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Biomedical subjects

J A Platts

Publications and source records attributed to J A Platts.

9 recordsLinked to original sources

Novel properties from experimental charge densities: an application to the zwitterionic neurotransmitter taurine.

The charge distribution of taurine (2-aminoethane-sulfonic acid) is revisited by using an orbital-based method that describes the density in a fixed molecular orbital basis with variable orbital occupation numbers. A new neutron data set is also employed to explore whether this improves the deconvolution of thermal motion and charge density. A range of molecular properties that are novel for experimentally determined charge densities are computed, including Weinhold population analysis, Mayer bond orders, and local kinetic energy densities, in addition to charge topological analysis and quantum theory of atoms-in-molecules (QTAIM) integrated properties. The ease with which a distributed multipole analysis can be performed on the fitted density matrix makes it straightforward to compute molecular moments, the lattice energy, and the electrostatic interaction energies of molecules removed from the crystal. Results are compared with high-level (QCISD) gas-phase calculations and band structure calculations employing density functional theory. Finally, the avenues available for extending the range of molecular properties that can be calculated from experimental charge densities still further using this approach are discussed.

Electrons↗

A putative bioactive conformation for the altered peptide ligand of myelin basic protein and inhibitor of experimental autoimmune encephalomyelitis [Arg91, Ala96] MBP87-99.

[Arg(91), Ala(96)] MBP(87-99) is an altered peptide ligand (APL) of myelin basic protein (MBP), shown to actively inhibit experimental autoimmune encephalomyelitis (EAE), which is studied as a model of multiple sclerosis (MS). The APL has been rationally designed by substituting two of the critical residues for recognition by the T-cell receptor. A conformational analysis of the APL has been sought using a combination of 2D NOESY nuclear magnetic resonance (NMR) experiments and detailed molecular dynamics (MD) calculations, in order to comprehend the stereoelectronic requirements for antagonistic activity, and to propose a putative bioactive conformation based on spatial proximities of the native peptide in the crystal structure. The proposed structure presents backbone similarity with the native peptide especially at the N-terminus, which is important for major histocompatibility complex (MHC) binding. Primary (Val(87), Phe(90)) and secondary (Asn(92), Ile(93), Thr(95)) MHC anchors occupy the same region in space, whereas T-cell receptor (TCR) contacts (His(88), Phe(89)) have different orientation between the two structures. A possible explanation, thus, of the antagonistic activity of the APL is that it binds to MHC, preventing the binding of myelin epitopes, but it fails to activate the TCR and hence to trigger the immunologic response. NMR experiments coupled with theoretical calculations are found to be in agreement with X-ray crystallography data and open an avenue for the design and synthesis of novel peptide restricted analogues as well as peptide mimetics that rises as an ultimate goal.

Amino Acid Sequence↗

Structural requirements for binding of myelin basic protein (MBP) peptides to MHC II: effects on immune regulation.

Confronting Multiple Sclerosis requires as an underlying step the manipulation of immune response through modification of Myelin Basic Protein peptides. The aim is to design peptidic or nonpeptidic molecules that compete for recognition of self-antigens at the level of antigen presentation. The rational approach is to substitute residues that serve as anchors for the T-Cell Receptor with others that show no binding at all, and those that serve as Major Histocompatibility Complex II anchors with others that present increased binding affinity. The resulting structure, hence, retains normal or increased MHC II binding properties, but fails to activate disease-inducing T-cells. This rational design can only be achieved by identifying the structural requirements for binding of the natural peptide to MHC II, and the anchor residues with their corresponding specific pockets in the binding groove. The peptide-MHC II complex then interacts with the TCR; thus, an additional way to trigger the desired immune response is to alter secondary anchor residues as well as primary ones. In this review, the structural requirements for binding of MBP peptides to MHC II are presented, as are the mechanism and key features for TCR recognition of the peptide-MHC II complex.

Animals↗

Hydrogen bond structural group constants.

The ability of functional groups to act as hydrogen bond acids and bases can be obtained from either equilibrium constants for 1:1 hydrogen bonding or overall hydrogen bond constants. Either method leads to structural constants for hydrogen bonding that in some way are analogous to substituent constants. Extensive lists of these functional group constants are reported. It is shown that those derived from overall hydrogen bond constants are the more useful in analyses of physicochemical and biochemical properties.

Journal Article↗

Calculation of the hydrophobicity of platinum drugs.

Models of the hydrophobicity of platinum drugs based on exposed surface areas of polar and nonpolar atoms are presented. For a total of 24 log P(oct) data, the best model resulted in a standard deviation of 0.35 over a range of more than 4 log units, with regression coefficients in broad agreement with previous models of log P(oct) for organic molecules. This model is used to compare log P(oct) to cell uptake for five platinum drugs and hence to establish an exponential relation between these parameters.

Antineoplastic Agents↗

Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors.

The human intestinal absorption of 241 drugs was evaluated. Three main methods were used to determine the human intestinal absorption: bioavailability, percentage of urinary excretion of drug-related material following oral administration, and the ratio of cumulative urinary excretion of drug-related material following oral and intravenous administration. The general solvation equation developed by Abraham's group was used to model the human intestinal absorption data of 169 drugs we considered to have reliable data. The model contains five Abraham descriptors calculated by the ABSOLV program. The results show that Abraham descriptors can successfully predict human intestinal absorption if the human absorption data is carefully classified based on solubility and administration dose to humans.

Administration, Oral↗

Correlation and prediction of a large blood-brain distribution data set--an LFER study.

We report linear free energy relation (LFER) models of the equilibrium distribution of molecules between blood and brain, as log BB values. This method relates log BB values to fundamental molecular properties, such as hydrogen bonding capability, polarity/polarisability and size. Our best model of this form covers 148 compounds, the largest set of log BB data yet used in such a model, resulting in R(2)=0.745 and e.s.d.=0.343 after inclusion of an indicator variable for carboxylic acids. This represents rather better accuracy than a number of previously reported models based on subsets of our data. The model also reveals the factors that affect log BB: molecular size and dispersion effects increase brain uptake, while polarity/polarisability and hydrogen-bond acidity and basicity decrease it. By splitting the full data set into several randomly selected training and test sets, we conclude that such a model can predict log BB values with an accuracy of less than 0.35 log units. The method is very rapid-log BB can be calculated from structure at a rate of 700 molecules per minute on a silicon graphics O(2).

Blood-Brain Barrier↗

Estimation of molecular linear free energy relationship descriptors. 4. Correlation and prediction of cell permeation.

PURPOSE: The passage of molecules across cell membranes is a crucial step in many physiological processes. We therefore seek physical models of this process, in order to predict permeation for new molecules, and to better understand the important interactions which determine the rate of permeation. METHODS: Several sets of cell permeation data reported by Collander have been correlated against calculated Linear Free Energy Relation (LFER) descriptors. These descriptors, taken as the sum of fragmental contributions, cover the size, polarity, polarizabilty, and hydrogen bonding capacity of each molecule. RESULTS: For 36 values of permeation into Chara ceratophylla cells, a model (sd = 0.24) dominated by hydrogen bond acidity is found, while for 63 rates of permeation values into Nitella cells a very similar model yields sd = 0.46. Comparisons between the two cell types are made directly for 17 compounds in both data sets, indicate differences of a similar magnitude to the standard deviations of the above models. The two data sets can be combined to yield a generic model of rates of permeation into cells, resulting in an sd value of 0.46 for a total of 100 data points. CONCLUSIONS: Models allowing accurate prediction of cell permeation have been constructed using 100 experimental data. We demonstrate that hydrogen bond acidity is the dominating factor in determining cell permeation for two distinct species of algal cell.

Algorithms↗

Correlation and estimation of gas-chloroform and water-chloroform partition coefficients by a linear free energy relationship method.

A linear free energy relationship, LFER, has been used to correlate 150 values of gas-chloroform partition coefficients, as log Lchl with a standard deviation, sd, of 0.23 log units, a correlation coefficient r2 of 0.985, and an F-statistic of 1919. The equation reveals that bulk chloroform is dipolar/polarizable, of little hydrogen-bond basicity, but as strong a hydrogen-bond acid as bulk methanol or bulk ethanol. However, the main influence on gaseous solubility in chloroform is due to solute-solvent London dispersion interactions. A slightly modified LFER has been used to correlate 302 values of water-chloroform partition coefficients, as log Pchl. The correlation equation predicts log Pchl for a further 34 compounds not used in the equation with sd = 0.17 log units. When the LFER is applied to all 335 log Pchl values, the resulting equation has sd = 0.25, r2 = 0.971, and F = 2218.

Chloroform↗