The van der Waals volume is a widely used descriptor in modeling physicochemical properties. However, the calculation of the van der Waals volume (V(vdW)) is rather time-consuming, from Bondi group contributions, for a large data set. A new method for calculating van der Waals volume has been developed, based on Bondi radii. The method, termed Atomic and Bond Contributions of van der Waals volume (VABC), is very simple and fast. The only information needed for calculating VABC is atomic contributions and the number of atoms, bonds, and rings. Then, the van der Waals volume (A(3)/molecule) can be calculated from the following formula: V(vdW) = summation operator all atom contributions - 5.92N(B) - 14.7R(A) - 3.8R(NR) (N(B) is the number of bonds, R(A) is the number of aromatic rings, and R(NA) is the number of nonaromatic rings). The number of bonds present (N(B)) can be simply calculated by N(B) = N - 1 + R(A) + R(NA) (where N is the total number of atoms). A simple Excel spread sheet has been made to calculate van der Waals volumes for a wide range of 677 organic compounds, including 237 drug compounds. The results show that the van der Waals volumes calculated from VABC are equivalent to the computer-calculated van der Waals volumes for organic compounds.

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The absorption models can predict the following three BCS (Biopharmaceutics Classification Scheme) classes of compounds: class I, high solubility and high permeability; class III, high solubility and low permeability; class IV, low solubility and low permeability. The absorption models overpredict the absorption of class II, low solubility and high permeability compounds because dissolution is the rate-limited step of absorption.

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Strains of the yeast Saccharomyces cerevisiae differ in their sensitivities to tobacco osmotin, an antifungal protein of the PR-5 family. However, cells sensitive to tobacco osmotin showed resistance to osmotin-like proteins purified from the plant Atriplex nummularia, indicating a strict specificity between the antifungal protein and its target cell. A member of a gene family encoding stress proteins induced by heat and nitrogen limitation, collectively called Pir proteins, was isolated among the genes that conveyed resistance to tobacco osmotin to a susceptible strain. We show that overexpression of Pir proteins increased resistance to osmotin, whereas simultaneous deletion of all PIR genes in a tolerant strain resulted in sensitivity. Pir proteins have been immunolocalized to the cell wall. The enzymatic digestion of the cell wall of sensitive and resistant cells rendered spheroplasts equally susceptible to the cytotoxic action of tobacco osmotin but not to other osmotin-like proteins, indicating that the cell membrane interacts specifically with osmotin and facilitates its action. Our results demonstrate that fungal cell wall proteins are determinants of resistance to antifungal PR-5 proteins.

Diverse functions for three soybean (Glycine max L. Merr.) cysteine proteinase inhibitors (CysPls) are inferred from unique characteristics of differential regulation of gene expression and inhibitory activities against specific Cys proteinases. Based on northern blot analyses, we found that the expression in leaves of one soybean CysPl gene (LI) was constitutive and the other two (N2 and R I ) were induced by wounding or methyl jasmonate treatment. Induction of N2 and R I transcript levels in leaves occurred coincidentally with increased papain inhibitory activity. Analyses of kinetic data from bacterial recombinant CysPl proteins indicated that soybean CysPls are noncompetitive inhibitors of papain. The inhibition constants against papain of the CysPls encoded by the wound and methyl jasmonate-inducible genes (57 and 21 nM for N2 and R1, respectively) were 500 to 1000 times lower than the inhibition constant of L1 (19,000 nM). N2 and R1 had substantially greater inhibitory activities than L l against gut cysteine proteinases of the third-instar larvae of western corn rootworm and Colorado potato beetle. Cysteine proteinases were the predominant digestive proteolytic enzymes i n the guts of these insects at this developmental stage. N2 and R1 were more inhibitory than the epoxide trans-epoxysuccinyl-~-leucylamide-(4-guanidino)butane (E-64) against western corn rootworm gut proteinases (50% inhibition concentration = 50, 200, and 7000 nM for N2, R1, and E-64, respectively). However, N2 and R1 were less effective than E-64 against the gut proteinases of Colorado potato beetle. These results indicate that the wound-inducible soybean CysPls, N2 and R1, function in host plant defense against insect predation, and that substantial variation in CysPl activity against insect digestive proteinases exists among plant CysPl proteins.Proteinaceous CysPIs, which specifically inhibit sulfl~y-dryl proteinase activities, are distributed ubiquitously among animal, plant, and microorganism species. The an-

The ability to cross the blood brain barrier (BBB), sometimes expressed as BBB+ and BBB-, is a very important property in drug design. Several computational methods have been employed for the prediction of BBB-penetrating (BBB+) and nonpenetrating (BBB-) compounds with overall accuracies from 75 to 97%. However, most of these models use a large number of descriptors (67-199), and it is not easy to implement the models in order to predict values of BBB+/-. In this work, 19 simple molecular descriptors calculated from Algorithm Builder and fragmentation schemes were used for the analysis of 1593 BBB+/- data. The results show that hydrogen-bonding properties of compounds play a very important role in modeling BBB penetration. Several BBB models based on hydrogen-bonding properties, such as Abraham descriptors, polar surface area (PSA), and number of hydrogen bonding donors and acceptors, have been built using binomial-PLS analysis. The results show that the overall classification accuracy for a training set is over 90%, and overall prediction accuracy for a test set is over 95%.