Paddy: an evolutionary optimization algorithm for chemical systems and spaces

Optimization of chemical systems and processes have been enhanced and enabled by the development of new algorithms and analytical approaches. While several methods systematically investigate how underlying variables correlate with a given outcome, there is often a substantial number of experiments needed to accurately model such relationships. As chemical systems increase in complexity, algorithms are needed to propose experiments that efficiently optimize the underlying objective, while effectively sampling parameter space to avoid convergence on local minima. We have developed the Paddy software package based on the Paddy field algorithm, a biologically inspired evolutionary optimization algorithm that propagates parameters without direct inference of the underlying objective function. We benchmarked Paddy against several optimization approaches: the Tree of Parzen Estimator through the Hyperopt software library, Bayesian optimization with a Gaussian process via Meta's Ax framework, and two population-based methods from EvoTorch-an evolutionary algorithm with Gaussian mutation, and a genetic algorithm using both a Gaussian mutation and single-point crossover-all representing diverse approaches to optimization. Paddy's performance is benchmarked for mathematical and chemical optimization tasks including global optimization of a two-dimensional bimodal distribution, interpolation of an irregular sinusoidal function, hyperparameter optimization of an artificial neural network tasked with classification of solvent for reaction components, targeted molecule generation by optimizing input vectors for a decoder network, and sampling discrete experimental space for optimal experimental planning. Paddy demonstrates robust versatility by maintaining strong performance across all optimization benchmarks, compared to other algorithms with varying performance. Additionally, Paddy avoids early convergence with its ability to bypass local optima in search of global solutions. We anticipate that the facile, versatile, robust and open-source nature of Paddy will serve as a toolkit in chemical problem-solving tasks towards automated experimentation with high priority for exploratory sampling and innate resistance to early convergence to identify optimal solutions.

Spaces of mathematical chemistry

In an effort to expand the domain of mathematical chemistry and inspire research beyond the realms of graph theory and quantum chemistry, we explore five mathematical chemistry spaces and their interconnectedness. These spaces comprise the chemical space, which encompasses substances and reactions; the space of reaction conditions, spanning the physical and chemical aspects involved in chemical reactions; the space of reaction grammars, which encapsulates the rules for creating and breaking chemical bonds; the space of substance properties, covering all documented measurements regarding substances; and the space of substance representations, composed of the various ontologies for characterising substances.

"Sea Water" Supplemented with Calcium Phosphate and Magnesium Sulfate in a Long-Term Miller-Type Experiment Yields Sugars, Nucleic Acids Bases, Nucleosides, Lipids, Amino Acids, and Oligopeptides

The standard approach to exploring prebiotic chemistry is to use a small number of highly purified reactants and to attempt to optimize the conditions required to produce a particular end product. However, purified reactants do not exist in nature. We have previously proposed that what drives prebiotic evolution are complex chemical ecologies. Therefore, we have begun to explore what happens if one substitutes "sea water", with its complex mix of minerals and salts, for distilled water in the classic Miller experiment. We have also adapted the apparatus to permit it to be regassed at regular intervals so as to maintain a relatively constant supply of methane, hydrogen, and ammonia. The "sea water" used in the experiments was created from Mediterranean Sea salt with the addition of calcium phosphate and magnesium sulfate. Tests included several types of mass spectrometry, an ATP-monitoring device capable of measuring femtomoles of ATP, and a high-sensitivity cAMP enzyme-linked immunoadsorption assay. As expected, amino acids appeared within a few days of the start of the experiment and accumulated thereafter. Sugars, including glucose and ribose, followed as did long-chain fatty acids (up to C20). At three-to-five weeks after starting the experiment, ATP was repeatedly detected. Thus, we have shown that it is possible to produce a "one-pot synthesis" of most of the key chemical prerequisites for living systems within weeks by mimicking more closely the complexity of real-world chemical ecologies.

Novel Apparatuses for Incorporating Natural Selection Processes into Origins-of-Life Experiments to Produce Adaptively Evolving Chemical Ecosystems

Origins-of-life chemical experiments usually aim to produce specific chemical end-products such as amino acids, nucleic acids or sugars. The resulting chemical systems do not evolve or adapt because they lack natural selection processes. We have modified Miller origins-of-life apparatuses to incorporate several natural, prebiotic physicochemical selection factors that can be tested individually or in tandem: freezing-thawing cycles; drying-wetting cycles; ultraviolet light-dark cycles; and catalytic surfaces such as clays or minerals. Each process is already known to drive important origins-of-life chemical reactions such as the production of peptides and synthesis of nucleic acid bases and each can also destroy various reactants and products, resulting selection within the chemical system. No previous apparatus has permitted all of these selection processes to work together. Continuous synthesis and selection of products can be carried out over many months because the apparatuses can be re-gassed. Thus, long-term chemical evolution of chemical ecosystems under various combinations of natural selection may be explored for the first time. We argue that it is time to begin experimenting with the long-term effects of such prebiotic natural selection processes because they may have aided biotic life to emerge by taming the combinatorial chemical explosion that results from unbounded chemical syntheses.

Exploring and mapping chemical space with molecular assembly trees

The rule-based search of chemical space can generate an almost infinite number of molecules, but exploration of known molecules as a function of the minimum number of steps needed to build up the target graphs promises to uncover new motifs and transformations. Assembly theory is an approach to compare the intrinsic complexity and properties of molecules by the minimum number of steps needed to build up the target graphs. Here, we apply this approach to prebiotic chemistry, gene sequences, plasticizers, and opiates. This allows us to explore molecules connected to the assembly tree, rather than the entire space of molecules possible. Last, by developing a reassembly method, based on assembly trees, we found that in the case of the opiates, a new set of drug candidates could be generated that would not be accessible via conventional fragment-based drug design, thereby demonstrating how this approach might find application in drug discovery.

A robotic prebiotic chemist probes long term reactions of complexifying mixtures

To experimentally test hypotheses about the emergence of living systems from abiotic chemistry, researchers need to be able to run intelligent, automated, and long-term experiments to explore chemical space. Here we report a robotic prebiotic chemist equipped with an automatic sensor system designed for long-term chemical experiments exploring unconstrained multicomponent reactions, which can run autonomously over long periods. The system collects mass spectrometry data from over 10 experiments, with 60 to 150 algorithmically controlled cycles per experiment, running continuously for over 4 weeks. We show that the robot can discover the production of high complexity molecules from simple precursors, as well as deal with the vast amount of data produced by a recursive and unconstrained experiment. This approach represents what we believe to be a necessary step towards the design of new types of Origin of Life experiments that allow testable hypotheses for the emergence of life from prebiotic chemistry.

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.

Understanding Periodic and Non-periodic Chemistry in Periodic Tables

The chemical elements are the "conserved principles" or "kernels" of chemistry that are retained when substances are altered. Comprehensive overviews of the chemistry of the elements and their compounds are needed in chemical science. To this end, a graphical display of the chemical properties of the elements, in the form of a Periodic Table, is the helpful tool. Such tables have been designed with the aim of either classifying real chemical substances or emphasizing formal and aesthetic concepts. Simplified, artistic, or economic tables are relevant to educational and cultural fields, while practicing chemists profit more from "chemical tables of chemical elements." Such tables should incorporate four aspects: (i) typical valence electron configurations of bonded atoms in chemical compounds (instead of the common but chemically atypical ground states of free atoms in physical vacuum); (ii) at least three basic chemical properties (valence number, size, and energy of the valence shells), their joint variation across the elements showing principal and secondary periodicity; (iii) elements in which the (sp)8, (d)10, and (f)14 valence shells become closed and inert under ambient chemical conditions, thereby determining the "fix-points" of chemical periodicity; (iv) peculiar elements at the top and at the bottom of the Periodic Table. While it is essential that Periodic Tables display important trends in element chemistry we need to keep our eyes open for unexpected chemical behavior in ambient, near ambient, or unusual conditions. The combination of experimental data and theoretical insight supports a more nuanced understanding of complex periodic trends and non-periodic phenomena.

Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis

Most chemical experiments are planned by human scientists and therefore are subject to a variety of human cognitive biases¹, heuristics² and social influences³. These anthropogenic chemical reaction data are widely used to train machine-learning models⁴ that are used to predict organic⁵ and inorganic^6,7 syntheses. However, it is known that societal biases are encoded in datasets and are perpetuated in machine-learning models⁸. Here we identify as-yet-unacknowledged anthropogenic biases in both the reagent choices and reaction conditions of chemical reaction datasets using a combination of data mining and experiments. We find that the amine choices in the reported crystal structures of hydrothermal synthesis of amine-templated metal oxides⁹ follow a power-law distribution in which 17% of amine reactants occur in 79% of reported compounds, consistent with distributions in social influence models^10-12. An analysis of unpublished historical laboratory notebook records shows similarly biased distributions of reaction condition choices. By performing 548 randomly generated experiments, we demonstrate that the popularity of reactants or the choices of reaction conditions are uncorrelated to the success of the reaction. We show that randomly generated experiments better illustrate the range of parameter choices that are compatible with crystal formation. Machine-learning models that we train on a smaller randomized reaction dataset outperform models trained on larger human-selected reaction datasets, demonstrating the importance of identifying and addressing anthropogenic biases in scientific data.

Exploration of the chemical space and its three historical regimes

Chemical research unveils the structure of chemical space, spanned by all chemical species, as documented in more than 200 y of scientific literature, now available in electronic databases. Very little is known, however, about the large-scale patterns of this exploration. Here we show, by analyzing millions of reactions stored in the Reaxys database, that chemists have reported new compounds in an exponential fashion from 1800 to 2015 with a stable 4.4% annual growth rate, in the long run neither affected by World Wars nor affected by the introduction of new theories. Contrary to general belief, synthesis has been the means to provide new compounds since the early 19th century, well before Wöhler's synthesis of urea. The exploration of chemical space has followed three statistically distinguishable regimes. The first one included uncertain year-to-year output of organic and inorganic compounds and ended about 1860, when structural theory gave way to a century of more regular and guided production, the organic regime. The current organometallic regime is the most regular one. Analyzing the details of the synthesis process, we found that chemists have had preferences in the selection of substrates and we identified the workings of such a selection. Regarding reaction products, the discovery of new compounds has been dominated by very few elemental compositions. We anticipate that the present work serves as a starting point for more sophisticated and detailed studies of the history of chemistry.

Rapid Assessment of the Reaction-Condition-Based Sensitivity of Chemical Transformations

A systematic, user-friendly assessment tool that delivers a clear overview of the sensitivity of reactions to key parameters is highly desirable. Herein, the development of such a method is described. The intuitive, standardized presentation of the results in a radar diagram enables the sensitivity of a protocol to be rapidly assessed. This method was applied to five different visible-light-mediated photochemical reactions, and the results were correlated to the underlying mechanism. Ultimately, we believe that this assessment will help to increase the uptake of new synthetic methods and their reproducibility.

An overview of peptide and peptoid foldamers in medicinal chemistry

INTRODUCTION

Foldamers are artificial self-organizing systems with various critical properties: i) a stable and designable secondary structure; ii) a larger molecular surface as compared with ordinary organic drug molecules; iii) appropriate control of the orientation of the side-chain functional groups; iv) resistance against proteolytic degradation, which leads to potentially increased oral bioavailability and a longer serum half-life relative to ordinary α-peptides; and v) the lower conformational freedom may result in increased receptor binding in comparison with the natural analogs.

AREAS COVERED

This article covers the general properties and types of foldamers. This includes highlighted examples of medicinal chemical applications, including antibacterial and cargo molecules, anti-Alzheimer compounds and protein-protein interaction modifiers.

EXPERT OPINION

Various new foldamers have been created with a range of structures and biological applications. Membrane-acting antibacterial foldamers have been introduced. A general property of these structures is their amphiphilic nature. The amphiphilicity can be stationary or induced by the membrane binding. Cell-penetrating foldamers have been described which serve as cargo molecules, and foldamers have been used as autophagy inducers. Anti-Alzheimer compounds too have been created and the greatest breakthrough was attained via the modification of protein-protein interactions. This can serve as the chemical and pharmaceutical basis for the relevance of foldamers in the future.

Continuous-flow technology—a tool for the safe manufacturing of active pharmaceutical ingredients

In the past few years, continuous-flow reactors with channel dimensions in the micro- or millimeter region have found widespread application in organic synthesis. The characteristic properties of these reactors are their exceptionally fast heat and mass transfer. In microstructured devices of this type, virtually instantaneous mixing can be achieved for all but the fastest reactions. Similarly, the accumulation of heat, formation of hot spots, and dangers of thermal runaways can be prevented. As a result of the small reactor volumes, the overall safety of the process is significantly improved, even when harsh reaction conditions are used. Thus, microreactor technology offers a unique way to perform ultrafast, exothermic reactions, and allows the execution of reactions which proceed via highly unstable or even explosive intermediates. This Review discusses recent literature examples of continuous-flow organic synthesis where hazardous reactions or extreme process windows have been employed, with a focus on applications of relevance to the preparation of pharmaceuticals.

Organic synthesis: march of the machines

Organic synthesis is changing; in a world where budgets are constrained and the environmental impacts of practice are scrutinized, it is increasingly recognized that the efficient use of human resource is just as important as material use. New technologies and machines have found use as methods for transforming the way we work, addressing these issues encountered in research laboratories by enabling chemists to adopt a more holistic systems approach in their work. Modern developments in this area promote a multi-disciplinary approach and work is more efficient as a result. This Review focuses on the concepts, procedures and methods that have far-reaching implications in the chemistry world. Technologies have been grouped as topics of opportunity and their recent applications in innovative research laboratories are described.

An efficient green protocol for the preparation of acetoacetamides and application of the methodology to a one-pot synthesis of Biginelli dihydropyrimidines. Expansion of dihydropyrimidine topological chemical space

A one pot synthesis of Biginelli dihydropyrimidines. The novel use of the amino acids allows topological diversification of the chemical space.

Flow chemistry as a versatile tool for the synthesis of triazoles

This review surveys the continuous-flow strategies for the synthesis of triazoles by means of copper-catalyzed and catalyst-free cycloadditions between azides and various dipolarophiles.