofilaments in amyloid fibrils is likely the result of stabilizing packing interactions of the protofilaments. The model also provides a binding mode for Congo red on A β amyloid fibrils. The model may be useful for the design of A β aggregation inhibitors.