Vedat Durmaz

A nontoxic pain killer designed by modeling of pathological receptor conformations

A pain killer without side effects Opioids are very strong and effective pain killers. However, they also have a range of well-known side effects and can cause addiction. Painful conditions such as inflammation or trauma are often associated with localized tissue acidification. Spahn et al. designed a novel opioid receptor agonist that, unlike clinically used opioids, best activates the receptors in such acidified tissues. In rat models of inflammatory pain, the new drug exerted strong pain relief essentially without the side effects of standard opioids. Science, this issue p. 966 A novel opioid selectively activates peripheral opioid receptors only in inflamed tissue. Indiscriminate activation of opioid receptors provides pain relief but also severe central and intestinal side effects. We hypothesized that exploiting pathological (rather than physiological) conformation dynamics of opioid receptor-ligand interactions might yield ligands without adverse actions. By computer simulations at low pH, a hallmark of injured tissue, we designed an agonist that, because of its low acid dissociation constant, selectively activates peripheral μ-opioid receptors at the source of pain generation. Unlike the conventional opioid fentanyl, this agonist showed pH-sensitive binding, heterotrimeric guanine nucleotide–binding protein (G protein) subunit dissociation by fluorescence resonance energy transfer, and adenosine 3′,5′-monophosphate inhibition in vitro. It produced injury-restricted analgesia in rats with different types of inflammatory pain without exhibiting respiratory depression, sedation, constipation, or addiction potential.

Photochemical trans-/cis-isomerization and quantitation of zearalenone in edible oils

The emphasis of the present work was to investigate the photochemical conversion of trans- to cis-zearalenone in edible oils under real-life conditions. For quantitation purposes a cis-zearalenone standard was synthesized and characterized for its identity and purity (≥95%) by (1)H NMR, X-ray crystallography, HPLC fluorescence and mass spectrometric detection. In a sample survey of 12 edible oils (9 corn oils, 3 hempseed oils) from local supermarkets all corn oils contained trans-zearalenone (median 194 μg/kg), but no cis-zearalenone was detected. For alteration studies trans-zearalenone contaminated corn oils were exposed to sunlight over 4 and 30 weeks, revealing an obvious shift toward cis-zearalenone up to a cis/trans ratio of 9:1 by storage in colorless glass bottles. Irradiation experiments of trans-zearalenone in different organic solvents confirmed the preferred formation of cis-zearalenone possibly caused by entropic effects rather than by enthalpic entities as investigated by quantum chemical and classical force field simulations.

Classical hybrid Monte-Carlo simulation of the interconversion of hexabromocyclododecane stereoisomers

The interconversion of the six main stereoisomers of the flame retardant hexabromocyclododecane (HBCD) is investigated by means of statistical thermodynamics using classical force-fields. ( ± )-α-, ( ± )-β- and ( ± )-γ-HBCD interconvert by swapping of absolute configurations on the three different (BrHC–CHBr)-moieties. The approach avoids saddle-point energy computations, but relies on classical thermodynamic simulation and pursues three consecutive steps. First, the application of classical hybrid Monte-Carlo simulations for quantum mechanical processes is justified. Second, the problem of insufficient convergence properties of hybrid Monte-Carlo methods for the generation of low temperature canonical ensembles is solved by an interpolation approach. Third, it is shown how free energy differences among stereoisomers are derived and how they can be used for the computation of interconversion rates. The simulation results confirm the experimentally observed interconversion rates and correctly identify α-HBCD as a thermodynamical sink in the oscillating mixture of stereoisomers.

Hands-off Linear Interaction Energy Approach to Binding Mode and Affinity Estimation of Estrogens

With this work we target the development of a predictictive model for the identification of small molecules which bind to the estrogen receptor alpha and, thus, may act as endocrine disruptors. We propose a combined thermodynamic approach for the estimation of preferential binding modes along with corresponding free energy differences using a linear interaction energy (LIE) ansatz. The LIE model is extended by a Monte Carlo approach for the computation of conformational entropies as recently developed by our group. Incorporating the entropy contribution substantially increased the correlation with experimental affinity values. Both squared coefficients for the fitted data as well as the more meaningful leave-one-out cross-validation of predicted energies were elevated up to r(Fit)² = 0.87 and q(LOO)² = 0.82, respectively. All calculations have been performed on a set of 31 highly diverse ligands regarding their structural properties and affinities to the estrogen receptor alpha. Comparison of predicted ligand orientations with crystallographic data retrieved from the Protein database pdb.org revealed remarkable binding mode predictions.

Investigation of the Ergopeptide Epimerization Process

Ergopeptides, like ergocornine and a-ergocryptine, exist in an S- and in an R-configuration. Kinetic experiments imply that certain configurations are preferred depending on the solvent. The experimental methods are explained in this article. Furthermore, computational methods are used to understand this configurational preference. Standard quantum chemical methods can predict the favored configurations by using minimum energy calculations on the potential energy landscape. However, the explicit role of the solvent is not revealed by this type of methods. In order to better understand its influence, classical mechanical molecular simulations are applied. It appears from our research that “folding” the ergopeptide molecules into an intermediate state (between the S- and the R-configuration) is mechanically hindered for the preferred configurations.

How to Simulate Affinities for Host-Guest Systems Lacking Binding Mode Information: application to the liquid chromatographic separation of hexabromocyclododecane stereoisomers

A novel approach for the simulation of host–guest systems by systematically scanning the host molecule’s orientations within the guest cavity is presented along with a thermodynamic strategy for determining preferential binding modes and corresponding optimal interaction energies between host and guest molecules. By way of example, the elution order of hexabromocyclododecane stereoisomers from high performance liquid chromatography separation on a permethylated β-cyclcodextrin stationary phase has been computed using classical molecular dynamics simulations with the explicit solvents water and acetonitrile. Comparison of estimated with experimental separation data reveals remarkable squared coefficients of correlation with R2 = 0.87 and a very high correlation

Medizin aus dem Computer

{R_{{{\text{LO}}{{\text{O}}^2}}}} = 0.72

Effects of carbamazepine and two of its metabolites on the non-biting midge Chironomus riparius in a sediment full life cycle toxicity test.

using the leave-one-out cross-validation method and water as solvent. In particular, the approach presented shapes up as very robust in terms of the evaluated time range under consideration, reflecting well thermodynamic equilibria. These and further observations correlating with experimental results suggest the suitability of the underlying force fields and our multi-mode approach for the estimation of relative binding affinities for host–guest systems with unknown binding modes.