Medicinal Chemistry Gone Wild.

Earth is currently experiencing a mass extinction event. The flora and fauna of our planet are experiencing mass die-offs from a multitude of factors, with wildlife disease emerging as one parameter where medicinal chemists are equipped to intervene. While contemporary medicinal chemistry focuses on human health, many traditional pharmaceutical companies have historic roots in human health, animal health, and plant health. This trifecta of health sciences perfectly maps to the current field of One Health, which recognizes that optimal health outcomes can only be achieved through the health of humans, plants, animals, and their shared environments. This Perspective imagines a world where state-of-the-art medicinal chemistry tactics are used to prevent the extinction of endangered species and points to preliminary work in the emerging area of conservation medicine.

Late-Stage Saturation of Drug Molecules.

The available methods of chemical synthesis have arguably contributed to the prevalence of aromatic rings, such as benzene, toluene, xylene, or pyridine, in modern pharmaceuticals. Many such sp2-carbon-rich fragments are now easy to synthesize using high-quality cross-coupling reactions that click together an ever-expanding menu of commercially available building blocks, but the products are flat and lipophilic, decreasing their odds of becoming marketed drugs. Converting flat aromatic molecules into saturated analogues with a higher fraction of sp3 carbons could improve their medicinal properties and facilitate the invention of safe, efficacious, metabolically stable, and soluble medicines. In this study, we show that aromatic and heteroaromatic drugs can be readily saturated under exceptionally mild rhodium-catalyzed hydrogenation, acid-mediated reduction, or photocatalyzed-hydrogenation conditions, converting sp2 carbon atoms into sp3 carbon atoms and leading to saturated molecules with improved medicinal properties. These methods are productive in diverse pockets of chemical space, producing complex saturated pharmaceuticals bearing a variety of functional groups and three-dimensional architectures. The rhodium-catalyzed method tolerates traces of dimethyl sulfoxide (DMSO) or water, meaning that pharmaceutical compound collections, which are typically stored in wet DMSO, can finally be reformatted for use as substrates for chemical synthesis. This latter application is demonstrated through the late-stage saturation (LSS) of 768 complex and densely functionalized small-molecule drugs.

Exploring the combinatorial explosion of amine-acid reaction space via graph editing.

Amines and carboxylic acids are abundant chemical feedstocks that are nearly exclusively united via the amide coupling reaction. The disproportionate use of the amide coupling leaves a large section of unexplored reaction space between amines and acids: two of the most common chemical building blocks. Herein we conduct a thorough exploration of amine-acid reaction space via systematic enumeration of reactions involving a simple amine-carboxylic acid pair. This approach to chemical space exploration investigates the coarse and fine modulation of physicochemical properties and molecular shapes. With the invention of reaction methods becoming increasingly automated and bringing conceptual reactions into reality, our map provides an entirely new axis of chemical space exploration for rational property design.

Rapid planning and analysis of high-throughput experiment arrays for reaction discovery.

High-throughput experimentation (HTE) is an increasingly important tool in reaction discovery. While the hardware for running HTE in the chemical laboratory has evolved significantly in recent years, there remains a need for software solutions to navigate data-rich experiments. Here we have developed phactor™, a software that facilitates the performance and analysis of HTE in a chemical laboratory. phactor™ allows experimentalists to rapidly design arrays of chemical reactions or direct-to-biology experiments in 24, 96, 384, or 1,536 wellplates. Users can access online reagent data, such as a chemical inventory, to virtually populate wells with experiments and produce instructions to perform the reaction array manually, or with the assistance of a liquid handling robot. After completion of the reaction array, analytical results can be uploaded for facile evaluation, and to guide the next series of experiments. All chemical data, metadata, and results are stored in machine-readable formats that are readily translatable to various software. We also demonstrate the use of phactor™ in the discovery of several chemistries, including the identification of a low micromolar inhibitor of the SARS-CoV-2 main protease. Furthermore, phactor™ has been made available for free academic use in 24- and 96-well formats via an online interface.

Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit.

Machine learning models are increasingly being utilized to predict outcomes of organic chemical reactions. A large amount of reaction data is used to train these models, which is in stark contrast to how expert chemists discover and develop new reactions by leveraging information from a small number of relevant transformations. Transfer learning and active learning are two strategies that can operate in low-data situations, which may help fill this gap and promote the use of machine learning for tackling real-world challenges in organic synthesis. This Perspective introduces active and transfer learning and connects these to potential opportunities and directions for further research, especially in the area of prospective development of chemical transformations.

Formal Cross-Coupling of Amines and Carboxylic Acids to Form sp3-sp2 Carbon-Carbon Bonds.

Amines and carboxylic acids are abundant synthetic building blocks that are classically united to form an amide bond. To access new pockets of chemical space, we are interested in the development of amine-acid coupling reactions that complement the amide coupling. In particular, the formation of carbon-carbon bonds by formal deamination and decarboxylation would be an impactful addition to the synthesis toolbox. Here, we report a formal cross-coupling of alkyl amines and aryl carboxylic acids to form C(sp3)-C(sp2) bonds following preactivation of the amine-acid building blocks as a pyridinium salt and N-acyl-glutarimide, respectively. Under nickel-catalyzed reductive cross-coupling conditions, a diversity of simple and complex substrates are united in good to excellent yield, and numerous pharmaceuticals are successfully diversified. High-throughput experimentation was leveraged in the development of the reaction and the discovery of performance-enhancing additives such as phthalimide, RuCl3, and GaCl3. Mechanistic investigations suggest phthalimide may play a role in stabilizing productive Ni complexes rather than being involved in oxidative addition of the N-acyl-imide and that RuCl3 supports the decarbonylation event, thereby improving reaction selectivity.

Computer-aided key step generation in alkaloid total synthesis.

Efficient chemical synthesis is critical to satisfying future demands for medicines, materials, and agrochemicals. Retrosynthetic analysis of modestly complex molecules has been automated over the course of decades, but the combinatorial explosion of route possibilities has challenged computer hardware and software until only recently. Here, we explore a computational strategy that merges computer-aided synthesis planning with molecular graph editing to minimize the number of synthetic steps required to produce alkaloids. Our study culminated in an enantioselective three-step synthesis of (-)-stemoamide by leveraging high-impact key steps, which could be identified in computer-generated retrosynthesis plans using graph edit distances.

Repurposing amine and carboxylic acid building blocks with an automatable esterification reaction.

New methodologies to unite amines and carboxylic acids that complement the popular amide coupling can significantly expand accessible chemical space if they yield products distinct from the classic R-NHC(O)-R' amide arrangement. Here we have developed an amine-acid esterification reaction based on pyridinium salt activation of amine C-N bonds to create products of type R-OC(O)-R' upon reaction with alkyl and aryl carboxylic acids. The protocol is robust and facile as demonstrated by automation on open-source robotics.

Predicting reaction conditions from limited data through active transfer learning.

Transfer and active learning have the potential to accelerate the development of new chemical reactions, using prior data and new experiments to inform models that adapt to the target area of interest. This article shows how specifically tuned machine learning models, based on random forest classifiers, can expand the applicability of Pd-catalyzed cross-coupling reactions to types of nucleophiles unknown to the model. First, model transfer is shown to be effective when reaction mechanisms and substrates are closely related, even when models are trained on relatively small numbers of data points. Then, a model simplification scheme is tested and found to provide comparative predictivity on reactions of new nucleophiles that include unseen reagent combinations. Lastly, for a challenging target where model transfer only provides a modest benefit over random selection, an active transfer learning strategy is introduced to improve model predictions. Simple models, composed of a small number of decision trees with limited depths, are crucial for securing generalizability, interpretability, and performance of active transfer learning.

Development of copper-catalyzed deaminative esterification using high-throughput experimentation.

Repurposing of amine and carboxylic acid building blocks provides an enormous opportunity to expand the accessible chemical space, because amine and acid feedstocks are typically low cost and available in high diversity. Herein, we report a copper-catalyzed deaminative esterification based on C-N activation of aryl amines via diazonium salt formation. The reaction was specifically designed to complement the popular amide coupling reaction. A chemoinformatic analysis of commercial building blocks demonstrates that by utilizing aryl amines, our method nearly doubles the available esterification chemical space compared to classic Fischer esterification with phenols. High-throughput experimentation in microliter reaction droplets was used to develop the reaction, along with classic scope studies, both of which demonstrated robust performance against hundreds of substrate pairs. Furthermore, we have demonstrated that this new esterification is suitable for late-stage diversification and for building-block repurposing to expand chemical space.

Reinforcing the supply chain of umifenovir and other antiviral drugs with retrosynthetic software.

The global disruption caused by the 2020 coronavirus pandemic stressed the supply chain of many products, including pharmaceuticals. Multiple drug repurposing studies for COVID-19 are now underway. If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it, will be available in the quantities required. Here, we utilize retrosynthetic software to arrive at alternate chemical supply chains for the antiviral drug umifenovir, as well as eleven other antiviral and anti-inflammatory drugs. We have experimentally validated four routes to umifenovir and one route to bromhexine. In one route to umifenovir the software invokes conversion of six C-H bonds into C-C bonds or functional groups. The strategy we apply of excluding known starting materials from search results can be used to identify distinct starting materials, for instance to relieve stress on existing supply chains.

The Formal Cross-Coupling of Amines and Carboxylic Acids to Form sp3 -sp3 Carbon-Carbon Bonds.

We have developed a deaminative-decarboxylative protocol to form new carbon(sp3 )-carbon(sp3 ) bonds from activated amines and carboxylic acids. Amines and carboxylic acids are ubiquitous building blocks, available in broad chemical diversity and at lower cost than typical C-C coupling partners. To leverage amines and acids for C-C coupling, we developed a reductive nickel-catalyzed cross-coupling utilizing building block activation as pyridinium salts and redox-active esters, respectively. Miniaturized high-throughput experimentation studies were critical to our reaction optimization, with subtle experimental changes such as order of reagent addition, composition of a binary solvent system, and ligand identity having a significant impact on reaction performance. The developed protocol is used in the late-stage diversification of pharmaceuticals while more than one thousand systematically captured and machine-readable reaction datapoints are reposited.

Ultrahigh-Throughput Experimentation for Information-Rich Chemical Synthesis.

The incorporation of data science is revolutionizing organic chemistry. It is becoming increasingly possible to predict reaction outcomes with accuracy, computationally plan new retrosynthetic routes to complex molecules, and design molecules with sophisticated functions. Critical to these developments has been statistical analysis of reaction data, for instance with machine learning, yet there is very little reaction data available upon which to build models. Reaction data can be mined from the literature, but experimental data tends to be reported in a text format that is difficult for computers to read. Compounding the issue, literature data are heavily biased toward "productive" reactions, and few "negative" reaction data points are reported even though they are critical for training of statistical models. High-throughput experimentation (HTE) has evolved over the past few decades as a tool for experimental reaction development. The beauty of HTE is that reactions are run in a systematic format, so data points are internally consistent, the reaction data are reported whether the desired product is observed or not, and automation may reduce the occurrence of false positive or negative data points. Additionally, experimental workflows for HTE lead to datasets with reaction metadata that are captured in a machine-readable format. We believe that HTE will play an increasingly important role in the data revolution of chemical synthesis. This Account details the miniaturization of synthetic chemistry culminating in ultrahigh-throughput experimentation (ultraHTE), wherein reactions are run in ∼1 µL droplets inside of 1536-well microtiter plates to minimize the use of starting materials while maximizing the output of experimental information. The performance of ultraHTE in 1536-well microtiter plates has led to an explosion of available reaction data, which have been used to identify specific substrate-catalyst pairs for maximal efficiency in novel cross-coupling reactions. The first iteration of ultraHTE focused on the use of dimethyl sulfoxide (DMSO) as a high-boiling solvent that is compatible with the plastics most commonly used in consumable well plates, which generated homogeneous reaction mixtures that are perfect for use with nanoliter-dosing liquid handling robotics. In this way, DMSO enabled diverse reagents to be arrayed in ∼1 µL droplets. Reactions were run at room temperature with no agitation and could be scaled up from the ∼0.05 mg reaction scale to the 1 g scale. Engineering enhancements enabled the use of ultraHTE with diverse and semivolatile solvents, photoredox catalysis, heating, and acoustic agitation. A main driver in the development of ultraHTE was the recognition of the opportunity for a direct merger between miniaturized reactions and biochemical assays. Indeed, a strategy was developed to feed ultraHTE reaction mixtures directly to a mass-spectrometry-based affinity selection bioassay. Thus, micrograms of starting materials could be used in the synthesis and direct biochemical testing of drug-like molecules. Reactions were performed at a reactant concentration of ∼0.1 M in an inert atmosphere, enabling even challenging transition-metal-catalyzed reactions to be used. Software to enable the workflow was developed. We recently initiated the mapping of reaction space, dreaming of a future where transformations, reaction conditions, structure, properties and function are studied in a systems chemistry approach.

A map of the amine-carboxylic acid coupling system.

Chemical transformations determine the structure of a product, and therefore its properties, which in turn affect complex macroscopic functions such as the metabolic stability of pharmaceuticals or the volatility of perfumes. Therefore, reaction selection can influence the success or failure of a candidate molecule to meet a functional objective. The coupling of an amine with a carboxylic acid to form an amide bond is the most popular chemical reaction used for drug discovery1. However, there are many other ways to connect these two common functional groups together. Here we show computationally that amines and acids can couple via hundreds of hypothetical yet plausible transformations, and we demonstrate experimentally the application of a dozen such reactions. To investigate the contribution of chemical transformations to properties, we developed a string-based notation and used an enumerative combinatorics approach to produce a map of conceivable amine-acid coupling transformations, which can be charted using chemoinformatic techniques. We find that critical physicochemical parameters of the products, such as partition coefficient and polar surface area, vary considerably depending on the transformation chosen. Data mining the amine-acid coupling system produced here should enable reaction discovery, which we demonstrate by developing an esterification reaction found within the mapped space. Complex molecules with distinct property profiles can also be discovered within the amine-acid coupling system, as we show here via the late-stage diversification of drugs and natural products.

Development of indazole mineralocorticoid receptor antagonists and investigation into their selective late-stage functionalization.

The derivatization of pharmaceuticals is a core activity in the discovery and development of new medicines. Late-stage functionalization via modern CH functionalization chemistry has emerged as a powerful technique with which to diversify advanced pharmaceutical intermediates. We report herein a case study in late-stage functionalization towards the development of a new class of indazole-based mineralocorticoid receptor antagonists (MRA). An effort to modify the electronics of the core indazole heterocycle inspired the use of modern CH borylation chemistry. New reactivity patterns were revealed and studied computationally. Ultimately, a de novo synthesis delivered a key 6-fluoroindazole compound 26, a potent MRA with excellent metabolic stability.

Pharmaceutical diversification via palladium oxidative addition complexes.

Palladium-catalyzed cross-coupling reactions have transformed the exploration of chemical space in the search for materials, medicines, chemical probes, and other functional molecules. However, cross-coupling of densely functionalized substrates remains a major challenge. We devised an alternative approach using stoichiometric quantities of palladium oxidative addition complexes (OACs) derived from drugs or drug-like aryl halides as substrates. In most cases, cross-coupling reactions using OACs proceed under milder conditions and with higher success than the analogous catalytic reactions. OACs exhibit remarkable stability, maintaining their reactivity after months of benchtop storage under ambient conditions. We demonstrated the utility of OACs in a variety of experiments including automated nanomole-scale couplings between an OAC derived from rivaroxaban and hundreds of diverse nucleophiles, as well as the late-stage derivatization of the natural product k252a.

Mapping the dark space of chemical reactions with extended nanomole synthesis and MALDI-TOF MS.

Understanding the practical limitations of chemical reactions is critically important for efficiently planning the synthesis of compounds in pharmaceutical, agrochemical, and specialty chemical research and development. However, literature reports of the scope of new reactions are often cursory and biased toward successful results, severely limiting the ability to predict reaction outcomes for untested substrates. We herein illustrate strategies for carrying out large-scale surveys of chemical reactivity by using a material-sparing nanomole-scale automated synthesis platform with greatly expanded synthetic scope combined with ultrahigh-throughput matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS).

Nanoscale synthesis and affinity ranking.

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 1060 drug-like possibilities 1 , and a single reaction used to synthesize each molecule has more than 107 plausible permutations of catalysts, ligands, additives and other parameters 2 . 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 synthesis3-7 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 condition8-13. High-density chemical synthesis approaches that have been coupled to bioassays, including on-bead 14 , on-surface 15 , on-DNA 16 and mass-encoding technologies 17 , 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.

Microscale High-Throughput Experimentation as an Enabling Technology in Drug Discovery: Application in the Discovery of (Piperidinyl)pyridinyl-1H-benzimidazole Diacylglycerol Acyltransferase 1 Inhibitors.

Miniaturization and parallel processing play an important role in the evolution of many technologies. We demonstrate the application of miniaturized high-throughput experimentation methods to resolve synthetic chemistry challenges on the frontlines of a lead optimization effort to develop diacylglycerol acyltransferase (DGAT1) inhibitors. Reactions were performed on ∼1 mg scale using glass microvials providing a miniaturized high-throughput experimentation capability that was used to study a challenging SNAr reaction. The availability of robust synthetic chemistry conditions discovered in these miniaturized investigations enabled the development of structure-activity relationships that ultimately led to the discovery of soluble, selective, and potent inhibitors of DGAT1.