Christian Bartels

CHARMM: The biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological 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 estimators, 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 numerous 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.

The program XEASY for computer-supported NMR spectral analysis of biological macromolecules.

SummaryA new program package, XEASY, was written for interactive computer support of the analysis of NMR spectra for three-dimensional structure determination of biological macromolecules. XEASY was developed for work with 2D, 3D and 4D NMR data sets. It includes all the functions performed by the precursor program EASY, which was designed for the analysis of 2D NMR spectra, i.e., peak picking and support of sequence-specific resonance assignments, cross-peak assignments, cross-peak integration and rate constant determination for dynamic processes. Since the program utilizes the X-window system and the Motif widget set, it is portable on a wide range of UNIX workstations. The design objective was to provide maximal computer support for the analysis of spectra, while providing the user with complete control over the final resonance assignments. Technically important features of XEASY are the use and flexible visual display of ‘strips’, i.e., two-dimensional spectral regions that contain the relevant parts of 3D or 4D NMR spectra, automated sorting routines to narrow down the selection of strips that need to be interactively considered in a particular assignment step, a protocol of resonance assignments that can be used for reliable bookkeeping, independent of the assignment strategy used, and capabilities for proper treatment of spectral folding and efficient transfer of resonance assignments between spectra of different types and different dimensionality, including projected, reduced-dimensionality triple-resonance experiments.

Multidimensional adaptive umbrella sampling: Applications to main chain and side chain peptide conformations

A new adaptive umbrella sampling technique for molecular dynamics simulations is described. The high efficiency of the technique renders multidimensional adaptive umbrella sampling possible and thereby enables uniform sampling of the conformational space spanned by several degrees of freedom. The efficiency is achieved by using the weighted histogram analysis method to combine the results from different simulations, by a suitable extrapolation scheme to define the umbrella potential for regions that have not been sampled, and by a criterion to identify simulations during which the system was not in equilibrium. The technique is applied to two test systems, the alanine dipeptide and the threonine dipeptide, to sample the configurational space spanned by one or two dihedral angles. The umbrella potentials applied at the end of each adaptive umbrella sampling run are equal to the negative of the corresponding potentials of mean force. The trajectories obtained in the simulations can be used to calculate dynamical variables that are of interest. An example is the distribution of the distance between the HN and the Hβ proton that can be important for the interpretation of NMR experiments. Factors influencing the accuracy of the calculated quantities are discussed. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1450–1462, 1997

GARANT‐a general algorithm for resonance assignment of multidimensional nuclear magnetic resonance spectra

A new program for automatic resonance assignment of nuclear magnetic resonance (NMR) spectra of proteins, GARANT (General Algorithm for Resonance AssignmeNT), is introduced. Three principal elements used in this approach are: (a) representation of resonance assignments as an optimal match of two graphs describing, respectively, peaks expected from combined knowledge of the primary structure and the magnetization transfer pathways in the spectra used, and experimentally observed peaks; (b) a scoring scheme able to distinguish between correct and incorrect resonance assignments; and (c) combination of an evolutionary algorithm with a local optimization routine. The score that evaluates the match of expected peaks to observed peaks relies on the agreement of the information available about these peaks, most prominently, but not exclusively, the chemical shifts. Tests show that the combination of an evolutionary algorithm and a local optimization routine yields results that are clearly superior to those obtained when using either of the two techniques separately in the search for the correct assignments. GARANT is laid out for assignment problems involving peaks observed in two‐ and three‐dimensional homonuclear and heteronuclear NMR spectra of proteins.

Automated sequence-specific NMR assignment of homologous proteins using the program GARANT.

SummaryThe program GARANT (General Algorithm for Resonance AssignmeNT) for automated sequence-specific NMR assignment of proteins is based on the mapping of peaks predicted from the amino acid sequence onto the peaks observed in multidimensional spectra [C. Bartels, P. Güntert, M. Billeter and K. Wüthrich (1996) J. Comput. Chem., manuscript submitted for publication]. In this paper we demonstrate the potential of GARANT for the assignment of homologous proteins when either the three-dimensional structure or the chemical shifts of the parent protein are known. In these applications, GARANT utilizes supplementary information either in the form of interatomic distances derived from the three-dimensional structure, in order to add nuclear Overhauser effects reflecting the tertiary structure to the list of expected peaks, or in the form of the chemical shifts of the parent protein, in order to obtain a better estimate of the positions of the expected peaks. The procedure is illustrated with three different proteins: (i) a mutant form of Tendamistat (74 residues), using homonuclear 2D 1H NMR spectra and either the three-dimensional structure or the chemical shifts of the wild-type protein; (ii) the mutant Antp(C39S, W56S) homeodomain (68 residues), using homonuclear 2D 1H NMR spectra and the three-dimensional structure of the Antp(C39S) homeodomain; and (iii) free cyclophilin A (165 residues), using heteronuclear 3D NMR spectra and the three-dimensional structure of a cyclophilin A-cyclosporin A complex. In these three systems nearly complete assignment of the polypeptide backbone resonances and assignment of over 80% of the amino acid side-chain resonances was obtained without manual intervention.

Determination of the pharmacokinetics of glycopyrronium in the lung using a population pharmacokinetic modelling approach

AIMS Glycopyrronium bromide (NVA237) is a once-daily long-acting muscarinic antagonist recently approved for the treatment of chronic obstructive pulmonary disease. In this study, we used population pharmacokinetic (PK) modelling to provide insights into the impact of the lung PK of glycopyrronium on its systemic PK profile and, in turn, to understand the impact of lung bioavailability and residence time on the choice of dosage regimen. METHODS We developed and validated a population PK model to characterize the lung absorption of glycopyrronium using plasma PK data derived from studies in which this drug was administered by different routes to healthy volunteers. The model was also used to carry out simulations of once-daily and twice-daily regimens and to characterize amounts of glycopyrronium in systemic compartments and lungs. RESULTS The model-derived PK parameters were comparable to those obtained with noncompartmental analysis, confirming the usefulness of our model. The model suggested that the lung absorption of glycopyrronium was dominated by slow-phase absorption with a half-life of about 3.5 days, which accounted for 79% of drug absorbed through the lungs into the bloodstream, from where glycopyrronium was quickly eliminated. Simulations of once-daily and twice-daily administration generated similar PK profiles in the lung compartments. CONCLUSIONS The slow absorption from the lungs, together with the rapid elimination from the systemic circulation, could explain how once-daily glycopyrronium provides sustained bronchodilatation with a low incidence of adverse effects in patients with chronic obstructive pulmonary disease. Its extended intrapulmonary residence time also provides pharmacokinetic evidence that glycopyrronium has the profile of a once-daily drug.

Absolute free energies of binding of peptide analogs to the HIV‐1 protease from molecular dynamics simulations

The constants of binding of five peptide analogs to the active site of the HIV‐1 aspartic‐protease are calculated based on a novel sampling scheme that is efficient and does not introduce any approximations in addition to the energy function used to describe the system. The results agree with experiments. The squared correlation coefficient of the calculated vs. the measured values is 0.79. The sampling scheme consists of a series of molecular dynamics integrations with biases. The biases are selected based on an estimate of the probability density function of the system in a way to explore the conformational space and to reduce the statistical error in the calculated binding constants. The molecular dynamics integrations are done with a vacuum potential using a short cutoff scheme. To estimate the probability density of the simulated system, the results of the molecular dynamics integrations are combined using an extension of the weighted histogram analysis method (C. Bartels, Chem. Phys. Letters 331 (2000) 446–454). The probability density of the solvated ligand–protein system is obtained by applying a correction for the use of the short cutoffs in the simulations and by taking into account solvation with an electrostatic term and a hydrophobic term. The electrostatic part of the solvation is determined by finite difference Poisson–Boltzmann calculations; the hydrophobic part of the solvation is set proportional to the solvent accessible surface area. Setting the hydrophobic surface tension parameter equal to 8 mol−1 K−1 A−2, absolute binding constants are in the μM to nM range. This is in agreement with experiments. The standard errors determined from eight repeated binding constant determinations are a factor of 14 to 411. A single determination of a binding constant is done with 499700 steps of molecular dynamics integration and 4500 finite difference Poisson–Boltzmann calculations. The simulations can be analyzed with respect to conformational changes of the active site of the HIV‐1 protease or the ligands upon binding and provide information that complements experiments and can be used in the drug development process.

A spectral correlation function for efficient sequential NMR assignments of uniformly 15N-labeled proteins

SummaryA new computer-based approach is described for efficient sequence-specific assignment of uniformly 15N-labeled proteins. For this purpose three-dimensional 15N-correlated [1H, 1H]-NOESY spectra are divided up into two-dimensional 1H-1H strips which extend over the entire spectral width along one dimension and have a width of ca. 100 Hz, centered about the amide proton chemical shifts along the other dimension. A spectral correlation function enables sorting of these strips according to proximity of the corresponding residues in the amino acid sequence. Thereby, starting from a given strip in the spectrum, the probability of its corresponding to the C-terminal neighboring residue is calculated for all other strips from the similarity of their peak patterns with a pattern predicted for the sequentially adjoining residue, as manifested in the scalar product of the vectors representing the predicted and measured peak patterns. Tests with five different proteins containing both α-helices and β-sheets, and ranging in size from 58 to 165 amino acid residues show that the discrimination achieved between the sequentially neighboring residue and all other residues compares well with that obtained with an unguided interactive search of pairs of sequentially neighboring strips, with important savings in the time needed for complete analysis of 3D 15N-correlated [1H, 1H]-NOESY spectra. The integration of this routine into the program package XEASY ensures that remaining ambiguities can be resolved by visual inspection of the strips, combined with reference to the amino acid sequence and information on spin-system types obtained from additional NMR spectra.

Population pharmacokinetics of IND/GLY (indacaterol/glycopyrronium) in COPD patients.

OBJECTIVE Indacaterol/glycopyrronium (IND/GLY) is a fixed-dose combination (FDC) of indacaterol, an inhaled long-acting β2-agonist (LABA), and glycopyrronium, an inhaled long-acting muscarinic antagonist (LAMA), developed as a maintenance bronchodilator treatment for patients with chronic obstructive pulmonary disease (COPD). A population pharmacokinetic (PK) analysis was performed to describe the PK profiles of indacaterol and glycopyrronium following the twice daily (b.i.d.) and once daily (o.d.) inhalation regimens as FDC or as monotherapies and to determine the effect of covariates. METHODS PK data in 556 COPD patients were pooled from three phase 3 studies. Two phase 3 studies investigated IND/GLY 27.5/12.5 μg b.i.d. and the third study investigated IND/GLY 110/50 μg o.d. Body weight was included in the model with fixed allometric coefficients for indacaterol and glycopyrronium. RESULTS Statistically significant effects of smoking, age, and sex on apparent clearance of indacaterol; smoking, and estimated glomerular filtration rate at baseline on apparent clearance and Japanese ethnicity on apparent central volume of distribution of glycopyrronium were identified. CONCLUSION Systemic exposure to indacaterol and glycopyrronium was shown to be dose-proportional and time-independent following inhalation either as monotherapies or FDC. None of the identified covariate effects was judged to be clinically relevant. There is no PK drug-drug interaction between indacaterol and glycopyrronium in its FDC.