Proof, Computation and Agency: Logic at the Crossroads: 352 (Synthese Library)

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Berline, K. McAloon and J. Ressayre Amsterdam, This higher than normal trend continues with the Vinca binding site 15 Using CDOCKER Accelrys , a total of 10 replicas for each of the colchicine derivatives were generated and randomly distributed around the center of the binding site models. The final step in the docking procedure was scoring of the refined docked poses using the Score Ligand Poses protocol of Discovery Studio.

Note that we were not interested in the overall score for each of the ligand poses, as we were using the average energy values for the 10 poses from each experiment to build our binding energy scores. This procedure yielded ligand conformers, whose energy evaluations were performed. Specifically, those derivatives exhibiting higher binding energies than colchicine tended to have a larger distribution in their binding energies, while those with lower overall binding energies had a narrower distribution. This trend seems to correlate with the polarity of each of the functional groups at the C1 position.

To examine the role these modifications had in vitro , all of the colchicine derivatives were then synthesized and tested in both cytotoxicity and tubulin binding assays. Cytotoxicity screening was performed on a number of cell lines based on the cancer of origin and differing morphologies. Based on this observation, we felt justified in taking for each drug the mean of the logIC 50 values over a set of cell lines, and using that value as a property of the drug.

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Cytotoxicity of the colchicine derivatives. A logIC 50 of each cell line as clustered by colchicine derivative. Each point corresponds to a colchicine derivative for each of the six cell lines investigated. B logIC 50 grouped by drug functional group. C I bot grouped by cell line. All drugs except, D01 and D14 for which limited or no cytotoxicity data was available were included in this calculation. The derivatives partitioned into four groups; those with IC 50 values weaker than colchicine, those with a similar IC 50 value to colchicine, those with slightly stronger IC 50 values and finally, those with significantly stronger IC 50 values.

The thiocolchicine scaffold may play a role in the stronger IC 50 values we have observed, as thiocolchicine has been shown to have an effect approximately three times greater than that of colchicine in L murine leukemia cells We should note that while this group of derivatives was based on a thiocolchicine scaffold, rather than a colchicine scaffold, simulations show that the substitution of sulfur rather than oxygen had little or no direct effect on the binding energy not shown. The computational results are also reinforced by cytotoxicity experiments on thiocolchicine that demonstrated weaker IC 50 values than colchicine itself not shown and that it was moderately superior to colchicine at inhibiting microtubule assembly The most potent derivative in our experiments D20 had an IC 50 of 2.

Selected drugs are labeled. As the correlation is weak, other methods for calculating binding might be expected to give a better correlation. The accurate modeling of protein—drug interactions is crucial for the future development of drug design strategies. For our model protein, we have chosen tubulin as it is already the primary target for some of the most successful chemotherapeutic drugs.

Thus, it is not surprising that paclitaxel and vinblastine cause significant peripheral neurological toxicity. Modeling predictions using a particular, fixed, conformation of a binding site may therefore be unreliable. It was consistent with our hypothesis that D06, D07, D08, and D09 were moderately better than colchicine in cytotoxicity assays and that D17, D19, and D20 were consistently the most effective. However, this would require additional studies of binding kinetics as a function of temperature.

The most potent derivative D20 had an IC 50 of 2. These results also suggest that modeling, while not totally predictive, is likely to generate better drugs and that rational drug design is possible with tubulin. Table S1. Table S2. Fraction of cells that survive at the highest drug concentrations I bot values for colchicine and various colchicine derivatives, determined by cytotoxicity testing on six different cell lines.

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