Jeffrey Daniel Schmitt

Alkyl-linked diglycerides inhibit protein kinase C activation by diacylglycerols

Alkylacylglycerols are synthesized when choline-phospholipids are degraded by a phospholipase C. This class of compounds has been shown to have biological activities; however, the mechanism of action is unknown. A series of alkyl-linked diglycerides were synthesized and tested for activity in an in vitro assay for protein kinase C. When protein kinase C activity was stimulated with the synthetic diacylglyceride analog 1-oleoyl-2-acetyl-sn-glycerol, the addition of alkyl glycerides caused a concentration-dependent inhibition of protein kinase C activity. Comparison of the protein kinase C inhibition by this series of 1-O-alkyl-2-acyl analogs revealed that both saturated and unsaturated long-chain groups in position 1 were effective and that dietherglycerols with short-chain moieties in position 2 were also effective. It is concluded from these studies that the biological activity of alkyl-linked glycerides may be expressed through protein kinase C inhibition.

Stereospecific activity of 1-O-alkyl-2-O-acetyl-sn-glycero-3-phosphocholine and comparison of analogs in the degranulation of platelets and neutrophils

Abstract 1-O-Hexadecyl-2-O-acetyl- sn -glycero-3-phosphocholine (platelet activating factor) stimulated the degranulation of rabbit platelets and human neutrophils, whereas the enantiomer, 3-O-hexadecyl-2-O-acetyl- sn -glycero-1-phosphocholine, was inactive. The analogs compared had the following relative potencies in degranulating platelets and neutrophils: 1-O-hexadecyl-2-O-acetyl- sn -glycero-3-phosphocholine > 1-O-hexadecyl-2-O-ethyl- sn -glycero-3-phosphocholine > rac -1-O-octadecyl-2-O-ethylglycero-3-phosphocholine = 1-O-hexadecyl-2-O-methyl- sn -glycero-3-phosphocholine > rac -1-O-dodecyl-2-O-ethyl-glycero-3-phosphocholine. The deacetylated compound, 1-O-hexadecyl-2-lyso- sn -glycero-3-phosphocholine, and 1-O-hexadecyl-2,2-dimethylpropanediol-3-phosphocholine were inactive. The active analogs selectively desensitized the response to each other in the neutrophils. It is suggested that these compounds may activate cells through interaction with a stereospecific receptor.

1-O-hexadecyl-2-acetyl-sn-glycerol stimulates differentiation of HL-60 human promyelocytic leukemia cells to macrophage-like cells

Summary The human promyelocytic leukemia cell line HL-60 can be differentiated to cells resembling either neutrophils or mononuclear phagocytes by a diverse group of stimuli. However, the underlying mechanisms remain unknown. We report that 1- O -hexadecyl-2-acetyl- sn -glycerol inhibits the growth of HL-60 cells and induces differentiation to cells resembling mononuclear phagocytes. HL-60 cultures incubated for 6 days with 1- O -hexadecyl-2-acetyl- sn -glycerol (5 μg/ml) demonstrated a ten-fold increase in nonspecific esterase activity, and produced cells with morphological features similar to those of monocytes and macrophages. Higher concentrations of 1- O -hexadecyl-2-acetyl- sn -glycerol significantly inhibited the growth of HL-60 cells and resulted in the virtual absence of cells resembling the original HL-60 line. 1- O -Oleoyl-2-acetyl- rac -glycerol added under the same conditions did not induce cell differentiation or inhibit cell growth.

Stimulation of hexose transport by human polymorphonuclear leukocytes: A possible role for protein kinase C

The protein C kinase activators 1-O-oleoyl, 2-O-acetylglycerol, 12-O-tetradecanoyl phorbol-13-acetate, and mezerein, stimulated deoxyglucose uptake in human neutrophils. The responses were stimulus specific since no effect was noted with the diether analogues 1-O-hexadecyl-2-O-ethylglycerol, 1-O-palmitoyl-2-O-acetyl or 1-O-palmitoyl-3-O-acetyl diesters of propanediol, or with 1,2-diolein. Stimulation of deoxyglucose uptake had the characteristics of carrier facilitated hexose transport. Stimulated uptake of deoxy-glucose was inhibited by trifluoperazine (10-30 microM). Activation of protein kinase C therefore appears to trigger events involved in hexose transport.

Genetic algorithms and self-organizing maps: a powerful combination for modeling complex QSAR and QSPR problems

Modeling non-linear descriptor-target activity/property relationships with many dependent descriptors has been a long-standing challenge in the design of biologically active molecules. In an effort to address this problem, we couple the supervised self-organizing map with the genetic algorithm. Although self-organizing maps are non-linear and topology-preserving techniques that hold great potential for modeling and decoding relationships, the large number of descriptors in typical quantitative structure--activity relationship or quantitative structure--property relationship analysis may lead to spurious correlation(s) and/or difficulty in the interpretation of resulting models. To reduce the number of descriptors to a manageable size, we chose the genetic algorithm for descriptor selection because of its flexibility and efficiency in solving complex problems. Feasibility studies were conducted using six different datasets, of moderate-to-large size and moderate-to-great diversity; each with a different biological endpoint. Since favorable training set statistics do not necessarily indicate a highly predictive model, the quality of all models was confirmed by withholding a portion of each dataset for external validation. We also address the variability introduced onto modeling through dataset partitioning and through the stochastic nature of the combined genetic algorithm supervised self-organizing map method using the z-score and other tests. Experiments show that the combined method provides comparable accuracy to the supervised self-organizing map alone, but using significantly fewer descriptors in the models generated. We observed consistently better results than partial least squares models. We conclude that the combination of genetic algorithms with the supervised self-organizing map shows great potential as a quantitative structure--activity/property relationship modeling tool.

Reacylation of platelet activating factor with eicosapentaenoic acid in fish-oil-enriched monkey neutrophils

Platelet activating factor (PAF) is rapidly metabolized via a deacetylation: reacylation pathway which shows striking specificity for arachidonate at the sn-2 position of the 1-O-alkyl-2-acyl-GPC thus formed. We have now examined the effects of a diet enriched in fish oils on the metabolism of PAF and specificity for arachidonate in the reacylation reaction. [3H]PAF was incubated for various lengths of time with neutrophils from monkeys fed a control diet or one enriched in fish oils. The [3H]PAF added to the cell suspension was rapidly converted to 1-O-alkyl-2-acyl-GPC. Reverse-phase HPLC analysis of the acyl chains added at the sn-2 position revealed that arachidonate was the major fatty acid incorporated into the 1-O-alkyl-2-acyl-GPC formed by neutrophils from monkeys on the control diet. In contrast, both 1-O-alkyl-2-arachidonoyl-GPC and 1-O-alkyl-2-eicosapentaenoyl-GPC were formed by the fish-oil-enriched neutrophils. We also report on the fatty acid composition of neutrophil phospholipids during such a diet.

Supervised self-organizing maps in drug discovery. 2. Improvements in descriptor selection and model validation

The modeling of nonlinear descriptor-target relationships is a topic of considerable interest in drug discovery. We, herein, continue reporting the use of the self-organizing map-a nonlinear, topology-preserving pattern recognition technique that exhibits considerable promise in modeling and decoding these relationships. Since simulated annealing is an efficient tool for solving optimization problems, we combined the supervised self-organizing map with simulated annealing to build high-quality, highly predictive quantitative structure-activity/property relationship models. This technique was applied to six data sets representing a variety of biological endpoints. Since a high statistical correlation in the training set does not indicate a highly predictive model, the quality of all the models was confirmed by withholding a portion of each data set for external validation. Finally, we introduce new cross-validation and dynamic partitioning techniques to address model overfitting and assessment.

Protonation-induced stereoisomerism in nicotine : Conformational studies using classical (AMBER) and ab initio (Car-Parrinello) molecular dynamics

A variety of biologically active small molecules contain prochiral tertiary amines, which become chiral centers upon protonation. S-nicotine, the prototypical nicotinic acetylcholine receptor agonist, produces two diastereomers on protonation. Results, using both classical (AMBER) and ab initio (Car–Parrinello) molecular dynamical studies, illustrate the significant differences in conformational space explored by each diastereomer. As is expected, this phenomenon has an appreciable effect on nicotine’s energy hypersurface and leads to differentiation in molecular shape and divergent sampling. Thus, protonation induced isomerism can produce dynamic effects that may influence the behavior of a molecule in its interaction with a target protein. We also examine differences in the conformational dynamics for each diastereomer as quantified by both molecular dynamics methods.

Molecular modeling of mono- and bis-quaternary ammonium salts as ligands at the α4β2 nicotinic acetylcholine receptor subtype using nonlinear techniques

The neuronal nicotinic acetylcholine receptor (nAChR) has been a target for drug development studies for over a decade. A series ofmono- andbis-quaternary ammonium salts, known to be antagonists at nAChRs, were separated into 3 structural classes and evaluated using both self-organizing map (SOM) and genetic functional approximation (GFA) algorithm models. Descriptors from these compounds were used to create several nonlinear quantitative structure-activity relationships (QSARs). The SOM methodology was effective in appropriately grouping these compounds with diverse structures and activities. The GFA models were also able to predict the activities of these molecules. Charge distribution and the hydrophobic free energies were found to be important indicators of bioactivity for this particular class of molecules. These QSAR approaches may be a useful to screen and selectin silico new drug candidates from larger compound libraries to be further evaluated in in vitro biological assays.

A facile synthesis of 1-O-alkyl-2-(R)-hydroxypropane-3-phosphonocholine (lyso-phosphono-platelet activating factor)

The synthesis of 1-O-alkyl-2-(R)-hydroxypropane-3-phosphonocholine is described. An efficient alkylation procedure using (NaH/DMSO) catalysis is also described and applied to the synthetic scheme. The key intermediate 1-O-alkyl-2-(R)-O-benzyl-3-bromopropane was phosphonylated using tris(methylsilyl)phosphite; the resulting phosphonic acid was coupled to choline using trichloroacetonitrile/pyridine or triisopropylbenzenesulfonyl chloride/pyridine followed by catalytic hydrogenation to yield 1-O-alkyl-2(R)-hydroxypropane-3-phosphonocholine.