Our database contains three-dimensional pharmaceutical structures simulated and optimized with the molecular modeling software Macromodel. The database has been compiled from the compounds contained in "Drug in Japan: Ethical Drugs", edited by the Japan pharmaceutical information center (Tokyo, Japan) in the initial stage of its development. The three-dimensional models were stored on the Web server where they can be viewed, rotated, and animated by the client with either the plug-in, Chemscape Chime, or the Java Applet, Chemis3D. We applied a molecular dynamics simulation to the molecular motion trajectories; three-dimensional animation demonstrates the actual movement and rotation of molecules on their bond axes. This database provides both zipped coordination files indicating conformational distribution for each drug and zipped virtual reality modeling language (VRML) files indicating its electrostatic potential mapped on the electron density surface. A search of the pharmaceutical structures can be conducted through drawing of partial plane structures or input of general names with JChem software to the SQL server containing fully optimized structural data.

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Derivatives of dimethy-2-phenoxyethylsulfonium p-toluenesulfonate (1) were evaluated for anti-allergic activity to develop the drug for treatment of type I allergic diseases as a lead optimization step. The IgE-induced passive cutaneous anaphylaxis (PCA) of rats was inhibited upon oral administration by 3-ethoxy, 3-phenoxy, and 2, 3-diethoxypropoxyphenoxy derivatives. The lead compound 2-[4-(3-ethoxy-2-hydroxypropoxy)phenoxy]ethyldimethyl- sulfonium p-toluenesulfonate (11) was selected as a candidate for preclinical study by considering its toxicity and cholinergic activity.

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Human ABCB1 (P-glycoprotein or MDR1) mediates the elimination of a variety of drugs from cells and thereby plays a critical role in determining the pharmacokinetic profiles of drugs in our body. In the present study, we have developed a high-speed screening system to investigate the substrate specificity of ABCB1 towards a variety of drugs and compounds. The plasma membrane fraction of Sf9 insect cells overexpressing human ABCB1 was used to measure the ATPase activity. Among 41 different compounds and therapeutic drugs tested in this study, Ca²⁺ channel blockers, such as verapamil, bepridil, fendiline, prenylamine, and nicardipine, stimulated the ATPase activity. Doxorubicin, paclitaxel, quinidine, and FK506 also stimulated the ABCB1 ATPase activity, although to an extent relatively smaller than that of the Ca²⁺ channel blockers. We have measured the surface activity of those 41 different compounds. A two-dimensional plot of the air-water partition coefficient (K_aw) vs. ABCB1 ATPase activity clearly classified those compounds into two groups; namely, ABCB1 substrate and non-substrate groups. ABCB1 substrates were found to have a log K_aw value higher than 4.3. Based on the ABCB1 ATPase activity, we have analyzed structure-activity relationships (SAR) for a total of 37 different compounds. The multiple linear regression analysis delineates a clear relationship between the ABCB1 ATPase activity and the chemical fragmentation codes. Thereby, we have identified multiple sets of chemical fragmentation codes closely related with the substrate specificity of ABCB1. This approach is considered to be practical and useful for the molecular design of such new drugs that can penetrate the blood-brain-barrier or circumvent the multidrug resistance of human cancer.

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Structurally analogous protein pairs with low sequence identity, such as analogues and remote homologues, comprise a large part of structurally similar pairs thus complicating the relationship between sequence and structure. To obtain clues for clarifying such intricate relationships, we developed a method to analyze the coarse-grained charge distribution in an amino acid sequence and analyzed the pattern of charge distribution for the pairs of structurally similar proteins with sequence identities lower than 20%. We found two types of pairs, those with similar patterns of charge distribution and those with inverted charge distribution. This finding suggested that the charge distribution in a sequence might be a good parameter for clustering the structures as analogs and remote homologs. The possibility of automatic fold recognition is discussed by a quantitative comparison of charge distribution patterns.

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        were called
P133  Table 1
        1C  receptor)
        2A  neclear (misspelling)
P134  line 15 & 23
         xenbiotic (misspelling)
P135  Figure 1
        endcrine (misspelling)
P140  Figure 5
        rodification (misspelling)
Right:P130  line 12
        was called
P133  Table 1
        1C  PPAR (Peroxisome proliferator activated receptor)
        2A  nuclear
P134  line 15 & 23
        xenobiotic
P135  Figure 1
        Endocrine
P140  Figure 5
        modification

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