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Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines ionizable lipid development with efficient library design, in silico lipid screening via deep neural networks, and adaptability to diverse cell lines. Using AGILE, we rapidly design, synthesize, and evaluate ionizable lipids for mRNA delivery, selecting from a vast library. Intriguingly, AGILE reveals cell-specific preferences for ionizable lipids, indicating tailoring for optimal delivery to varying cell types. These highlight AGILE’s potential in expediting the development of customized LNPs, addressing the complex needs of mRNA delivery in clinical practice, thereby broadening the scope and efficacy of mRNA therapies. In this work, the authors develop a platform called AGILE or AI Guided Ionizable Lipid Engineering, which streamlines ionizable lipid development. Using AGILE, they rapidly design, synthesize, and evaluate ionizable lipids for mRNA delivery.

The authoritative reference on High Content Screening (HCS) in biological and pharmaceutical research, this guide covers: the basics of HCS: examples of HCS used in biological applications and early drug discovery, emphasizing oncology and neuroscience; the use of HCS across the drug development pipeline; and data management, data analysis, and systems biology, with guidelines for using large datasets. With an accompanying CD-ROM, this is the premier reference on HCS for researchers, lab managers, and graduate students.

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry—many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry–virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

Solid-phase synthesis represents the methodological showcase for technological advances such as split-and-pool combinatorial chemistry and the automated synthesis of peptides, nucleic acids and polysaccharides. These strategies involve iterative coupling cycles that do not generate functional diversity besides that incorporated by the amino acids, nucleosides and monosaccharide building blocks. In sharp contrast, multicomponent reactions (MCRs) are traditionally used to generate both skeletal and appendage diversity in short, batchwise procedures. On-resin MCRs have traditionally been employed for the construction of heterocycle and peptidomimetic libraries, but that scenario has changed recently, and today the focus is more on the solid-phase derivatization of peptides and oligonucleotides. This review presents relevant experimental details and addresses the synthetic scope of such on-resin multicomponent protocols employed to accomplish specific biopolymer covalent modifications that are practically inviable by traditional solution-phase methodologies. Recommendations are provided to facilitate the implementation of solid-supported protocols and avoid possible pitfalls associated with the selection of the polymeric resin, the solvent and the order and amount of the reagents employed. We describe procedures comprising the multicomponent lipidation, biotinylation and labeling of both termini and the side chains, as well as the use of MCRs in the traceless on-resin synthesis of ligated and cyclic peptides. Solid-phase protocols for the assembly of α-helical and parallel β-sheet peptides as well as hybrid peptide-peptoid and peptide-peptide nucleic acid architectures are described. Finally, the solid-supported multicomponent derivatization of DNA oligonucleotides is illustrated as part of the DNA-encoded library technology relying on MCR-derived heterocyclic compounds.

Iron is one of the most abundant elements in the Universe and Earth’s surfaces, and undergoes a redox change of approximately 0.77 mV in changing between its +2 and +3 states. Many contemporary terrestrial organisms are deeply connected to inorganic geochemistry via exploitation of this redox change, and iron redox reactions and catalysis are known to cause significant changes in the course of complex abiotic reactions. These observations point to the question of whether iron may have steered prebiotic chemistry during the emergence of life. Using kinetically naive in silico reaction modeling we explored the potential effects of iron ions on complex reaction networks of prebiotic interest, namely the formose reaction, the complexifying degradation reaction of pyruvic acid in water, glucose degradation, and the Maillard reaction. We find that iron ions produce significant changes in the connectivity of various known diversity-generating reaction networks of proposed prebiotic significance, generally significantly diversifying novel molecular products by ~20%, but also adding the potential for kinetic effects that could allow iron to steer prebiotic chemistry in marked ways.

Multifunctionalized materials are expected to be versatile probes to find specific interactions between a ligand and a target biomaterial. Thus, efficient methods to prepare possible combinations of the functionalities is desired. The concept of dynamic combinatorial chemistry (DCC) is ideal for the generation of any possible combination, as well as screening for target biomaterials. Here, we propose a new molecular design of multitopic probes for ligand discovery in DCC. We synthesized a new Gable Porphyrin, GP1, having prop-2-yne groups as a scaffold to introduce various functional groups. GP1 is a bis(imidazolylporphyrinatozinc) compound connected through a 1,3-phenylene moiety, and it gives macrocycles spontaneously and quantitatively by strong imidazole-to-zinc complementary coordination. Some different types of functional groups were introduced into GP1 in high yields. Formation of heterogeneous macrocycles composed of GP1 derivatives having different types of substituents was accomplished under equilibrium conditions. These results promise that enormous numbers of macrocycles having various functional groups can be provided when the kinds of GP components increase. These features are desirable for DCC, and the present system using GP1 is a potential candidate to provide a dynamic combinatorial library of multitopic probes to discover specific interactions between a ligand and a biomaterial.

Base‐filling, i. e ., post‐synthetic furnishing of an oligonucleotide scaffold with base moieties or their analogues, is an interesting alternative to the conventional approach of sequential coupling of building blocks (modified or otherwise). Reversible attachment of the base moieties is particularly attractive as it allows the use of dynamic combinatorial chemistry and usually leads to higher fidelity. This concept article summarizes the various backbones and coupling reactions used for base‐filling over the past fifteen years, discusses the impact of base stacking and pairing on efficiency and fidelity and highlights potential and realized applications.

It is crucial to establish relationship between nanoparticle structures (or properties) and nanotoxicity. Previous investigations have shown that a nanoparticle’s size, shape, surface and core materials all impact its toxicity. However, the relationship between the redox property of nanoparticles and their toxicity has not been established when all other nanoparticle properties are identical. Here, by synthesizing an 80-membered combinatorial gold nanoparticle (GNP) library with diverse redox properties, we systematically explored this causal relationship. The compelling results revealed that the oxidative reactivity of GNPs, rather than their other physicochemical properties, directly caused cytotoxicity via induction of cellular oxidative stress. Our results show that the redox diversity of nanoparticles is regulated by GNPs modified with redox reactive ligands.

An implementation of the three-component one-pot approach to unsymmetrical 1,3,5-trisubstituted-1,2,4-triazoles into combinatorial chemistry is described. The procedure is based on the coupling of amidines with carboxylic acids and subsequent cyclization with hydrazines. After the preliminary assessment of the reagent scope, the method had 81% success rate in parallel synthesis. It was shown that over a billion-sized chemical space of readily accessible (“REAL”) compounds may be generated based on the proposed methodology. Analysis of physicochemical parameters shows that the library contains significant fractions of both drug-like and “beyond-rule-of-five” members. More than 10 million of accessible compounds meet the strictest lead-likeness criteria. Additionally, 195 Mln of sp3-enriched compounds can be produced. This makes the proposed approach a valuable tool in medicinal chemistry.Graphic abstract

All aspects of plant and animal development are controlled by complex networks of transcription factors. Transcription factors are essential for converting signaling inputs, such as changes in daylength, into complex gene regulatory outputs. While some transcription factors control gene expression by binding to cis-regulatory elements as individual subunits, others function in a combinatorial fashion. How individual subunits of combinatorial transcription factors are spatially and temporally deployed (e.g. expression-level, posttranslational modifications and subcellular localization) has profound effects on their control of gene expression. In the model plant Arabidopsis (Arabidopsis thaliana), we have identified 36 Nuclear Factor Y (NF-Y) transcription factor subunits (10 NF-YA, 13 NF-YB, and 13 NF-YC subunits) that can theoretically combine to form 1,690 unique complexes. Individual plant subunits have functions in flowering time, embryo maturation, and meristem development, but how they combine to control these processes is unknown. To assist in the process of defining unique NF-Y complexes, we have created promoter:β-glucuronidase fusion lines for all 36 Arabidopsis genes. Here, we show NF-Y expression patterns inferred from these promoter:β-glucuronidase lines for roots, light- versus dark-grown seedlings, rosettes, and flowers. Additionally, we review the phylogenetic relationships and examine protein alignments for each NF-Y subunit family. The results are discussed with a special emphasis on potential roles for NF-Y subunits in photoperiod-controlled flowering time.