Accurate and affordable assessment of ligand–protein affinity for structure-based virtual screening (SB-VS) is a standing challenge. Hence, empirical postdocking filters making use of various types of structure–activity information may prove useful. Here, we introduce one such filter based upon three-dimensional structural protein–ligand interaction fingerprints (SPLIF). SPLIF permits quantitative assessment of whether a docking pose interacts with the protein target similarly to a known ligand and rescues active compounds penalized by poor initial docking scores. An extensive benchmark study on 10 diverse data sets selected from the DUD-E database has been performed in order to evaluate the absolute and relative efficiency of this method. SPLIF demonstrated an overall better performance than relevant standard methods.

Systematic methods that speed-up the assignment of absolute configuration using vibrational circular dichrosim (VCD) and simplify its usage will advance this technique into a robust platform technology. Applying VCD to pharmaceutically relevant compounds has been handled in an ad hoc fashion, relying on fragment analysis and technical shortcuts to reduce the computational time required. We leverage a large computational infrastructure to provide adequate conformational exploration which enables an accurate assignment of absolute configuration. We describe a systematic approach for rapid calculation of VCD/IR spectra and comparison with corresponding measured spectra and apply this approach to assign the correct stereochemistry of nine test cases. We suggest moving away from the fragment approach when making VCD assignments. In addition to enabling faster and more reliable VCD assignments of absolute configuration, the ability to rapidly explore conformational space and sample conformations of complex molecules will have applicability in other areas of drug discovery.

The synthesis, biological evaluation and molecular modeling of a series of pyrrole compounds related to 3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid that evaluates and optimizes C-4 substituents are reported. The key factor for microtubule depolymerization activity appears to be the presence of an appropriately positioned acceptor for Cys241β in the otherwise hydrophobic subpocket A.

3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid ethyl ester is a promising antitubulin lead agent that targets the colchicine site of tubulin. C-2 analogs were synthesized and tested for microtubule depolymerizing and antiproliferative activity. Molecular modeling studies using both GOLD docking and HINT (Hydropathic INTeraction) scoring revealed two distinct binding modes that explain the structural-activity relationships and are in accord with the structural basis of colchicine binding to tubulin. The binding mode of higher activity compounds is buried deeper in the site and overlaps well with rings A and C of colchicine, while the lower activity binding mode shows fewer critical contacts with tubulin. The model distinguishes highly active compounds from those with weaker activities and provides novel insights into the colchicine site and compound design.

αβ-tubulin colchicine site inhibitors (CSIs) from four scaffolds that we previously tested for antiproliferative activity were modeled to better understand their effect on microtubules. Docking models, constructed by exploiting the SAR of a pyrrole subset and HINT scoring, guided ensemble docking of all 59 compounds. This conformation set and two variants having progressively less structure knowledge were subjected to CoMFA, CoMFA+HINT, and CoMSIA 3D-QSAR analyses. The CoMFA+HINT model (docked alignment) showed the best statistics: leave-one-out q2 of 0.616, r2 of 0.949 and r2pred (internal test set) of 0.755. An external (tested in other laboratories) collection of 24 CSIs from eight scaffolds were evaluated with the 3D-QSAR models, which correctly ranked their activity trends in 7/8 scaffolds for CoMFA+HINT (8/8 for CoMFA). The combination of SAR, ensemble docking, hydropathic analysis and 3D-QSAR provides an atomic-scale colchicine site model more consistent with a target structure resolution much higher than the ~3.6 Å available for αβ-tubulin.