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Reaction generality is crucial in determining the overall impact and usefulness of synthetic methods. Typical generalization protocols require a priori mechanistic understanding and suffer when applied to complex, less understood systems. We developed an additive mapping approach that rapidly expands the utility of synthetic methods while generating concurrent mechanistic insight. Validation of this approach on the metallaphotoredox decarboxylative arylation resulted in the discovery of a phthalimide ligand additive that overcomes many lingering limitations of this reaction and has important mechanistic implications for nickel-catalyzed cross-couplings.
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Chemical reaction data in journal articles, patents, and even electronic laboratory notebooks are currently stored in various formats, often unstructured, which presents a significant barrier to downstream applications, including the training of machine-learning models. We present the Open Reaction Database (ORD), an open-access schema and infrastructure for structuring and sharing organic reaction data, including a centralized data repository. The ORD schema supports conventional and emerging technologies, from benchtop reactions to automated high-throughput experiments and flow chemistry. The data, schema, supporting code, and web-based user interfaces are all publicly available on GitHub. Our vision is that a consistent data representation and infrastructure to support data sharing will enable downstream applications that will greatly improve the state of the art with respect to computer-aided synthesis planning, reaction prediction, and other predictive chemistry tasks.
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The synthetic chemistry literature traditionally reports the scope of new methods using simple, nonstandardized test molecules that have uncertain relevance in applied synthesis. In addition, published examples heavily favor positive reaction outcomes, and failure is rarely documented. In this environment, synthetic practitioners have inadequate information to know whether any given method is suitable for the task at hand. Moreover, the incomplete nature of published data makes it poorly suited for the creation of predictive reactivity models via machine learning approaches. In 2016, we reported the concept of chemistry informer libraries as standardized sets of medium- to high-complexity substrates with relevance to pharmaceutical synthesis as demonstrated using a multidimensional principle component analysis (PCA) comparison to the physicochemical properties of marketed drugs. We showed how informer libraries could be used to evaluate leading synthetic methods with the complete capture of success and failure and how this knowledge could lead to improved reaction conditions with a broader scope with respect to relevant applications. In this Account, we describe the progress made and lessons learned in subsequent studies using informer libraries to profile eight additional reaction classes. Examining broad trends across multiple types of bond disconnections against a standardized chemistry "measuring stick" has enabled comparisons of the relative potential of different methods for applications in complex synthesis and has identified opportunities for further development. Furthermore, the powerful combination of informer libraries and 1536-well-plate nanoscale reaction screening has allowed the parallel evaluation of scores of synthetic methods in the same experiment and as such illuminated an important role for informers as part of a larger data generation workflow for predictive reactivity modeling. Using informer libraries as problem-dense, strong filters has allowed broad sets of reaction conditions to be narrowed down to those that display the highest tolerance to complex substrates. These best conditions can then be used to survey broad swaths of substrate space using nanoscale chemistry approaches. Our experiences and those of our collaborators from several academic laboratories applying informer libraries in these contexts have helped us identify several areas for potential improvements to the approach that would increase their ease of use, utility in generating interpretable results, and resulting uptake by the broader community. As we continue to evolve the informer library concept, we believe it will play an ever-increasing role in the future of the democratization of high-throughput experimentation and data science-driven synthetic method development.
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Innovations in synthetic chemistry have enabled the discovery of many breakthrough therapies that have improved human health over the past century. In the face of increasing challenges in the pharmaceutical sector, continued innovation in chemistry is required to drive the discovery of the next wave of medicines. Novel synthetic methods not only unlock access to previously unattainable chemical matter, but also inspire new concepts as to how we design and build chemical matter. We identify some of the most important recent advances in synthetic chemistry as well as opportunities at the interface with partner disciplines that are poised to transform the practice of drug discovery and development.
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Química Farmacéutica/tendencias , Descubrimiento de Drogas , Preparaciones Farmacéuticas/síntesis química , Biocatálisis , Industria Farmacéutica , Enzimas/química , Ensayos Analíticos de Alto Rendimiento , Invenciones , Aprendizaje Automático , FotoquímicaRESUMEN
We demonstrate that the chemical-feature model described in our original paper is distinguishable from the nongeneralizable models introduced by Chuang and Keiser. Furthermore, the chemical-feature model significantly outperforms these models in out-of-sample predictions, justifying the use of chemical featurization from which machine learning models can extract meaningful patterns in the dataset, as originally described.
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Aprendizaje Automático , Modelos QuímicosRESUMEN
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).
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Machine learning methods are becoming integral to scientific inquiry in numerous disciplines. We demonstrated that machine learning can be used to predict the performance of a synthetic reaction in multidimensional chemical space using data obtained via high-throughput experimentation. We created scripts to compute and extract atomic, molecular, and vibrational descriptors for the components of a palladium-catalyzed Buchwald-Hartwig cross-coupling of aryl halides with 4-methylaniline in the presence of various potentially inhibitory additives. Using these descriptors as inputs and reaction yield as output, we showed that a random forest algorithm provides significantly improved predictive performance over linear regression analysis. The random forest model was also successfully applied to sparse training sets and out-of-sample prediction, suggesting its value in facilitating adoption of synthetic methodology.
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The structural complexity of pharmaceuticals presents a significant challenge to modern catalysis. Many published methods that work well on simple substrates often fail when attempts are made to apply them to complex drug intermediates. The use of high-throughput experimentation (HTE) techniques offers a means to overcome this fundamental challenge by facilitating the rational exploration of large arrays of catalysts and reaction conditions in a time- and material-efficient manner. Initial forays into the use of HTE in our laboratories for solving chemistry problems centered around screening of chiral precious-metal catalysts for homogeneous asymmetric hydrogenation. The success of these early efforts in developing efficient catalytic steps for late-stage development programs motivated the desire to increase the scope of this approach to encompass other high-value catalytic chemistries. Doing so, however, required significant advances in reactor and workflow design and automation to enable the effective assembly and agitation of arrays of heterogeneous reaction mixtures and retention of volatile solvents under a wide range of temperatures. Associated innovations in high-throughput analytical chemistry techniques greatly increased the efficiency and reliability of these methods. These evolved HTE techniques have been utilized extensively to develop highly innovative catalysis solutions to the most challenging problems in large-scale pharmaceutical synthesis. Starting with Pd- and Cu-catalyzed cross-coupling chemistry, subsequent efforts expanded to other valuable modern synthetic transformations such as chiral phase-transfer catalysis, photoredox catalysis, and C-H functionalization. As our experience and confidence in HTE techniques matured, we envisioned their application beyond problems in process chemistry to address the needs of medicinal chemists. Here the problem of reaction generality is felt most acutely, and HTE approaches should prove broadly enabling. However, the quantities of both time and starting materials available for chemistry troubleshooting in this space generally are severely limited. Adapting to these needs led us to invest in smaller predefined arrays of transformation-specific screening "kits" and push the boundaries of miniaturization in chemistry screening, culminating in the development of "nanoscale" reaction screening carried out in 1536-well plates. Grappling with the problem of generality also inspired the exploration of cheminformatics-driven HTE approaches such as the Chemistry Informer Libraries. These next-generation HTE methods promise to empower chemists to run orders of magnitude more experiments and enable "big data" informatics approaches to reaction design and troubleshooting. With these advances, HTE is poised to revolutionize how chemists across both industry and academia discover new synthetic methods, develop them into tools of broad utility, and apply them to problems of practical significance.
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Técnicas de Química Sintética/métodos , Tecnología Farmacéutica/métodos , Catálisis/efectos de la radiación , Complejos de Coordinación/química , Descubrimiento de Drogas , Hidrogenación , MiniaturizaciónRESUMEN
A novel approach to produce chiral diaryl sulfoxides from aryl benzyl sulfoxides and aryl bromides via an enantioselective arylation of aryl sulfenate anions is reported. A (JosiPhos)Pd-based catalyst successfully promotes the asymmetric arylation reaction with good functional group compatibility. A wide range of enantioenriched diaryl, aryl heteroaryl, and even diheteroaryl sulfoxides were generated. Many of the sulfoxides prepared herein would be difficult to prepare via classic enantioselective oxidation of sulfides, including Ph(Ph-d5)SO (90% ee, 95% yield). A DFT-based computational study suggested that chiral induction originates from two primary factors: (i) both a kinetic and a thermodynamic preference for oxidative addition that places the bromide trans to the JosiPhos-diarylphosphine moiety and (ii) Curtin-Hammett-type control over the interconversion between O- and S-bound isomers of palladium sulfenate species following rapid interconversion between re- and si-bound transmetalation products, re/si-Pd-OSPh (re/si-PdO-trans).
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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 â¼1 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.
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Diacilglicerol O-Acetiltransferasa/antagonistas & inhibidores , Inhibidores Enzimáticos/química , Inhibidores Enzimáticos/farmacología , Cromatografía Liquida , Espectrometría de Masas , Espectroscopía de Protones por Resonancia MagnéticaRESUMEN
The reactivity of a representative set of 17 organozinc pivalates with 18 polyfunctional druglike electrophiles (informers) in Negishi cross-coupling reactions was evaluated by high-throughput experimentation protocols. The high-fidelity scaleup of successful reactions in parallel enabled the isolation of sufficient material for biological testing, thus demonstrating the high value of these new solid zinc reagents in a drug-discovery setting and potentially for many other applications in chemistry. Principal component analysis (PCA) clearly defined the independent roles of the zincates and the informers toward druggable-space coverage.
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Compuestos Organometálicos/química , Piridinas/síntesis química , Zinc/química , Ensayos Analíticos de Alto Rendimiento , Estructura Molecular , Análisis de Componente Principal , Piridinas/químicaRESUMEN
Over the past two decades, there have been major developments in transition metal-catalyzed aminations of aryl halides to form anilines, a common structure found in drug agents, natural product isolates, and fine chemicals. Many of these approaches have enabled highly efficient and selective coupling through the design of specialized ligands, which facilitate reductive elimination from a destabilized metal center. We postulated that a general and complementary method for carbon-nitrogen bond formation could be developed through the destabilization of a metal amido complex via photoredox catalysis, thus providing an alternative approach to the use of structurally complex ligand systems. Here, we report the development of a distinct mechanistic paradigm for aryl amination using ligand-free nickel(II) salts, in which facile reductive elimination from the nickel metal center is induced via a photoredox-catalyzed electron-transfer event.
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The first two highly enantioselective palladium-catalyzed allylic alkylations with benzylic nucleophiles, activated with Cr(CO)3 , have been developed. These methods enable the enantioselective synthesis of α-2-propenyl benzyl motifs, which are important scaffolds in natural products and pharmaceuticals. A variety of cyclic and acyclic allylic carbonates are competent electrophilic partners furnishing the products in excellent enantioselectivity (up to 99 % ee and 92 % yield). This approach was employed to prepare a nonsteroidal anti-inflammatory drug analogue.
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Paladio/química , Tolueno/química , Alquilación , CatálisisRESUMEN
Major new advances in synthetic chemistry methods are typically reported using simple, non-standardized reaction substrates, and reaction failures are rarely documented. This makes the evaluation and choice of a synthetic method difficult. We report a standardized complex molecule diagnostic approach using collections of relevant drug-like molecules which we call chemistry informer libraries. With this approach, all chemistry results, successes and failures, can be documented to compare and evolve synthetic methods. To aid in the visualization of chemistry results in drug-like physicochemical space we have used an informatics methodology termed principal component analysis. We have validated this method using palladium- and copper-catalyzed reactions, including Suzuki-Miyaura, cyanation and Buchwald-Hartwig amination.
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The non-nucleophilic organic superbase P2Et phosphazene can enable a broad range of palladium-catalyzed cross-coupling reactions, including C-C, C-N, and C-O couplings of aryl chlorides, bromides, and iodides at room temperature. The mildness and substrate compatibility of this chemistry can deliver immediate synthetic utility for the preparation of complex molecules.
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At the forefront of new synthetic endeavors, such as drug discovery or natural product synthesis, large quantities of material are rarely available and timelines are tight. A miniaturized automation platform enabling high-throughput experimentation for synthetic route scouting to identify conditions for preparative reaction scale-up would be a transformative advance. Because automated, miniaturized chemistry is difficult to carry out in the presence of solids or volatile organic solvents, most of the synthetic "toolkit" cannot be readily miniaturized. Using palladium-catalyzed cross-coupling reactions as a test case, we developed automation-friendly reactions to run in dimethyl sulfoxide at room temperature. This advance enabled us to couple the robotics used in biotechnology with emerging mass spectrometry-based high-throughput analysis techniques. More than 1500 chemistry experiments were carried out in less than a day, using as little as 0.02 milligrams of material per reaction.
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Ensayos Analíticos de Alto Rendimiento/métodos , Nanopartículas , Nanotecnología/métodos , Preparaciones Farmacéuticas/síntesis química , Biotecnología , Catálisis , Espectrometría de Masas , Paladio/química , Robótica/métodosRESUMEN
Although the past 15 years have witnessed the development of sterically bulky and electron-rich alkylphosphine ligands for palladium-catalyzed cross-couplings with aryl chlorides, examples of palladium catalysts based on either triarylphosphine or bidentate phosphine ligands for efficient room temperature cross-coupling reactions with unactivated aryl chlorides are rare. Herein we report a palladium catalyst based on NiXantphos, a deprotonatable chelating aryldiphosphine ligand, to oxidatively add unactivated aryl chlorides at room temperature. Surprisingly, comparison of an extensive array of ligands revealed that under the basic reaction conditions the resultant heterobimetallic Pd-NiXantphos catalyst system outperformed all the other mono- and bidentate ligands in a deprotonative cross-coupling process (DCCP) with aryl chlorides. The DCCP with aryl chlorides affords a variety of triarylmethane products, a class of compounds with various applications and interesting biological activity. Additionally, the DCCP exhibits remarkable chemoselectivity in the presence of aryl chloride substrates bearing heteroaryl groups and sensitive functional groups that are known to undergo 1,2-addition, aldol reaction, and O-, N-, enolate-α-, and C(sp(2))-H arylations. The advantages and importance of the Pd-NiXantphos catalyst system outlined herein make it a valuable contribution for applications in Pd-catalyzed arylation reactions with aryl chlorides.
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Cloruros/química , Hidrocarburos Aromáticos/química , Paladio/química , Fosfinas/química , Catálisis , Ligandos , Modelos Moleculares , Oxidación-Reducción , Protones , TemperaturaRESUMEN
The palladium-catalyzed α-arylation of unactivated sulfoxides has been developed. The weakly acidic α-protons of sulfoxides are reversibly deprotonated by LiOtBu, and a palladium phosphine complex facilitates the arylation. A variety of aryl methyl sulfoxides were coupled with aryl bromides. More challenging coupling partners, such as alkyl methyl sulfoxides (including dimethyl sulfoxide) and aryl chlorides proved to be suitable under the optimized conditions. This method was utilized to synthesize bioactive benzyl sulfoxide intermediates.