Biomedical subjects

Chris Oostenbrink

Publications and source records attributed to Chris Oostenbrink.

At least 19 recordsLinked to original sources

PubMed2006

On using oscillating time-dependent restraints in MD simulation.

The use of time-dependent restraints in molecular simulation in order to generate a conformational ensemble for molecules that is in accordance with measured ensemble averages for particular observable quantities is investigated. Using a model system consisting of liquid butane and the cyclic peptide antamanide the reproduction of particular average (3) J-coupling constant values in a molecular dynamics simulation is analysed. It is shown that the multiple-valuedness and the sizeable gradients of the Karplus curve relating (3) J-coupling constants measured in NMR experiments to the corresponding torsional-angle values cause severe problems when trying to restrain a (3) J-coupling constant to a value close to the extrema of the Karplus curve. The introduction of a factor oscillating with time into the restraining penalty function alleviates this problem and enhances the restrained conformational sampling.

Algorithms↗

PubMed2006

Biomolecular modeling: Goals, problems, perspectives.

Computation based on molecular models is playing an increasingly important role in biology, biological chemistry, and biophysics. Since only a very limited number of properties of biomolecular systems is actually accessible to measurement by experimental means, computer simulation can complement experiment by providing not only averages, but also distributions and time series of any definable quantity, for example, conformational distributions or interactions between parts of systems. Present day biomolecular modeling is limited in its application by four main problems: 1) the force-field problem, 2) the search (sampling) problem, 3) the ensemble (sampling) problem, and 4) the experimental problem. These four problems are discussed and illustrated by practical examples. Perspectives are also outlined for pushing forward the limitations of biomolecular modeling.

Computer Simulation↗

PubMed2006

Configurational entropy change of netropsin and distamycin upon DNA minor-groove binding.

Binding of a small molecule to a macromolecular target reduces its conformational freedom, resulting in a negative entropy change that opposes the binding. The goal of this study is to estimate the configurational entropy change of two minor-groove-binding ligands, netropsin and distamycin, upon binding to the DNA duplex d(CGCGAAAAACGCG).d(CGCGTTTTTCGCG). Configurational entropy upper bounds based on 10-ns molecular dynamics simulations of netropsin and distamycin in solution and in complex with DNA in solution were estimated using the covariance matrix of atom-positional fluctuations. The results suggest that netropsin and distamycin lose a significant amount of configurational entropy upon binding to the DNA minor groove. The estimated changes in configurational entropy for netropsin and distamycin are -127 J K(-1) mol(-1) and -104 J K(-1) mol(-1), respectively. Estimates of the configurational entropy contributions of parts of the ligands are presented, showing that the loss of configurational entropy is comparatively more pronounced for the flexible tails than for the relatively rigid central body.

Binding Sites↗

PubMed2006

Catalytic site prediction and virtual screening of cytochrome P450 2D6 substrates by consideration of water and rescoring in automated docking.

Automated docking strategies successfully applied to binding mode predictions of ligands in Cyt P450 crystal structures in an earlier study (de Graaf et al. J. Med. Chem. 2005, 7, 2308-2318) were used for the catalytic site prediction (CSP) of 65 substrates in a CYP2D6 homology model. The consideration of water molecules at predicted positions in the active site and the rescoring of pooled docking poses from four different docking programs (AutoDock, FlexX, GOLD-Goldscore, and GOLD-Chemscore) with the SCORE scoring function enabled the successful prediction of experimentally reported sites of catalysis of more than 80% of the substrates. Three docking algorithms (FlexX, GOLD-Goldscore, and GOLD-Chemscore) were subsequently used in combination with six scoring functions (Chemscore, DOCK, FlexX, GOLD, PMF, and SCORE) to assess the ability of docking-based virtual screening methods to prioritize known CYP2D6 substrates seeded into a drug-like chemical database (in the absence and presence of active-site water molecules). Finally, the optimal docking strategy in terms of virtual screening accuracy, GOLD-Chemscore with the consideration of active-site water (60% of known substrates recovered in the top 5% of the ranked drug-like database), was verified experimentally; it was successfully used to identify high-affinity CYP2D6 ligands among a larger proprietary database.

Catalytic Domain↗

PubMed2006

Binding of 7-methoxy-4-(aminomethyl)-coumarin to wild-type and W128F mutant cytochrome P450 2D6 studied by time-resolved fluorescence spectroscopy.

Enzyme structure and dynamics may play a main role in substrate binding and the subsequent steps in the CYP (cytochrome P450) catalytic cycle. In the present study, changes in the structure of human CYP2D6 upon binding of the substrate are studied using steady-state and time-resolved fluorescence methods, focusing not only on the emission of the tryptophan residues, but also on emission of the substrate. As a substrate, MAMC [7-methoxy-4-(aminomethyl)-coumarin] was selected, a compound exhibiting native fluorescence. As well as the wild-type, the W128F (Trp128-->Phe) mutant of CYP2D6 was studied. After binding, a variety of energy transfer possibilities exist, and molecular dynamics simulations were performed to calculate distances and relative orientations of donors and acceptors. Energy transfer from Trp128 to haem appeared to be important; its emission was related to the shortest of the three average tryptophan fluorescence lifetimes observed for CYP2D6. MAMC to haem energy transfer was very efficient as well: when bound in the active site, the emission of MAMC was fully quenched. Steady-state anisotropy revealed that besides the MAMC in the active site, another 2.4% of MAMC was bound outside of the active site to wild-type CYP2D6. The tryptophan residues in CYP2D6 appeared to be less accessible for the external quenchers iodide and acrylamide in presence of MAMC, indicating a tightening of the enzyme structure upon substrate binding. However, the changes in the overall enzyme structure were not very large, since the emission characteristics of the enzyme were not very different in the presence of MAMC.

Amino Acid Substitution↗

PubMed2006

Computational study of ground-state chiral induction in small peptides: comparison of the relative stability of selected amino acid dimers and oligomers in homochiral and heterochiral combinations.

The relative stabilities of homochiral and heterochiral forms of selected dipeptides, AA, AS, AC, AV, AF, AD, AK, tripeptides, AAA, AVA, and an acetylpentapeptide, AcGLSFA, have been calculated using thermodynamic integration protocols and the GROMOS 53A6 force field. Integration pathways have been designed that produce minimal disturbance to the system, including the use of soft atoms, low-energy intermediates, and chiral inversion of the smaller amino acid in the peptide. Comparison of the results obtained by thermodynamic integration between the diastereomeric forms (in explicit water, at 300 K) and from exhaustive global minimum-energy searches for the individual dipeptides (implicit water, epsilon = 78, 0 K) suggests that entropic contributions to the relative stability of the chiral forms are important. This conclusion is supported by the results of explicit calculation of the effect of temperature on the relative stability of alanylvalylalanine diastereomers. The Gibbs free energy calculations predict that at ambient temperature and pressure homochiral dipeptides with small side chains or polar groups in the vicinity of the peptide backbone, AA, AS, and AD, are more stable than their heterochiral counterparts by fractions of a kJ/mol. For bigger side chains, AC, AV, AF, and AK, the heterochiral diastereomers appear to be more stable. Predicted relative stabilities are in line with observations reported in the literature for AE and YY. Excellent agreement is found for the calculated and experimentally determined relative stabilities of the diastereomers of the dipeptide AA and of all-L AcGLSFA and its diastereomer containing D-serine in the central position. Addition of counterions to the solvent box has no significant effects on charged and neutral forms. From the present findings it would appear unlikely that the intrinsic stability difference between homo- and heterochiral dipeptides has been a driving force in a primordial selection process leading to the incorporation of amino acids with a single enantiomeric configuration in natural proteins.

Amino Acids↗

PubMed2005

Metabolic regio- and stereoselectivity of cytochrome P450 2D6 towards 3,4-methylenedioxy-N-alkylamphetamines: in silico predictions and experimental validation.

A series of 3,4-methylenedioxy-N-alkylamphetamines (MDAAs) were automatically docked and subjected to molecular dynamics (MD) simulations in a cytochrome P450 2D6 (CYP2D6) protein model. The predicted substrate binding orientations, sites of oxidation, and relative reactivities were compared to the experimental data of wild-type and Phe120Ala mutant CYP2D6. Automated docking results were not sufficient to accurately rationalize experimental binding orientations of 3,4-methylenedioxy-N-methylamphetamine (MDMA) in the two enzymes as measured with spin lattice relaxation NMR. Nevertheless, the docking results could be used as starting structures for MD simulations. Predicted binding orientations of MDMA and sites of oxidation of the MDAAs derived from MD simulations matched well with the experimental data. It appeared the experimental results were best described in MD simulations considering the nitrogen atoms of the MDAAs in neutral form. Differences in regioselectivity and stereoselectivity in the oxidative metabolism of the MDAAs by the Phe120Ala mutant CYP2D6 were correctly predicted, and the effects of the Phe120Ala mutation could be rationalized as well.

Amphetamines↗

PubMed2005

Amine hydration: a united-atom force-field solution.

The free energies of hydration for ammonia and mono-, di-, and trimethylated amines experimentally show an unexpected trend that has, in the past, been difficult to reproduce computationally. Absolute and relative free energies of hydration of these compounds were calculated using the OPLS all-atom and the united-atom GROMOS force fields. Both force fields reproduce the relative free energy of hydration, but the absolute free energies of hydration were only reproduced within kBT when using the recently developed GROMOS parameter set 53A6. Relative free energies of solvation in chloroform could also be reproduced indicating a proper partitioning of the compounds between polar and apolar media. Overall we conclude that it is possible to resolve the amine hydration problem using a simple united-atom force field.

Journal Article↗

PubMed2005

Efficient calculation of many stacking and pairing free energies in DNA from a few molecular dynamics simulations.

Through the use of the one-step perturbation approach, 130 free energies of base stacking and 1024 free energies of base pairing in DNA have been calculated from only five simulations of a nonphysical reference state. From analysis of a diverse set of 23 natural and unnatural bases, it appears that stacking free energies and stacking conformations play an important role in pairing of DNA nucleotides. On the one hand, favourable pairing free energies were found for bases that do not have the possibility to form canonical hydrogen bonds, while on the other hand, good hydrogen-bonding possibilities do not guarantee a favourable pairing free energy if the stacking of the bases dictates an unfavourable conformation. In this application, the one-step perturbation approach yields a wealth of both energetic and structural information at minimal computational cost.

Base Pairing↗

PubMed2005

Validation of the 53A6 GROMOS force field.

The quality of biomolecular dynamics simulations relies critically on the force field that is used to describe the interactions between particles in the system. Force fields, which are generally parameterized using experimental data on small molecules, can only prove themselves in realistic simulations of relevant biomolecular systems. In this work, we begin the validation of the new 53A6 GROMOS parameter set by examining three test cases. Simulations of the well-studied 129 residue protein hen egg-white lysozyme, of the DNA dodecamer d(CGCGAATTCGCG)(2), and a proteinogenic beta(3)-dodecapeptide were performed and analysed. It was found that the new parameter set performs as well as the previous parameter sets in terms of protein (45A3) and DNA (45A4) stability and that it is better at describing the folding-unfolding balance of the peptide. The latter is a property that is directly associated with the free enthalpy of hydration, to which the 53A6 parameter set was parameterized.

Animals↗

PubMed2005

Free energies of ligand binding for structurally diverse compounds.

The one-step perturbation approach is an efficient means to calculate many relative free energies from a common reference compound. Combining lessons learned in previous studies, an application of the method is presented that allows for the calculation of relative binding free energies for structurally rather diverse compounds from only a few simulations. Based on the well known statistical-mechanical perturbation formula, the results do not require any empirical parameters, or training sets, only limited knowledge of the binding characteristics of the ligands suffices to design appropriate reference compounds. Depending on the choice of reference compound, relative free energies of binding rigid ligands to the ligand-binding domain of the estrogen receptor can be obtained that show good agreement with the experimental values. The approach presented here can easily be applied to many rigid ligands, and it should be relatively easy to extend the method to account for ligand flexibility. The free-energy calculations can be straightforwardly parallelized, allowing for an efficient means to understand and predict relative binding free energies.

Algorithms↗

PubMed2005

Molecular dynamics simulations and free energy calculations of netropsin and distamycin binding to an AAAAA DNA binding site.

Molecular dynamics simulations have been performed on netropsin in two different charge states and on distamycin binding to the minor groove of the DNA duplex d(CGCGAAAAACGCG).d(CGCGTTTTTCGCG). The relative free energy of binding of the two non-covalently interacting ligands was calculated using the thermodynamic integration method and reflects the experimental result. From 2 ns simulations of the ligands free in solution and when bound to DNA, the mobility and the hydrogen-bonding patterns of the ligands were studied, as well as their hydration. It is shown that even though distamycin is less hydrated than netropsin, the loss of ligand-solvent interactions is very similar for both ligands. The relative mobilities of the ligands in their bound and free forms indicate a larger entropic penalty for distamycin when binding to the minor groove compared with netropsin, partially explaining the lower binding affinity of the distamycin molecule. The detailed structural and energetic insights obtained from the molecular dynamics simulations allow for a better understanding of the factors determining ligand-DNA binding.

Anti-Bacterial Agents↗

PubMed2005

Calculation of the redox potential of the protein azurin and some mutants.

Azurin from Pseudomonas aeruginosa is a small 128-residue, copper-containing protein. Its redox potential can be modified by mutating the protein. Free-energy calculations based on classical molecular-dynamics simulations of the protein and from mutants in aqueous solution at different pH values were used to compute relative redox potentials. The precision of the free-energy calculations with the lambda coupling-parameter approach is evaluated as function of the number and sequence of lambda values, the sampling time and initial conditions. It is found that the precision is critically dependent on the relaxation of hydrogen-bonding networks when changing the atomic-charge distribution due to a change of redox state or pH value. The errors in the free energies range from 1 to 10 k(B)T, depending on the type of process. Only qualitative estimates of the change in redox potential by protein mutation can be obtained.

Amino Acid Substitution↗

PubMed2005

An improved nucleic acid parameter set for the GROMOS force field.

Over the past decades, the GROMOS force field for biomolecular simulation has primarily been developed for performing molecular dynamics (MD) simulations of polypeptides and, to a lesser extent, sugars. When applied to DNA, the 43A1 and 45A3 parameter sets of the years 1996 and 2001 produced rather flexible double-helical structures, in which the Watson-Crick hydrogen-bonding content was more limited than expected. To improve on the currently available parameter sets, the nucleotide backbone torsional-angle parameters and the charge distribution of the nucleotide bases are reconsidered based on quantum-chemical data. The new 45A4 parameter set resulting from this refinement appears to perform well in terms of reproducing solution NMR data and canonical hydrogen bonding. The deviation between simulated and experimental observables is now of the same order of magnitude as the uncertainty in the experimental values themselves.

Algorithms↗

PubMed2005

The GROMOS software for biomolecular simulation: GROMOS05.

We present the latest version of the Groningen Molecular Simulation program package, GROMOS05. It has been developed for the dynamical modelling of (bio)molecules using the methods of molecular dynamics, stochastic dynamics, and energy minimization. An overview of GROMOS05 is given, highlighting features not present in the last major release, GROMOS96. The organization of the program package is outlined and the included analysis package GROMOS++ is described. Finally, some applications illustrating the various available functionalities are presented.

Algorithms↗

PubMed2004

Estimating entropies from molecular dynamics simulations.

While the determination of free-energy differences by MD simulation has become a standard procedure for which many techniques have been developed, total entropies and entropy differences are still hardly ever computed. An overview of techniques to determine entropy differences is given, and the accuracy and convergence behavior of five methods based on thermodynamic integration and perturbation techniques was evaluated using liquid water as a test system. Reasonably accurate entropy differences are obtained through thermodynamic integration in which many copies of a solute are desolvated. When only one solute molecule is involved, only two methods seem to yield useful results, the calculation of solute-solvent entropy through thermodynamic integration, and the calculation of solvation entropy through the temperature derivative of the corresponding free-energy difference. One-step perturbation methods seem unsuitable to obtain entropy estimates.

Journal Article↗

PubMed2004

Free energies of binding of polychlorinated biphenyls to the estrogen receptor from a single simulation.

Relative free energies of binding to the ligand-binding domain of the estrogen receptor have been calculated for a series of 17 hydroxylated polychlorinated biphenyls. Because traditional thermodynamic integration or perturbation approaches are hardly feasible for these numbers of compounds, the one-step perturbation approach is applied and is shown to yield accurate results based on only two 2-ns molecular dynamics simulations of an unphysical, judiciously chosen, reference state. The mean absolute difference between the calculated and experimental binding free energies for the 17 compounds is 3.4 kJ/mol, which illustrates the accuracy of the GROMOS biomolecular force field used. Excluding the three largest ligands from the comparison reduces the deviation to 2.0 kJ/mol (i.e., < k(B)T). Apart from the relative free energy, structural information about the binding mode and binding orientation for every compound can also be extracted from the simulation, showing that a ligand bound to its receptor cannot be represented by a single conformation, but it samples an ensemble of different orientations.

Carbon↗

PubMed2004

A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6.

Successive parameterizations of the GROMOS force field have been used successfully to simulate biomolecular systems over a long period of time. The continuing expansion of computational power with time makes it possible to compute ever more properties for an increasing variety of molecular systems with greater precision. This has led to recurrent parameterizations of the GROMOS force field all aimed at achieving better agreement with experimental data. Here we report the results of the latest, extensive reparameterization of the GROMOS force field. In contrast to the parameterization of other biomolecular force fields, this parameterization of the GROMOS force field is based primarily on reproducing the free enthalpies of hydration and apolar solvation for a range of compounds. This approach was chosen because the relative free enthalpy of solvation between polar and apolar environments is a key property in many biomolecular processes of interest, such as protein folding, biomolecular association, membrane formation, and transport over membranes. The newest parameter sets, 53A5 and 53A6, were optimized by first fitting to reproduce the thermodynamic properties of pure liquids of a range of small polar molecules and the solvation free enthalpies of amino acid analogs in cyclohexane (53A5). The partial charges were then adjusted to reproduce the hydration free enthalpies in water (53A6). Both parameter sets are fully documented, and the differences between these and previous parameter sets are discussed.

Algorithms↗