Computational and molecular modeling evaluation of the structural basis for tubulin polymerization inhibition by colchicine site agents

The computer-automated structure evaluation programs MultiCASE and CASE were used to perform a quantitative structure-activity relationship study on tubulin polymerization inhibitors. A learning set of 536 chemicals (202 active, 27 marginal, and 307 inactive), built using IC 50 values for inhibition of tubulin polymerization or mitosis from this and previous studies, was used for artificial intelligence self-teaching. The algorithms successfully predicted the activity of agents in the learning set with > 90% accuracy. Seventeen MultiCASE and twelve CASE (mostly included in the MultiCASE set) biophores (substructures significantly correlated with activity) were identified with a probability > 0.95. Here we present the biophores of podophyllotoxins, colchicinoids, and certain combretastatins, each examined for structure-activity relationships. For the podophyllotoxins and colchicinoids in the learning set, the correlations between observed and predicted potencies were > 0.85. The algorithms recognized the importance of several known site, electronic, and steric effects in the two classes. A predictive QSAR ( R 2 = 0.98) was developed for combretastatin A-2 and dihydrocombretastatin analogues. The MultiCASE/CASE analyzes were used in combination with molecular models to study relative orientations of colchicine, podophyllotoxin, combretastatin A-4, and steganacin at the colchicine site. This resulted in a new hypothesis, consistent with extensive published experimental data, in which the C-ring and part of the B-ring of colchicine overlap with the A- and B-rings of podophyllotoxin. Consequently, the trimethoxyphenyl rings of colchicine and podophyllotoxin occupied different regions of space, each pointing out from a hydrophobic ‘core’ occupied by the overlapping biophores. The molecular model of the highly potent combretastatin A-4 could fit into the model binding site in at least three different ways. The developed QSARs were used to identify the potent microtubule stabilizer discodermolide. Its identification, in concert with recently reported findings, suggest potential overlap in the colchicine and paclitaxel binding sites on tubulin. Computational QSAR led to discovery of the potent microtubule stabilizer (+)-discodermolide.