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Understanding the functional effects of sequence variation is crucial in genomics. Individual human genomes contain millions of variants that contribute to phenotypic variability and disease risks at the population level. Because variants rarely act in isolation, we must consider potential interactions of neighboring variants to accurately predict functional effects. We can accomplish this using haplotagging, which matches sequencing reads to their parental haplotypes using alleles observed at known heterozygous variants. However, few published tools for haplotagging exist and these share several technical and usability-related shortcomings that limit applicability, in particular a lack of insight or control over error rates, and lack of key metrics on the underlying sources of haplotagging error. Here we present HaplotagLR: a user-friendly tool that haplotags long sequencing reads based on a multinomial model and existing phased variant lists. HaplotagLR is user-configurable and includes a basic error model to control the empirical FDR in its output. We show that HaplotagLR outperforms the leading haplotagging method in simulated datasets, especially at high levels of specificity, and displays 7% greater sensitivity in haplotagging real data. HaplotagLR advances both the immediate utility of haplotagging and paves the way for further improvements to this important method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. All possible chemical transformations between amine and carboxylic acid groups are mapped using an automated string-based combinatorics method, showing that the properties and functions of the products vary considerably over all plausible reactions. [ABSTRACT FROM AUTHOR]

In the acknowledgements section "Shane Krska and Melodie Christensen of Merck & Co., Inc". should have read "Shane Krska and Melodie Christensen of MSD". Finally, the competing interests statement stated 'The Cernak Lab has received research funding or in-kind donations from MilliporeSigma, Relay Therapeutics, Janssen Therapeutics, SPT Labtech and Merck & Co., Inc'. but should read as 'The Cernak Lab has received research funding or in-kind donations from Merck, Relay Therapeutics, Janssen Therapeutics, SPT Labtech, and MSD'. [Extracted from the article]