Most drugs are developed through iterative rounds of chemical synthesis and biochemical testing to optimize the affinity of a particular compound for a protein target of therapeutic interest. This process is challenging because candidate molecules must be selected from a chemical space of more than 10 drug-like possibilities , and a single reaction used to synthesize each molecule has more than 10 plausible permutations of catalysts, ligands, additives and other parameters . The merger of a method for high-throughput chemical synthesis with a biochemical assay would facilitate the exploration of this enormous search space and streamline the hunt for new drugs and chemical probes. Miniaturized high-throughput chemical synthesis has enabled rapid evaluation of reaction space, but so far the merger of such syntheses with bioassays has been achieved with only low-density reaction arrays, which analyse only a handful of analogues prepared under a single reaction condition. High-density chemical synthesis approaches that have been coupled to bioassays, including on-bead , on-surface , on-DNA and mass-encoding technologies , greatly reduce material requirements, but they require the covalent linkage of substrates to a potentially reactive support, must be performed under high dilution and must operate in a mixture format. These reaction attributes limit the application of transition-metal catalysts, which are easily poisoned by the many functional groups present in a complex mixture, and of transformations for which the kinetics require a high concentration of reactant. Here we couple high-throughput nanomole-scale synthesis with a label-free affinity-selection mass spectrometry bioassay. Each reaction is performed at a 0.1-molar concentration in a discrete well to enable transition-metal catalysis while consuming less than 0.05 milligrams of substrate per reaction. The affinity-selection mass spectrometry bioassay is then used to rank the affinity of the reaction products to target proteins, removing the need for time-intensive reaction purification. This method enables the primary synthesis and testing steps that are critical to the invention of protein inhibitors to be performed rapidly and with minimal consumption of starting materials.

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Recent advances in understanding the relevance of noncoding RNA (ncRNA) to disease have increased interest in drugging ncRNA with small molecules. The recent discovery of ribocil, a structurally distinct synthetic mimic of the natural ligand of the flavin mononucleotide (FMN) riboswitch, has revealed the potential chemical diversity of small molecules that target ncRNA. Affinity-selection mass spectrometry (AS-MS) is theoretically applicable to high-throughput screening (HTS) of small molecules binding to ncRNA. Here, we report the first application of the Automated Ligand Detection System (ALIS), an indirect AS-MS technique, for the selective detection of small molecule-ncRNA interactions, high-throughput screening against large unbiased small-molecule libraries, and identification and characterization of novel compounds (structurally distinct from both FMN and ribocil) that target the FMN riboswitch. Crystal structures reveal that different compounds induce various conformations of the FMN riboswitch, leading to different activity profiles. Our findings validate the ALIS platform for HTS screening for RNA-binding small molecules and further demonstrate that ncRNA can be broadly targeted by chemically diverse yet selective small molecules as therapeutics.

A novel series of CHK1 inhibitors with a distinctive hinge binding mode, exemplified by 2-aryl-N-(2-(piperazin-1-yl)phenyl)thiazole-4-carboxamide, was discovered through high-throughput screening using the affinity selection−mass spectrometry (AS-MS)-based Automated Ligand Identification System (ALIS) platform. Structure-based ligand design and optimization led to significant improvements in potency to the single digit nanomolar range and hundred-fold selectivity against CDK2.KEYWORDS: affinity selection−mass spectrometry (AS-MS), Automated Ligand Identification System (ALIS), CHK1 protein kinase, structure-based drug design, thiazole-4-carboxamide C ancer is the leading cause of death globally. 1 Among the treatments used in cancer clinics, DNA-damaging chemotherapies have received widespread use despite their severe side effects on highly proliferative tissues and vulnerability to drug resistance. 2 There is an urgent need in cancer therapy for improved tolerability and longer lasting efficacy. When cells are exposed to agents that induce DNA damage, DNA repair pathways are activated by arresting at various cell cycle check points, G1, S, and G2/M. 3 While normal cells could arrest in the G1 phase through the tumor suppressor protein p53, most cancer cells lack this option because of p53 mutations and will have to rely on the S or G2/M checkpoint for DNA repair and survival. Such reliance in p53 mutant cancer cells would offer a significant opportunity for targeted cancer therapy. 4 CHK1 (checkpoint kinase 1) is a serine/threonine kinase and the key mediator in S and G2/M checkpoints. 5 The abrogation of CHK1 and the remaining checkpoints consequentially will cause cancer cells with DNA damage premature entry into mitosis and result in cell death. 6 Therefore, an enlarged therapeutic window would be expected in anticancer therapies utilizing a combination of a DNA-damaging agent with a CHK1 inhibitor.Over the past years, extensive research efforts in CHK1 inhibition have been undertaken in oncology. Several small molecule CHK1 inhibitors have been discovered and entered into clinical trials. 7−11 In our efforts to discover novel small molecule CHK1 inhibitors, the AS-MS ALIS (affinity selection−mass spectrometry-based Automated Ligand Identification System) platform was used to identify hits from mixture-based combinatorial libraries. 12 ALIS has demonstrated its unique capability in screening label-free mixture-based libraries and finding hits that were subsequently developed into lead compounds in various classes of protein targets, including the anti-infective target Escherichia coli dihydrofolate reductase, 13 antibacterial AccC (acetyl coenzyme-A carboxylase), 14 HCV NS5B (hepatitis C virus nonstructural protein 5B) polymerase, 15−17 protein kinase CDK2 (cyclin-dependent kinase 2), 18 KSP (kinesin spindle protein) in oncology, 19 FABP4 (fatty acid binding protein-4) 20 and the lipid phosphatase SHIP2 (SH2 domain-containing inositol 5-phosphatase 2) 21 in diabetes, MK2 (mitogen-activated protein ...

The primary objective of early drug discovery is to associate druggable target space with a desired phenotype. The inability to efficiently associate these often leads to failure early in the drug discovery process. In this proof-of-concept study, the most tractable starting points for drug discovery within the NF-κB pathway model system were identified by integrating affinity selection-mass spectrometry (AS-MS) with functional cellular assays. The AS-MS platform Automated Ligand Identification System (ALIS) was used to rapidly screen 15 NF-κB proteins in parallel against large-compound libraries. ALIS identified 382 target-selective compounds binding to 14 of the 15 proteins. Without any chemical optimization, 22 of the 382 target-selective compounds exhibited a cellular phenotype consistent with the respective target associated in ALIS. Further studies on structurally related compounds distinguished two chemical series that exhibited a preliminary structure-activity relationship and confirmed target-driven cellular activity to NF-κB1/p105 and TRAF5, respectively. These two series represent new drug discovery opportunities for chemical optimization. The results described herein demonstrate the power of combining ALIS with cell functional assays in a high-throughput, target-based approach to determine the most tractable drug discovery opportunities within a pathway.