Anton Simeonov Ph.D. National Institute of Health

Review of a new method for the discovery of catalytic reactions shows its importance for also finding more optimal catalysts.

ASSAY & Drug Development Technologies offers a unique combination of original research and reports on the techniques and tools being used in cutting-edge drug development. The journal includes a “Literature Search and Review” column that identifies published papers of note and discusses their importance. GEN presents one article that was analyzed in the “Literature Search and Review” column, a paper published in Science 2011 (333: 1423–1427) titled “A simple, multidimensional approach to high-throughput discovery of catalytic reactions” and authored by D.W. Robbins and J.F. Hartwig is analyzed.

Abstract from Science

Transition metal complexes catalyze many important reactions that are employed in medicine, materials science, and energy production. Although high-throughput methods for the discovery of catalysts that would mirror related approaches for the discovery of medicinally active compounds have been the focus of much attention, these methods have not been sufficiently general or accessible to typical synthetic laboratories to be adopted widely. We report a method to evaluate a broad range of catalysts for potential coupling reactions with the use of simple laboratory equipment. Specifically, we screen an array of catalysts and ligands with a diverse mixture of substrates and then use mass spectrometry to identify reaction products that, by design, exceed the mass of any single substrate. With this method, we discovered a copper-catalyzed alkyne hydroamination and two nickel-catalyzed hydroarylation reactions, each of which displays excellent functional-group tolerance.


Testing combinations of reactants and candidate catalysts with the aim of discovering a new reaction or a more optimal catalyst has been done over the past decades in both academic and industrial settings. Almost invariably this process has required the use of robotic liquid dispensing equipment (to accommodate the large number of individual samples involved in the scheme) and/or the application of complicated deconvolution steps. To make such matrix testing easily adoptable by any typical organic synthesis laboratory, Robbins and Hartwig present a dramatically simplified workflow: candidate substrates, ligands, and catalysts are mixed by simple pipetting into a 96-well plate and the outcome of the matrix test is determined by a simple mass spectrometry analysis of a small fraction of the samples on the plate.

The authors achieve this by testing a pool of substrates dispensed in each reaction well and combining them with one individual ligand per column and one catalyst candidate per row; thus, in the proof-of-principle experiments, a pool of 17 substrates was tested against 12 ligands and eight metal catalysts (Figure 1), resulting in over 50,000 possible combinations.

Figure 1 [Taken from Science paper]: Contents of a single well in the multidimensional experiments for reaction discovery. The combination of 17 substrates was placed into each reaction well. 12 ligands were dispensed, one into each well of a column, and eight metal catalyst precursors were dispensed, one into each well of a row. The plate was sealed and heated at 100°C for 18 hours. After this time, the contents of the wells in the plate were analyzed by mass spectrometry. The number of substrates is arbitrary; the 17 substrates contain a representative set, not a comprehensive set, of typical organic functional groups. A group of catalysts derived from Mn, Fe, Cr, Co, Cu, Ni, and W was chosen because of its abundance and low cost. In addition, we examined catalysts derived from Ru and Mo because these are inexpensive relative to the more precious metals, Yb as a representative f-block metal, and Au because of its wide range of reactivity that has recently been uncovered. The ligands we combined with these metals included common phosphines and amines, as well as less explored phosphine oxides, phosphine sulfides, and amidinates (Table S1 in the article’s Supporting Online Material). Excess of the metal complexes were used in this system to alleviate poisoning all of the potential catalysts by one substrate. Reactions discovered in such a system would be rendered catalytic after initial identification of the transformation and metal-ligand combination that induces the transformation. The 17 substrates, in combination with catalysts derived from 15 metal centers and 23 ligands or the absence of a ligand, correspond to more than 50,000 reactions. These reactions were conducted in a few days, after developing our protocol. Bu, butyl; tBu, tert-butyl; Me, methyl; Ph, phenyl.

Figure 1

During the initial phase of the deconvolution, a total of 20 samples were tested by gas chromatography–mass spectroscopy (GC-MS) and electrospray ionization mass spectrometry (ESI-MS), the two techniques being used in order to capture both potential polar and nonpolar reaction products. The initial 20 samples corresponded to eight mixtures of aliquots from each row and 12 mixtures representing the 12 columns. The appearance of novel mass peaks from any of these 20 samples was flagged as a successful reaction. Further deconvolution involved judicious binary splitting of the reactants into smaller subsets and testing the simplified reaction pools (Figure 2).

Using this strategy, the authors ended up conducting only an additional 10 reactions followed by the corresponding GC-MS and ESI-MS analyses. The study is particularly noteworthy because it not only provides proof-of-principle results to support the simplified matrix testing and deconvolution strategy but also shows novel reactions with unexpected stereochemistry outcome. Additionally, new catalysts based on the more abundant and significantly cheaper earth-abundant metals such as nickel and manganese were identified.

Figure 2: Deconvolution strategy to identify coupling partners for products observed in high-throughput reaction discovery. [Taken from Science paper]

To learn about more tools and techniques aimed at simplifying workflows involved in using LC/MS for the analysis of drug candidates, click here for an article from GEN’s Mar. 1 issue.

Anton Simeoniv works at the NIH.

Previous articlePoll Respondents Undecided About Helpfulness of President’s Proposed Budgets for NIH, NSF
Next articleVelesco to Manufacture Rubicon’s TransPLEX Amplification Kits for Supply to Agendia