An afferent hippocampal fiber system in the fornix of the monkey

No Abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49987/1/901210205_ftp.pd

A COMPARISON OF CHOLINESTERASE DISTRIBUTION IN THE CEREBELLUM OF SEVERAL SPECIES *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65142/1/j.1471-4159.1964.tb06717.x.pd

Studies on the diencephalon of the virginia opossum.

No Abstract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49929/1/900770304_ftp.pd

Qualitative prediction of blood–brain barrier permeability on a large and refined dataset

The prediction of blood–brain barrier permeation is vitally important for the optimization of drugs targeting the central nervous system as well as for avoiding side effects of peripheral drugs. Following a previously proposed model on blood–brain barrier penetration, we calculated the cross-sectional area perpendicular to the amphiphilic axis. We obtained a high correlation between calculated and experimental cross-sectional area (r = 0.898, n = 32). Based on these results, we examined a correlation of the calculated cross-sectional area with blood–brain barrier penetration given by logBB values. We combined various literature data sets to form a large-scale logBB dataset with 362 experimental logBB values. Quantitative models were calculated using bootstrap validated multiple linear regression. Qualitative models were built by a bootstrapped random forest algorithm. Both methods found similar descriptors such as polar surface area, pKa, logP, charges and number of positive ionisable groups to be predictive for logBB. In contrast to our initial assumption, we were not able to obtain models with the cross-sectional area chosen as relevant parameter for both approaches. Comparing those two different techniques, qualitative random forest models are better suited for blood-brain barrier permeability prediction, especially when reducing the number of descriptors and using a large dataset. A random forest prediction system (ntrees = 5) based on only four descriptors yields a validated accuracy of 88%

Isothermal Microcalorimetry to Investigate Non Specific Interactions in Biophysical Chemistry

Isothermal titration microcalorimetry (ITC) is mostly used to investigate the thermodynamics of “specific” host-guest interactions in biology as well as in supramolecular chemistry. The aim of this review is to demonstrate that ITC can also provide useful information about non-specific interactions, like electrostatic or hydrophobic interactions. More attention will be given in the use of ITC to investigate polyelectrolyte-polyelectrolyte (in particular DNA-polycation), polyelectrolyte-protein as well as protein-lipid interactions. We will emphasize that in most cases these “non specific” interactions, as their definition will indicate, are favoured or even driven by an increase in the entropy of the system. The origin of this entropy increase will be discussed for some particular systems. We will also show that in many cases entropy-enthalpy compensation phenomena occur

Identification of Novel Functional Inhibitors of Acid Sphingomyelinase

We describe a hitherto unknown feature for 27 small drug-like molecules, namely functional inhibition of acid sphingomyelinase (ASM). These entities named FIASMAs (Functional Inhibitors of Acid SphingoMyelinAse), therefore, can be potentially used to treat diseases associated with enhanced activity of ASM, such as Alzheimer's disease, major depression, radiation- and chemotherapy-induced apoptosis and endotoxic shock syndrome. Residual activity of ASM measured in the presence of 10 µM drug concentration shows a bimodal distribution; thus the tested drugs can be classified into two groups with lower and higher inhibitory activity. All FIASMAs share distinct physicochemical properties in showing lipophilic and weakly basic properties. Hierarchical clustering of Tanimoto coefficients revealed that FIASMAs occur among drugs of various chemical scaffolds. Moreover, FIASMAs more frequently violate Lipinski's Rule-of-Five than compounds without effect on ASM. Inhibition of ASM appears to be associated with good permeability across the blood-brain barrier. In the present investigation, we developed a novel structure-property-activity relationship by using a random forest-based binary classification learner. Virtual screening revealed that only six out of 768 (0.78%) compounds of natural products functionally inhibit ASM, whereas this inhibitory activity occurs in 135 out of 2028 (6.66%) drugs licensed for medical use in humans

Some effects of muscarinic cholinergic blocking drugs on behavior and the electrocorticogram

Results are presented for the effects of drugs with muscarinic cholinergic blocking actions, both central and peripheral (scopolamine and 1-hyoscyamine) and primarily peripheral (methyl atropine and methyl scopolamine), on conditioned avoidance behavior, spontaneous motor activity, and the ECG in the rat.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46397/1/213_2006_Article_BF02341261.pd

"In silico" prediction of blood-brain barrier permeation and P-glycoprotein activity

P-glycoprotein is an ATP-dependent efflux transport protein which is highly expressed in many human tissues such as the intestinal epithelium and the blood-brain barrier, and is over-expressed in many cancer cells.1 This transporter carries a wide variety of chemically unrelated compounds. It binds them within the cell lipid membrane, and flips them to the outer leaflet or exports them to the extracellular medium.2 Since P-glycoprotein affects the distribution of many drugs, assessing the interactions between drugs and Pglycoprotein at an early stage of drug development is important. It has been shown that the binding of a drug to the transporter occurs in a two-step process.3{5 (i) The drug partitions from the extracellular environment to the lipid membrane, and after diffusion to the inner cytosolic leaflet of the bilayer, (ii) it binds to P-glycoprotein most likely via hydrogen bond formation. Different methods have been used to assess the lipid-water partition coefficient, such as isothermal titration calorimetry, and lipid monolayer insertion measurements. However, the lipid-water partition coefficient depends on the lipid used, and in turn on the lateral packing density of the lipid layer. Therefore an approach based on surface activity measurements was developed, which allows the prediction of the lipid-water partition coe�cient for membranes of different lateral packing densities.7 Measurements of the surface pressure of the drug in buffer solution as a function of concentration (Gibbs adsorption isotherm) yields the air-water partition coefficient (Kaw), the critical micellar concentration (CMC), and the cross-sectional area of the compound (AD), provided experiments are performed under conditions of minimal electrostatic repulsion. Since air has a dielectric constant close to that of the lipid core region of a membrane, there is a direct relationship between the partition of a drug into the air-water interface, and the partition into the lipid-water interface.8 The cross-sectional area, as well as the lipid-water partition coefficient (and by extension the air-water partition coefficient), are thus crucial parameters to assess the binding and diffusion of a drug into a lipid bilayer. In a first part of the thesis, I focused on the membrane binding step. Since the cross-sectional area of a compound is a crucial parameter for drug partitioning into the lipid bilayer, the quality of the data obtained by mean of surface activity measurements are most important. For this purpose, in a first step, I improved the calibration of the experimental settings, by assessing several factors like the evaporation or the solvent effect. In a second step, I developed computer routines for unbiased evaluation of these measurements. In a third step, I developed an algorithm to calculate the cross-sectional area of a compound oriented at a hydrophilic-hydrophobic interface; this algorithm has been calibrated on a set of measured data, in order to find from a conformational ensemble the conformation of the membrane-bound drug. In a second part of the thesis, I focused on the binding of a drug to P-glycoprotein. P-glycoprotein is monitored essentially by three types of assays, (i) the measurement of ATP hydrolysis activity of the transporter, (ii) a competition assay against calcein-AM, and (iii) a transcellular transport assay through polarized P-glycoprotein over-expressing cell monolayer. Based on a modular binding approach to assess the two-step binding of a drug to P-glycoprotein (Figure 1),5 I developed several rules to predict the outcome of these experimental assays. Each rule, predicting one particular assay, has been tested on experimental datasets. In a third part of the thesis, I developed a working interface to handle multiple structures of compounds, to calculate the new descriptors involved in the two-step binding of drugs to P-glycoprotein (membrane partitioning, and binding to the transporter), and to calculate the outcome of the prediction rules. Moreover the working interface has been designed in a way the user can easily define new rules, or even introduce a new multidrug transporter (e.g. the multidrug transporter MRP1). Starting from well characterized physical-chemical parameters, I developed a coherent ensemble of descriptors to assess by a rule-based approach the thermodynamics and kinetics of P-glycoprotein activation. This ensemble has been embedded in a customizable working interface, allowing easy evaluation of the in silico predictions

People of TM: Video Gregori Gerebtzoff

The video will be used for an external social media engagement campaign on platforms like linked-in, facebook etc. featruing stories of people in TM. No IP related content

Recherches oscillographiques et anatomo-physiologiques sur les centres cortical et thalamique du goût

SCOPUS: ar.jinfo:eu-repo/semantics/publishe