Automated synthesis: new tools for the organic chemist

A robotic system for automated chemical synthesis of therapeutic agents

The development of novel compounds for tissue-specific targeting and imaging is often impeded by a lack of lead compounds and the availability of reliable chemistry. Automated chemical synthesis systems provide a potential solution by enabling reliable, repeated access to large compound libraries for screening. Here we report an integrated solid-phase combinatorial chemistry system created using commercial and customized robots. Our goal is to optimize reaction parameters, such as varying temperature, shaking, microwave irradiation, aspirating and dispensing large-sized solid beads, and handling different washing solvents for separation and purification. This automated system accommodates diverse chemical reactions such as peptide synthesis and conventional coupling reactions. To confirm its functionality and reproducibility, 20 nerve-specific contrast agents for biomedical imaging were systematically and repeatedly synthesized and compared to other nerve-targeted agents using molecular fingerprinting and Uniform Manifold Approximation and Projection, which lays the foundation for creating reliable and reproductive chemical libraries in bioimaging and nanomedicine.

Autonomous Molecular Design: Then and Now

The success of deep machine learning in processing of large amounts of data, for example, in image or voice recognition and generation, raises the possibilities that these tools can also be applied for solving complex problems in materials science. In this forum article, we focus on molecular design that aims to answer the question on how we can predict and synthesize molecules with tailored physical, chemical, or biological properties. A potential answer to this question could be found by using intelligent systems that integrate physical models and computational machine learning techniques with automated synthesis and characterization tools. Such systems learn through every single experiment in an analogy to a human scientific expert. While the general idea of an autonomous system for molecular synthesis and characterization has been around for a while, its implementations for the materials sciences are sparse. Here we provide an overview of the developments in chemistry automation and the applications of machine learning techniques in the chemical and pharmaceutical industries with a focus on the novel capabilities that deep learning brings in.

Glutathione-Responsive Prodrug Nanoparticles for Effective Drug Delivery and Cancer Therapy

Spurred by recent progress in medicinal chemistry, numerous lead compounds have sprung up in the past few years, although the majority are hindered by hydrophobicity, which greatly challenges druggability. In an effort to assess the potential of platinum (Pt) candidates, the nanosizing approach to alter the pharmacology of hydrophobic Pt(IV) prodrugs in discovery and development settings is described. The construction of a self-assembled nanoparticle (NP) platform, composed of amphiphilic lipid-polyethylene glycol (PEG) for effective delivery of Pt(IV) prodrugs capable of resisting thiol-mediated detoxification through a glutathione (GSH)-exhausting effect, offers a promising route to synergistically improving safety and efficacy. After a systematic screening, the optimized NPs (referred to as P6 NPs) exhibited small particle size (99.3 nm), high Pt loading (11.24%), reliable dynamic stability (∼7 days), and rapid redox-triggered release (∼80% in 3 days). Subsequent experiments on cells support the emergence of P6 NPs as a highly effective means of transporting a lethal dose of cargo across cytomembranes through macropinocytosis. Upon reduction by cytoplasmic reductants, particularly GSH, P6 NPs under disintegration released sufficient active Pt(II) metabolites, which covalently bound to target DNA and induced significant apoptosis. The PEGylation endowed P6 NPs with in vivo longevity and tumor specificity, which were essential to successfully inhibiting the growth of cisplatin-sensitive and -resistant xenograft tumors, while effectively alleviating toxic side-effects associated with cisplatin. P6 NPs are, therefore, promising for overcoming the bottleneck in the development of Pt drugs for oncotherapy.

Automatic Dendritic Length Quantification for High Throughput Screening of Mature Neurons

High-throughput automated fluorescent imaging and screening are important for studying neuronal development, functions, and pathogenesis. An automatic approach of analyzing images acquired in automated fashion, and quantifying dendritic characteristics is critical for making such screens high-throughput. However, automatic and effective algorithms and tools, especially for the images of mature mammalian neurons with complex arbors, have been lacking. Here, we present algorithms and a tool for quantifying dendritic length that is fundamental for analyzing growth of neuronal network. We employ a divide-and-conquer framework that tackles the challenges of high-throughput images of neurons and enables the integration of multiple automatic algorithms. Within this framework, we developed algorithms that adapt to local properties to detect faint branches. We also developed a path search that can preserve the curvature change to accurately measure dendritic length with arbor branches and turns. In addition, we proposed an ensemble strategy of three estimation algorithms to further improve the overall efficacy. We tested our tool on images for cultured mouse hippocampal neurons immunostained with a dendritic marker for high-throughput screen. Results demonstrate the effectiveness of our proposed method when comparing the accuracy with previous methods. The software has been implemented as an ImageJ plugin and available for use.

High Throughput Chemistry in Drug Discovery

This chapter outlines the evolution of high throughput chemistry from its origins in the genome revolution of the early 1990's to its current practice as an integral tool in drug discovery, via the concept of the large “universal library” to the practice of small targeted arrays for structure–activity relationship generation. The technologies developed as part of this evolution are also outlined including early ACT peptide synthesisers and other automated and non-automated devices for both solid-supported and solution-based approaches. Finally, the chapter outlines several case studies of the application of high throughput synthesis to drug discovery.

Screening and synthesis: high throughput technologies applied to parasitology

High throughput technologies continue to develop in response to the challenges set by the genome projects. This article discusses how the techniques of both high throughput screening (HTS) and synthesis can influence research in parasitology. Examples of the use of targeted and phenotype-based HTS using unbiased compound collections are provided. The important issue of identifying the protein target(s) of bioactive compounds is discussed from the synthetic chemist's perspective. This article concludes by reviewing recent examples of successful target identification studies in parasitology.

Automated medicinal chemistry

With the advent of high throughput technologies in biological screening in the 1980s, providing sufficient numbers of small molecules for screening became a bottleneck in the drug discovery process. Combinatorial chemistry was the first attempt by chemists to address this issue. However, since its first applications, combinatorial chemistry has evolved rapidly into diverse fields. This review will focus on the evolution and the current status of what we refer to today as automated medicinal chemistry.

A convenient solid-phase synthesis methodology for preparing peptide-derived molecular imaging agents — Synthesis, characterization, and in vitro screening of Tc(I) – chemotactic peptide conjugates

A versatile solid-phase synthesis strategy for preparing peptide–chelate conjugates was developed. The methodology was optimized using a series of ligands, designed to bind Tc(I)/Re(I), and a chemotactic peptide fMFL, which was exploited as a model targeting vector. The peptide derivatives were prepared in parallel using a conventional automated peptide synthesizer in multi-milligram quantities, which provided sufficient material to perform complete characterization, radiolabelling, and in vitro screening studies. Because of the robust nature of the metal–chelate complexes, the Re complex of a chelate–peptide conjugate was prepared on the resin using the same methodology employed to prepare the free ligand conjugates. As such, the reported methodology is amenable to the preparation of libraries of novel Tc radiopharmaceutical ligands and their corresponding Re reference standards in which several factors, including peptide sequence, site of derivatization, and both the type and length of the spacer, can be easily varied.Key words: radiopharmaceuticals, technetium, rhenium, peptides, solid-phase synthesis.

New tools and concepts for modern organic synthesis

The increasing need to efficiently assemble small molecules as potential modulators of therapeutic targets that are emerging from genomics and proteomics is driving the development of novel technologies for small-molecule synthesis. Here, we describe some of the general applications and approaches to synthesis using one such technology--solid-supported reagents--that has been shown to significantly improve productivity in the generation of combinatorial libraries and complex target molecules.

Life in the fast lane: high-throughput chemistry for lead generation and optimisation

The pharmaceutical industry has come under increasing pressure due to regulatory restrictions on the marketing and pricing of drugs, competition, and the escalating costs of developing new drugs. These forces can be addressed by the identification of novel targets, reductions in the development time of new drugs, and increased productivity. Emphasis has been placed on identifying and validating new targets and on lead generation: the response from industry has been very evident in genomics and high throughput screening, where new technologies have been applied, usually coupled with a high degree of automation. The combination of numerous new potential biological targets and the ability to screen large numbers of compounds against many of these targets has generated the need for large diverse compound collections. To address this requirement, high-throughput chemistry has become an integral part of the drug discovery process.

Combinatorial synthesis of libraries of indole derivatives

The synthesis of two indole derivative libraries is described. 2-Acyl-3-amino-indoles 4 can easily be accessed by treatment of the intermediates 3 with bases in a one-pot reaction sequence whereas the reaction of the isolated intermediates 5 (R(3)=aromatic-, heteroaromatic, or cycloalkyl) with acid chlorides yielded the novel indole derivatives 6. The products were purified by reversed phase column chromatography and obtained in multi-milligram quantities in acceptable yields.

The application of non-combinatorial chemistry to lead discovery

Non-combinatorial chemistry is a powerful technology for the synthesis of large numbers of compounds, with complete control over the properties of those compounds. We have developed a Library Creation, Registration and Automation system (LiCRA), which harnesses an efficient non-combinatorial chemistry design and synthesis engine, together with high-throughput automated purification. This LiCRA system also operates in a closed loop mode for hit-to-lead optimization, and contains an integrated IT system that controls and facilitates all aspects of the operation from design to registration. Quality has been our watchword, from the quality of compound design through to the quality of the products.

Techniques for analysis and purification in high-throughput chemistry

The success of combinatorial chemistry, and the increased emphasis on single well-characterised compounds of high purity, has had a significant impact on analytical and purification technologies. The requirement for ever-increasing throughput has led to the automation and parallelisation of these techniques. Advances have also been made in developing faster methods to augment throughput further.

Successful implementation of automation in medicinal chemistry

Automation in medicinal chemistry is often seen simply as a part of the combinatorial chemistry technologies used to meet the need for large, diverse screening collections for lead generation. However, the application of automation to the lead optimization phase of drug discovery offers the prospect of reduced cycle times via increased efficiency in target compound preparation. The realization of this goal requires the integration of efficient processes with equipment capable of delivering quality compounds - and, of course, the skilled medicinal chemists.