Surrogate docking: structure-based virtual screening at high throughput speed

Summary Structure-based screening using fully flexible docking is still too slow for large molecular libraries. High quality docking of a million molecule library can take days even on a cluster with hundreds of CPUs. This performance issue prohibits the use of fully flexible docking in the design of large combinatorial libraries. We have developed a fast structure-based screening method, which utilizes docking of a limited number of compounds to build a 2D QSAR model used to rapidly score the rest of the database. We compare here a model based on radial basis functions and a Bayesian categorization model. The number of compounds that need to be actually docked depends on the number of docking hits found. In our case studies reasonable quality models are built after docking of the number of molecules containing 50 docking hits. The rest of the library is screened by the QSAR model. Optionally a fraction of the QSAR-prioritized library can be docked in order to find the true docking hits. The quality of the model only depends on the training set size – not on the size of the library to be screened. Therefore, for larger libraries the method yields higher gain in speed no change in performance. Prioritizing a large library with these models provides a significant enrichment with docking hits: it attains the values of 13 and 35 at the beginning of the score-sorted libraries in our two case studies: screening of the NCI collection and a combinatorial libraries on CDK2 kinase structure. With such enrichments, only a fraction of the database must actually be docked to find many of the true hits. The throughput of the method allows its use in screening of large compound collections and in the design of large combinatorial libraries. The strategy proposed has an important effect on efficiency but does not affect retrieval of actives, the latter being determined by the quality of the docking method itself. Electronic supplementary material is available at http://dx.doi.org/10.1007/s10822-005-9002-6.     

Visualization and interpretation of high content screening data

High content screening is a method for identifying small molecule modulators of mammalian cell biology. The nature of the experiment generates an enormous amount of data in the form of photographic images of cells after treatment with compounds of interest. The interpretation of data from these experiments is challenging both in terms of automatically perceiving the images, extracting, and understanding differences between screened compounds and visualizing the results. This paper discusses the application of statistical and visual methods that have been used to interpret data from a simplified DNA stain (DAPI) screen to quickly identify compounds of interest. An understanding of the mechanism of action of the screened compounds can be obtained by comparing them to control compounds of known mechanism of action. Statistical and visual methods will be shown that facilitate easy comparison of screened compounds against these control compounds. As an example, a subset of the internal repository at ArQule was screened, together with control compounds that were known to induce characteristic mitotic arrest. Subsequent data processing described in this paper permitted the easy identification of compounds that were similar to (and very different from) the control compounds.     

Synthesis of 2-pyranosyl benzothiazoles, benzimidazoles and benzoxazoles via nucleophilic addition reactions of pyranosyl nitrile oxides

Reaction of per-O-acetylated-β-d-pyranosyl nitrile oxides, generated by dehydrochlorination of the corresponding hydroximoyl chlorides, with 2-aminothiophenol afforded 2-(β-d-pyranosyl)benzothiazoles. 1,2-Diaminobenzene and 2-aminophenol reacted similarly to yield 2-(β-d-pyranosyl)benzimidazoles and 2-(β-d-pyranosyl)benzoxazoles, respectively. The structures of 2-β-d-glucopyranosylbenzimidazole (17), 2-(2,3,4-tri-O-acetyl-β-d-xylopyranosyl)benzimidazole (19) and the xylopyranosyl thiohydroximate 13 were established by X-ray crystallography.