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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. High-throughput experimentation is an increasingly important tool in reaction discovery, while there remains a need for software solutions to navigate data-rich experiments. Here the authors report phactor™, a software that facilitates the performance and analysis of high-throughput experimentation in a chemical laboratory.

When chemists synthesize compounds, the threshold for success is at least a milligram of product. This has been true for decades—even though biochemical assays have long since descended into microgram territory—and results in part from the constraints of characterization methods. Buitrago Santanilla et al. present an automated dosing and characterization protocol for optimizing chemical reaction conditions on the microgram scale. This allowed them to screen numerous base and ligand combinations for catalytic C-N bond-forming reactions between complex pairs of compounds, in short supply, that resisted standard coupling conditions. Science , this issue p. 49 Automated technology enables chemical reaction optimization using micrograms of material. 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.

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. COVID-19 has exposed the fragility of supply chains, particularly for goods that are essential or may suddenly become essential, such as repurposed pharmaceuticals. Here the authors develop a methodology to provide routes to pharmaceutical targets that allow low-supply starting materials or intermediates to be avoided, with representative pathways validated experimentally.

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. Given their low cost and diverse nature, coupling of amine and carboxylic acid building blocks provides an opportunity to expand the accessible chemical space. Here, a copper-catalyzed deaminative esterification of aryl amines with carboxylic acids is developed and its use in library synthesis with high-throughput experimentation is demonstrated.

Letter to the Editor

Two invasive adelgids are associated with widespread damage to several North American conifer species. Adelges tsugae, hemlock woolly adelgid, was introduced from Japan and reproduces parthenogenetically in North America, where it has rapidly decimated Tsuga canadensis and Tsuga caroliniana (eastern and Carolina hemlocks, respectively). Adelges abietis, eastern spruce gall adelgid, introduced from Europe, forms distinctive pineapple-shaped galls on several native spruce species. While not considered a major forest pest, it weakens trees and increases susceptibility to additional stressors. Broad-spectrum insecticides that are often used to control adelgid populations can have off-target impacts on beneficial insects. Whole-genome sequencing was performed on both species to aid in the development of targeted solutions that may minimize ecological impact. A. abietis was sequenced using barcoded linked-reads from 30 pooled individuals, with Hi-C scaffolding performed using data from a single individual collected from the same host plant. A. tsugae used long-read sequencing from pooled nymphs. The assembled A. tsugae and A. abietis genomes, pooled from several parthenogenetic females, are 220.75 and 253.16 Mb, respectively. Each consists of 8 autosomal chromosomes, as well as 2 sex chromosomes (X1/X2), supporting the XX-XO sex determination system. The genomes are over 96% complete based on BUSCO assessment. Genome annotation identified 11,424 and 12,060 protein-coding genes in A. tsugae and A. abietis, respectively. Comparative analysis of proteins across 31 hemipteran species and 14 arthropod outgroups identified 32,340 putative gene families. Gene family evolution analysis with CAFE revealed lineage-specific expansions in immune-related aminopeptidases (ERAP1) and juvenile hormone binding proteins (JHBP), contractions in juvenile hormone acid methyltransferases (JHAMT), and conservation of nicotinic acetylcholine receptors (nAChRs). These genes were explored as candidate families toward a long-term objective of developing adelgid-selective insecticides. Structural comparisons of proteins across 7 focal species (A. tsugae, A. abietis, Adelges cooleyi, Rhopalosiphum maidis, Apis mellifera, Danaus plexippus, and Drosophila melanogaster) revealed high conservation of nAChR and ERAP1, while JHAMT exhibited species-specific structural divergence. The potential of JHAMT as a lineage-specific target for pest control was explored through virtual screening of drugs and pesticides.

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. Amines and carboxylic acids are abundant chemical feedstocks, however, the current reaction space of those two building blocks is focused on amide coupling. Here, the authors extensively explore the amine–acid reaction space via systematic reaction enumeration using graph editing and demonstrate its utility in retrosynthetic analysis as well as late-stage diversification.

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.

The molecules of today — the medicines that cure diseases, the agrochemicals that protect our crops, the materials that make life convenient — are becoming increasingly sophisticated thanks to advancements in chemical synthesis. As tools for synthesis improve, molecular architects can be bold and creative in the way they design and produce molecules. Several emerging tools at the interface of chemical synthesis and data science have come to the forefront in recent years, including algorithms for retrosynthesis and reaction prediction, and robotics for autonomous or high-throughput synthesis. This Primer covers recent additions to the toolbox of the data-savvy organic chemist. There is a new movement in retrosynthetic logic, predictive models of reactivity and chemistry automata, with considerable recent engagement from contributors in diverse fields. The promise of chemical synthesis in the information age is to improve the quality of the molecules of tomorrow through data-harnessing and automation. This Primer is written for organic chemists and data scientists looking to understand the software, hardware, data sets and tactics that are commonly used as well as the capabilities and limitations of the field. The Primer is split into three main components covering retrosynthetic logic, reaction prediction and automated synthesis. The former of these topics is about distilling the strategy of multistep synthesis to a logic that can be taught to a computer. The section on reaction prediction details modern tools and models for developing reaction conditions, catalysts and even new transformations based on information-rich data sets and statistical tools such as machine learning. Finally, we cover recent advances in the use of liquid handling robotics and autonomous systems that can physically perform experiments in the chemistry laboratory.This Primer summarizes the most relevant aspects of chemical synthesis in this information age for those looking to understand the software, hardware and data and how these are used to enable retrosynthetic logic, reaction prediction and automation.