Nanoscale, automated, high throughput synthesis and screening for the accelerated discovery of protein modifiers

Rapid Affinity and Microsomal Stability Ranking of Crude Mixture Libraries of Histone Deacetylase Inhibitors

The science of drug discovery involves multiparameter optimization of molecular structures through iterative design-make-test cycles. For medicinal chemistry library synthesis, traditional workflows involve the isolation of each individual compound, gravimetric quantitation, and preparation of a standard concentration solution for biological assays. In this work, we explore ways to expedite this process by testing unpurified library mixtures using a combination of mass spectrometry-based assays for affinity selection and microsomal metabolic stability. Utilizing this approach, microgram quantities of crude library mixtures can be used to identify high affinity, metabolically stable library members for isolation and full characterization. This streamlined approach was demonstrated for the synthesis and evaluation of two libraries of histone deacetylase inhibitors and was shown to generate decision-making data in line with traditional workflows. The advantages of this paradigm include greatly reduced cycle time, reduced material requirements, and concentration of resources on the most promising compounds.

An Automated Purification Workflow Coupled with Material-Sparing High-Throughput 1H NMR for Parallel Medicinal Chemistry

In medicinal chemistry, purification and characterization of organic compounds is an ever-growing challenge, with an increasing number of compounds being synthesized at a decreased scale of preparation. In response to this trend, we developed a parallel medicinal chemistry (PMC)-tailored platform, coupling automated purification to mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) on a range of synthetic scales (∼3.0-75.0 μmol). Here, the generation and acquisition of 1.7 mm NMR samples is fully integrated into a high-throughput automated workflow, processing 36 000 compounds yearly. Utilizing dead volume, which is inaccessible in conventional liquid handling, NMR samples are generated on as little as 10 μg without consuming material prioritized for biological assays. As miniaturized PMC synthesis becomes the industry standard, we can now obtain quality NMR spectra from limited material. Paired with automated structure verification, this platform has the potential to allow NMR to become as important for high-throughput analysis as ultrahigh performance liquid chromatography (UPLC)-MS.

The Evaluation of Debranone Series Strigolactone Agonists for Germination Stimulants in Orobanche Species

Strigolactones (SLs) are plant hormones that regulate shoot branching. In addition, SLs act as compounds that stimulate the germination of root parasitic weeds, such as Striga spp. and Orobanche spp., which cause significant damage to agriculture worldwide. Thus, SL agonists have the potential to induce suicidal germination, thereby reducing the seed banks of root parasitic weeds in the soil. Particularly, phenoxyfuranone-type SL agonists, known as debranones, exhibit SL-like activity in rice and Striga hermonthica. However, little is known about their effects on Orobanche spp. In this study, we evaluated the germination-inducing activity of debranones against Orobanche minor. Analysis of structure-activity relationships revealed that debranones with electron-withdrawing substituents at the 2,4- or 2,6-position strongly induced the germination of Orobanche minor. Lastly, biological assays indicated that 5-(2-fluoro-4-nitrophenoxy)-3-methylfuran-2(5H)-one (test compound 61) induced germination to a comparable or even stronger extent than GR24, a well-known synthetic SL. Altogether, our data allowed us to infer that this enhanced activity was due to the recognition of compound 61 by the SLs receptor, KAI 2d, in Orobanche minor.

Generation of multimillion chemical space based on the parallel Groebke-Blackburn-Bienaymé reaction

Parallel Groebke-Blackburn-Bienaymé reaction was evaluated as a source of multimillion chemically accessible chemical space. Two most popular classical protocols involving the use of Sc(OTf)3 and TsOH as the catalysts were tested on a broad substrate scope, and prevalence of the first method was clearly demonstrated. Furthermore, the scope and limitations of the procedure were established. A model 790-member library was obtained with 85% synthesis success rate. These results were used to generate a 271-Mln. readily accessible (REAL) heterocyclic chemical space mostly containing unique chemotypes, which was confirmed by comparative analysis with commercially available compound collections. Meanwhile, this chemical space contained 432 compounds that already showed biological activity according to the ChEMBL database.

Carbenoid-involved reactions integrated with scaffold-based screening generates a Nav1.7 inhibitor

The discovery of selective Nav1.7 inhibitors is a promising approach for developing anti-nociceptive drugs. In this study, we present a novel oxindole-based readily accessible library (OREAL), which is characterized by readily accessibility, unique chemical space, ideal drug-like properties, and structural diversity. We used a scaffold-based approach to screen the OREAL and discovered compound C4 as a potent Nav1.7 inhibitor. The bioactivity characterization of C4 reveals that it is a selective Nav1.7 inhibitor and effectively reverses Paclitaxel-induced neuropathic pain (PINP) in rodent models. Preliminary toxicology study shows C4 is negative to hERG. The consistent results of molecular docking and molecular simulations further support the reasonability of the in-silico screening and show the insight of the binding mode of C4. Our discovery of C4 paves the way for pushing the Nav1.7-based anti-nociceptive drugs forward to the clinic.

Direct-to-biology platform: From synthesis to biological evaluation of SHP2 allosteric inhibitors

Tyrosine phosphatase SHP2 is a proto-oncogenic protein involved in cell growth and differentiation via diverse intracellular signaling pathways. With the scope of identifying new SHP2 allosteric inhibitors, we report here the development and optimization of a high-throughput "Direct-to-Biology" (D2B) workflow including the synthesis and the biological evaluation of the reaction crude, thus eliminating the need for purification. During this labor-saving procedure, the structural diversity was introduced through a SNAr reaction. A wide array of analogues with good chemical purity was generated, allowing the obtention of reliable biological data which validated this efficient technique. This approach enabled the fast evaluation of a variety of structurally diverse fragments leading to nanomolar SHP2 allosteric inhibitors and a new series bearing a novel bicyclo[3.1.0]hexane moiety.

Novel SK channel positive modulators prevent ferroptosis and excitotoxicity in neuronal cells

Small conductance calcium-activated potassium (SK) channel activity has been proposed to play a role in the pathology of several neurological diseases. Besides regulating plasma membrane excitability, SK channel activation provides neuroprotection against ferroptotic cell death by reducing mitochondrial Ca2+ uptake and reactive oxygen species (ROS). In this study, we employed a multifaceted approach, integrating structure-based and computational techniques, to strategically design and synthesize an innovative class of potent small-molecule SK2 channel modifiers through highly efficient multicomponent reactions (MCRs). The compounds' neuroprotective activity was compared with the well-studied SK positive modulator, CyPPA. Pharmacological SK channel activation by selected compounds confers neuroprotection against ferroptosis at low nanomolar ranges compared to CyPPA, that mediates protection at micromolar concentrations, as shown by an MTT assay, real-time cell impedance measurements and propidium iodide staining (PI). These novel compounds suppress increased mitochondrial ROS and Ca2+ level induced by ferroptosis inducer RSL3. Moreover, axonal degeneration was rescued by these novel SK channel activators in primary mouse neurons and they attenuated glutamate-induced neuronal excitability, as shown via microelectrode array. Meanwhile, functional afterhyperpolarization of the novel SK2 channel modulators was validated by electrophysiological measurements showing more current change induced by the novel modulators than the reference compound, CyPPA. These data support the notion that SK2 channel activation can represent a therapeutic target for brain diseases in which ferroptosis and excitotoxicity contribute to the pathology.

A Brief Introduction to Chemical Reaction Optimization

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

'Chemistry at the speed of sound': automated 1536-well nanoscale synthesis of 16 scaffolds in parallel

Screening of large and diverse libraries is the 'bread and butter' in the first phase of the discovery of novel drugs. However, maintenance and periodic renewal of high-quality large compound collections pose considerable logistic, environmental and monetary problems. Here, we exercise an alternative, the 'on-the-fly' synthesis of large and diverse libraries on a nanoscale in a highly automated fashion. For the first time, we show the feasibility of the synthesis of a large library based on 16 different chemistries in parallel on several 384-well plates using the acoustic dispensing ejection (ADE) technology platform. In contrast to combinatorial chemistry, we produced 16 scaffolds at the same time and in a sparse matrix fashion, and each compound was produced by a random combination of diverse large building blocks. The synthesis, analytics, resynthesis of selected compounds, and chemoinformatic analysis of the library are described. The advantages of the herein described automated nanoscale synthesis approach include great library diversity, absence of library storage logistics, superior economics, speed of synthesis by automation, increased safety, and hence sustainable chemistry.

Discovery of Biologically Optimized Polymyxin Derivatives Facilitated by Peptide Scanning and In Situ Screening Chemistry

Peptides can be converted to highly active compounds by introducing appropriate substituents on the suitable amino acid residue. Although modifiable residues in peptides can be systematically identified by peptide scanning methodologies, there is no practical method for optimization at the "scanned" position. With the purpose of using derivatives not only for scanning but also as a starting point for further chemical functionalization, we herein report the "scanning and direct derivatization" strategy through chemoselective acylation of embedded threonine residues by a serine/threonine ligation (STL) with the help of in situ screening chemistry. We have applied this strategy to the optimization of the polymyxin antibiotics, which were selected as a model system to highlight the power of the rapid derivatization of active scanning derivatives. Using this approach, we explored the structure-activity relationships of the polymyxins and successfully prepared derivatives with activity against polymyxin-resistant bacteria and those with Pseudomonas aeruginosa selective antibacterial activity. This strategy opens up efficient structural exploration and further optimization of peptide sequences.

Integrated and automated high-throughput purification of libraries on microscale

We herein report the development of an automation platform for rapid purification and quantification of chemical libraries including reformatting of chemical matter to 10 mM DMSO stock solutions. This fully integrated workflow features tailored conditions for preparative reversed-phase (RP) HPLC-MS on microscale based on analytical data, online fraction QC and CAD-based quantification as well as automated reformatting to enable rapid purification of chemical libraries. This automated workflow is entirely solution-based, eliminating the need to weigh or handle solids. This increases process efficiency and creates a link between high-throughput synthesis and profiling of novel chemical matter with respect to biological and physicochemical properties in relevant assays.

Optimization of Covalent MKK7 Inhibitors via Crude Nanomole-Scale Libraries

High-throughput nanomole-scale synthesis allows for late-stage functionalization (LSF) of compounds in an efficient and economical manner. Here, we demonstrated that copper-catalyzed azide-alkyne cycloaddition could be used for the LSF of covalent kinase inhibitors at the nanoscale, enabling the synthesis of hundreds of compounds that did not require purification for biological assay screening, thus reducing experimental time drastically. We generated crude libraries of inhibitors for the kinase MKK7, derived from two different parental precursors, and analyzed them via the high-throughput In-Cell Western assay. Select inhibitors were resynthesized, validated via conventional biological and biochemical methods such as western blots and liquid chromatography-mass spectrometry (LC-MS) labeling, and successfully co-crystallized. Two of these compounds showed over 20-fold increased inhibitory activity compared to the parental compound. This study demonstrates that high-throughput LSF of covalent inhibitors at the nanomole-scale level can be an auspicious approach in improving the properties of lead chemical matter.

Synthesis and direct assay of large macrocycle diversities by combinatorial late-stage modification at picomole scale

Macrocycles have excellent potential as therapeutics due to their ability to bind challenging targets. However, generating macrocycles against new targets is hindered by a lack of large macrocycle libraries for high-throughput screening. To overcome this, we herein established a combinatorial approach by tethering a myriad of chemical fragments to peripheral groups of structurally diverse macrocyclic scaffolds in a combinatorial fashion, all at a picomole scale in nanoliter volumes using acoustic droplet ejection technology. In a proof-of-concept, we generate a target-tailored library of 19,968 macrocycles by conjugating 104 carboxylic-acid fragments to 192 macrocyclic scaffolds. The high reaction efficiency and small number of side products of the acylation reactions allowed direct assay without purification and thus a large throughput. In screens, we identify nanomolar inhibitors against thrombin (K_i = 44 ± 1 nM) and the MDM2:p53 protein-protein interaction (K_d MDM2 = 43 ± 18 nM). The increased efficiency of macrocycle synthesis and screening and general applicability of this approach unlocks possibilities for generating leads against any protein target.

Macrocycles have potential as therapeutics, but their libraries are currently not large enough for high-throughput screening. Here, the authors show a combinatorial approach to generate a library of almost 20’000 macrocycles by conjugating carboxylic-acid fragments to macrocyclic scaffolds, identifying nanomolar inhibitors against thrombin and binders of MDM2.

Artificial intelligence to bring nanomedicine to life

The technology of drug delivery systems (DDSs) has demonstrated an outstanding performance and effectiveness in production of pharmaceuticals, as it is proved by many FDA-approved nanomedicines that have an enhanced selectivity, manageable drug release kinetics and synergistic therapeutic actions. Nonetheless, to date, the rational design and high-throughput development of nanomaterial-based DDSs for specific purposes is far from a routine practice and is still in its infancy, mainly due to the limitations in scientists' capabilities to effectively acquire, analyze, manage, and comprehend complex and ever-growing sets of experimental data, which is vital to develop DDSs with a set of desired functionalities. At the same time, this task is feasible for the data-driven approaches, high throughput experimentation techniques, process automatization, artificial intelligence (AI) technology, and machine learning (ML) approaches, which is referred to as The Fourth Paradigm of scientific research. Therefore, an integration of these approaches with nanomedicine and nanotechnology can potentially accelerate the rational design and high-throughput development of highly efficient nanoformulated drugs and smart materials with pre-defined functionalities. In this Review, we survey the important results and milestones achieved to date in the application of data science, high throughput, as well as automatization approaches, combined with AI and ML to design and optimize DDSs and related nanomaterials. This manuscript mission is not only to reflect the state-of-art in data-driven nanomedicine, but also show how recent findings in the related fields can transform the nanomedicine's image. We discuss how all these results can be used to boost nanomedicine translation to the clinic, as well as highlight the future directions for the development, data-driven, high throughput experimentation-, and AI-assisted design, as well as the production of nanoformulated drugs and smart materials with pre-defined properties and behavior. This Review will be of high interest to the chemists involved in materials science, nanotechnology, and DDSs development for biomedical applications, although the general nature of the presented approaches enables knowledge translation to many other fields of science.

Picomole-Scale Synthesis and Screening of Macrocyclic Compound Libraries by Acoustic Liquid Transfer

Macrocyclic compounds are an attractive class of therapeutic ligands against challenging targets, such as protein-protein interactions. However, the development of macrocycles as drugs is hindered by the lack of large combinatorial macrocyclic libraries, which are cumbersome, expensive, and time consuming to make, screen, and deconvolute. Here, we established a strategy for synthesizing and screening combinatorial libraries on a picomolar scale by using acoustic droplet ejection to combine building blocks at nanoliter volumes, which reduced the reaction volumes, reagent consumption, and synthesis time. As a proof-of-concept, we assembled a 2700-member target-focused macrocyclic library that we could subsequently assay in the same microtiter synthesis plates, saving the need for additional transfers and deconvolution schemes. We screened the library against the MDM2-p53 protein-protein interaction and generated micromolar and sub-micromolar inhibitors. Our approach based on acoustic liquid transfer provides a general strategy for the development of macrocycle ligands.