Drug Target Strategies

ALIS Affinity Selection in Pharmaceutical Discovery

Wednesday, February 7
9:30 AM - 10:00 AM
Location: 6D

Affinity selection mass spectrometry (ASMS) is a general, high-throughput method to select and identify small molecule ligands from complex compound mixtures. Merck has advanced a specific ASMS approach termed ALIS (Automated Ligand Identification System), a two-dimensional LC/MS system in line with high-resolution mass spectrometry, to routinely assess one million compound / target encounters per day. This high throughput capability, while traditionally employed for small molecule hit identification, has recently been adapted to deconvolute molecular targets of phenotypically active compounds of unknown mechanism, in an approach termed Protein Array ALIS (PA-ALIS), and to quantitatively rank order the binding affinity of medicinal chemistry analogs in complex mixtures (Protein Titration or PT-ALIS). The PT-ALIS method, when combined with nanoscale parallel or mixture synthesis permits identification of analogs most likely to exhibit potent functional activity starting from very small quantities of material and without need for compound purification prior to biological assay. An introduction to ALIS and the novel application to medicinal chemistry and target identification will be presented.

Peter J. Dandliker

Director
Merck

Professional Background: Dr. Dandliker leads the Merck ALIS affinity screening group, located in Boston. In 20 years of pharmaceutical discovery research, Peter has held a range of leadership roles at the chemistry / biology interface, establishing teams dedicated to hit-to-lead medicinal chemistry and biology, high-throughput ADME, and founding a research lab on behalf of a western pharma company in Shanghai. He enjoys purposeful technical innovation in the areas of target & lead discovery, pharmacological characterization, and chemical optimization, and applying those new capabilities to discovery programs. He holds a Ph.D. in organic chemistry from UCLA and performed his postdoctoral work at the California Institute of Technology.

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