A novel class of nonpeptidic, selective thrombin inhibitors has resulted from structure-based design and subsequent improvement of the initial lead molecule. These compounds, which are preorganized for binding to thrombin through a rigid, bicyclic or tricyclic central core, could aid in the development of new antithrombotic drugs. Correlative binding and X-ray structural studies within a series of related, highly preorganized inhibitors, which all prefer similar modes of association to thrombin, generate detailed information on the strength of individual intermolecular bonding interactions and their contribution to the overall free energy of complexation.
A novel class of nonpeptidic, active, and selective thrombin inhibitors has resulted from X‐ray‐structure‐based design and subsequent improvement of the initial lead molecules. These inhibitors possess a bi‐ or tricyclic central core structure with attached side chains to reach the three binding pockets (selectivity S1 pocket, distal D pocket, and proximal P pocket) present in the active site of the enzyme. The key step in the preparation of these compounds is the 1,3‐dipolar cycloaddition between an azomethine ylide, prepared in situ by the decarboxylative method from an aromatic aldehyde and an α‐amino acid, with an N‐substituted maleimide (e.g., see Schemes 1 and 2). All potent inhibitors contain an amidinium residue in the side chain for incorporation into the S1 pocket, which was introduced in the last step of the synthesis by a Pinner reaction. The compounds were tested in biological assays for activity against thrombin and the related serine protease trypsin. The first‐generation lead compounds (±)‐11 and (±)‐19 (Scheme 1) with a bicyclic central scaffold showed Ki values for thrombin inhibition of 18 μM and 0.67 μM, respectively. Conformationally more restricted second‐generation analogs (Scheme 2) were more active ((±)‐22i: Ki=90 nM (Table 1)); yet the selectivity for thrombin over trypsin remained weak. In the third‐generation compounds, a small lipophilic side chain for incorporation into the hydrophobic P pocket was introduced (Schemes 7 and 8). Since this pocket is present in thrombin but not in trypsin, an increase in binding affinity was accompanied by an increase in selectivity for thrombin over trypsin. The most selective inhibitor (Ki=13 nM, 760‐fold selectivity for thrombin over trypsin; Table 2) was (±)‐1 with an i‐Pr group for incorporation into the P pocket. Optical resolution of (±)‐1 (Scheme 9) provided (+)‐1 with a Ki value of 7 nM and a 740‐fold selectivity, whereas (−)‐1 was 800‐fold less active (Ki=5.6 μM, 21‐fold selectivity). The absolute configuration of the stronger‐binding enantiomer was assigned based on the X‐ray crystal structure of the complex formed between thrombin and this inhibitor. Compound (+)‐1 mimics the natural thrombin substrate, fibrinogen, which binds to the enzyme with the Ph group of a phenylalanine (piperonyl in (+)‐1) in the distal D pocket, with the i‐Pr group of a valine (i‐Pr in (+)‐1) in the proximal P pocket, and with a guanidinium side chain of an arginine residue (phenylamidinium group in (+)‐1) in the selectivity S1 pocket of thrombin. A series of analogs of (±)‐1 with the phenylamidinium group replaced by aromatic and aliphatic rings bearing OH or NH2 groups (Schemes 10 – 14) were not effectively bound by thrombin. A number of X‐ray crystal‐structure analyses of free inhibitors confirmed the high degree of preorganization of these compounds in the unbound state. Since all inhibitors prefer similar modes of association with thrombin, detailed information on the strength of individual intermolecular bonding interactions and their incremental con...
Eine wirksame Hemmung der Serin‐Protease Thrombin, die bei der Blutgerinnung eine wichtige Rolle spielt, wurde mit den hier vorgestellten, de novo entwickelten Inhibitoren erreicht. Als aktivste Verbindung erwies sich dabei die rechts gezeigte. Die Röntgenstrukturanalyse eines Thromin‐Inhibitor‐Komplexes ergab den Bindungsmodus dieser Verbindungen und zeigte, daß nur das in Modellstudien vorhergesagte Enantiomer des racemischen Inhibitors im aktiven Zentrum vorlag.
Therefore, instead of converting the model forest fires from a noncumulative to a cumulative distribution, we present the frequency-area data for actual forest fires in a noncumulative form. This could be done by binning the data. However, there would be ambiguities (for example, whether the bin size is in linear or logarithmic coordinates). Therefore, in order to compare the (noncumulative) model forest fire results with real forest fires, we converted a cumulative distribution of actual fire areas t o a noncumu-lative one. We started with cumulative data, where 1(1,, is the number of forest fires per year with an area greater than A, . We defined a noncumulative distribution in terms of the negative of the derivative of the cumulative distribution with respect to A, . This value is negative because the cumulative distribution is summed from the largest t o the smallest values. The derivative (dNCFld~,) is the slope of the best-fit line for a specified number of adjacent cumulative data points. Generally, we obtained excellent results Multiple copies of a molecule, held together in finite aggregates, give rise to properties and functions that are unique to their assembled states. Because these aggregates are held together by weak forces operating over short distances, a premium is placed on complementarity: The molecular surfaces must facilitate specific interactions that direct the assembly to one aggregate rather than another. Hydrogen-bonding preferences can be combined with molecular curvature to favor the assembly of four self-complementary subunits into a pseudo-spherical capsule. Filling the capsule with smaller, complementary molecules provides the final instruction for the assembly process.
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