AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

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.

Building Block-Centric Approach to DNA-Encoded Library Design.

DNA-encoded library technology grants access to nearly infinite opportunities to explore the chemical structure space for drug discovery. Successful navigation depends on the design and synthesis of libraries with appropriate physicochemical properties (PCPs) and structural diversity while aligning with practical considerations. To this end, we analyze combinatorial library design constraints including the number of chemistry cycles, bond construction strategies, and building block (BB) class selection in pursuit of ideal library designs. We compare two-cycle library designs (amino acid + carboxylic acid, primary amine + carboxylic acid) in the context of PCPs and chemical space coverage, given different BB selection strategies and constraints. We find that broad availability of amines and acids is essential for enabling the widest exploration of chemical space. Surprisingly, cost is not a driving factor, and virtually, the same chemical space can be explored with "budget" BBs.

Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry.

To unlock the full promise of messenger (mRNA) therapies, expanding the toolkit of lipid nanoparticles is paramount. However, a pivotal component of lipid nanoparticle development that remains a bottleneck is identifying new ionizable lipids. Here we describe an accelerated approach to discovering effective ionizable lipids for mRNA delivery that combines machine learning with advanced combinatorial chemistry tools. Starting from a simple four-component reaction platform, we create a chemically diverse library of 584 ionizable lipids. We screen the mRNA transfection potencies of lipid nanoparticles containing those lipids and use the data as a foundational dataset for training various machine learning models. We choose the best-performing model to probe an expansive virtual library of 40,000 lipids, synthesizing and experimentally evaluating the top 16 lipids flagged. We identify lipid 119-23, which outperforms established benchmark lipids in transfecting muscle and immune cells in several tissues. This approach facilitates the creation and evaluation of versatile ionizable lipid libraries, advancing the formulation of lipid nanoparticles for precise mRNA delivery.

Innovative, combinatorial and high-throughput approaches to degrader synthesis.

Targeted protein degraders such as PROTACs and molecular glues are a rapidly emerging therapeutic modality within industry and academia. Degraders possess unique mechanisms of action that lead to the removal of specific proteins by co-opting the cell's natural degradation mechanisms via induced proximity. Their optimisation thus far has often been largely empirical, requiring the synthesis and screening of a large number of analogues. In addition, the synthesis and development of degraders is often challenging, leading to lengthy optimisation campaigns to deliver candidate-quality compounds. This review highlights how the synthesis of degraders has evolved in recent years, in particular focusing on means of applying high-throughput chemistry and screening approaches to expedite these timelines, which we anticipate to be valuable in shaping the future of degrader optimisation campaigns.

Discovery of selective monosaccharide receptors via dynamic combinatorial chemistry.

The molecular recognition of saccharides by synthetic hosts has become an appealing but elusive task in the last decades. Herein, we combine Dynamic Combinatorial Chemistry (DCC) for the rapid self-assembly and screening of virtual libraries of receptors, with the use of ITC and NMR to validate the hits and molecular modelling to understand the binding mechanisms. We discovered a minimalistic receptor, 1F (N-benzyl-L-phenylalanine), with considerable affinity for fructose (Ka = 1762 M-1) and remarkable selectivity (>50-fold) over other common monosaccharides. The approach accelerates the discovery process of receptors for saccharides.

Ternary Complex-Templated Dynamic Combinatorial Chemistry for the Selection and Identification of Homo-PROTACs.

Dynamic combinatorial chemistry (DCC) leverages a reversible reaction to generate compound libraries from constituting building blocks under thermodynamic control. The position of this equilibrium can be biased by addition of a target macromolecule towards enrichment of bound ligands. While DCC has been applied to select ligands for a single target protein, its application to identifying chimeric molecules inducing proximity between two proteins is unprecedented. In this proof-of-concept study, we develop a DCC approach to select bifunctional proteolysis targeting chimeras (PROTACs) based on their ability to stabilize the ternary complex. We focus on VHL-targeting Homo-PROTACs as model system, and show that the formation of a VHL2 : Homo-PROTAC ternary complex reversibly assembled using thiol-disulfide exchange chemistry leads to amplification of potent VHL Homo-PROTACs with degradation activities which correlated well with their biophysical ability to dimerize VHL. Ternary complex templated dynamic combinatorial libraries allowed identification of novel Homo-PROTAC degraders. We anticipate future applications of ternary-complex directed DCC to early PROTAC screenings and expansion to other proximity-inducing modalities beyond PROTACs.

Combinatorial Libraries of Bipodal Binders of the Insulin Receptor.

The binding process of insulin to its transmembrane receptor entails a sophisticated interplay between two proteins, each possessing two binding sites. Given the difficulties associated with the use of insulin in the treatment of diabetes, despite its remarkable efficacy, there is interest in smaller and more stable compounds than the native hormone that would effectively activate the receptor. Our study adopts a strategy focused on synthesizing extensive combinatorial libraries of bipodal compounds consisting of two distinct peptides linked to a molecular scaffold. These constructs, evaluated in a resin bead-bound format, were designed to assess their binding to the insulin receptor. Despite notable nonspecific binding, our approach successfully generated and tested millions of compounds. Rigorous evaluations via flow cytometry and specific antibodies revealed peptide sequences with specific interactions at either receptor binding Site 1 or 2. Notably, these sequences bear similarity to peptides discovered through phage display by other researchers. This convergence of chemical and biological methods underscores nature's beauty, revealing general principles in peptide binding to the insulin receptor. Overall, our study deepens the understanding of molecular interactions in ligand binding to the insulin receptor, highlighting the challenges of targeting large proteins with small synthetic peptides.

Expanding Chemical Frontiers: Approaches for Generating Diverse and Bioactive Natural Product-Like Compounds Libraries from Extracts.

The realms of natural products and synthetic compounds exhibit distinct chemical spaces that not only differ but also complement each other. While the convergence of these two domains has been explored through semisynthesis and conventional pharmacomodulation endeavours applied to natural frameworks, a recent and innovative approach has emerged that involves the combinatorial generation of libraries of 'natural product-like compounds' (NPLCs) through the direct synthetic derivatization of natural extracts. This has led to the production of numerous NPLCs that incorporate structural elements from both their natural (multiple saturated rings, oxygen content, chiral centres) and synthetic (aromatic rings, nitrogen and halogen content, drug-like properties) precursors. Through careful selection of extracts and reagents, specific bioactivities have been achieved, and this strategy has been deployed in various ways, showing great promise without reaching its full potential to date. This review seeks to provide an overview of reported examples involving the chemical engineering of extracts, showcasing a spectrum of natural product alterations spanning from simple substitutions to complete scaffold remodelling. It also includes an analysis of the accomplishments, perspectives and technical challenges within this field.

NeuroClick: software for mimicking click reaction to generate drug-like molecules permeating the blood-brain barrier.

Background: Traditional methods for chemical library generation in virtual screening often impose limitations on the accessible chemical space or produce synthetically irrelevant structures. Incorporating common chemical reactions into generative algorithms could offer significant benefits. Materials & methods: In this study, we developed NeuroClick, a graphical user interface software designed to perform in silico azide-alkyne cycloaddition, a widely utilized synthetic approach in modern medicinal chemistry. Results & conclusion: NeuroClick facilitates the generation and filtering of large combinatorial libraries at a remarkable rate of 10,000 molecules per minute. Moreover, the generated products can be filtered to identify subsets of pharmaceutically relevant compounds based on Lipinski's rule of five and blood-brain barrier permeability prediction. We demonstrate the utility of NeuroClick by generating and filtering several thousand molecules for dopamine D3 receptor ligand screening.

Screening Ultra-Large Encoded Compound Libraries Leads to Novel Protein-Ligand Interactions and High Selectivity.

The DNA-encoded library (DEL) discovery platform has emerged as a powerful technology for hit identification in recent years. It has become one of the major parallel workstreams for small molecule drug discovery along with other strategies such as HTS and data mining. For many researchers working in the DEL field, it has become increasingly evident that many hits and leads discovered via DEL screening bind to target proteins with unique and unprecedented binding modes. This Perspective is our attempt to analyze reports of DEL screening with the purpose of providing a rigorous and useful account of the binding modes observed for DEL-derived ligands with a focus on binding mode novelty.

Solid-phase peptide synthesis in 384-well plates.

Newer solid-phase peptide synthesis and release strategies enable the production of short peptides with high purity, allowing direct screening for desired bioactivity without prior chromatographic purification. However, the maximum number of peptides that can currently be synthesized per microplate reactor is 96, allowing the parallel synthesis of 384 peptides in modern devices that have space for 4 microplate reactors. To synthesize larger numbers of peptides, we modified a commercially available peptide synthesizer to enable the production of peptides in 384-well plates, which allows the synthesis of 1,536 peptides in one run (4 × 384 peptides). We report new hardware components and customized software that allowed for the synthesis of 1,536 short peptides in good quantity (average > 0.5 µmol), at high concentration (average > 10 mM), and decent purity without purification (average > 80%). The high-throughput peptide synthesis, which we developed with peptide drug development in mind, may be widely used for peptide library synthesis and screening, antibody epitope scanning, epitope mimetic development, or protease/kinase substrate screening.

De novo development of small cyclic peptides that are orally bioavailable.

Cyclic peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, as with biological drugs, most cyclic peptides cannot be applied orally because they are rapidly digested and/or display low absorption in the gastrointestinal tract, hampering their development as therapeutics. In this study, we developed a combinatorial synthesis and screening approach based on sequential cyclization and one-pot peptide acylation and screening, with the possibility of simultaneously interrogating activity and permeability. In a proof of concept, we synthesized a library of 8,448 cyclic peptides and screened them against the disease target thrombin. Our workflow allowed multiple iterative cycles of library synthesis and yielded cyclic peptides with nanomolar affinities, high stabilities and an oral bioavailability (%F) as high as 18% in rats. This method for generating orally available peptides is general and provides a promising push toward unlocking the full potential of peptides as therapeutics.

Analytical Tools for Dynamic Combinatorial Libraries of Cyclic Peptides.

Target-directed dynamic combinatorial chemistry is a very attractive strategy for the discovery of bioactive peptides. However, its application has not yet been demonstrated, presumably due to analytical challenges that arise from the diversity of a peptide library with combinatorial side-chains. We previously reported an efficient method to generate, under biocompatible conditions, large dynamic libraries of cyclic peptides grafted with amino acid's side-chains, by thiol-to-thioester exchanges. In this work, we present analytical tools to easily characterize such libraries by HPLC and mass spectrometry, and in particular to simplify the isomers' distinction requiring sequencing by MS/MS fragmentations. After structural optimization, the cyclic scaffold exhibits a UV-tag, absorbing at 415 nm, and an ornithine residue which favors the regioselective ring-opening and simultaneous MS/MS fragmentation, in the gas-phase.

Initial study of the detection of ADAM 10 in the urine of type-2 diabetic patients.

Diabetes mellitus (DM) is a disease of civilization. If left untreated, it can cause serious complications and significantly shortens the life time. DM is one of the leading causes of end-stage renal disease (uremia) worldwide. Early diagnosis is a prerequisite for successful treatment, preferably before the first symptoms appear. In this paper, we describe the optimization and synthesis of the internally quenched fluorescent substrate disintegrin and metalloproteinase 10 (ADAM10). Using combinatorial chemistry methods with iterative deconvolution, the substrate specificity of the enzyme in non-primed and primed positions was determined. We used the ABZ-Lys-Ile-Ile-Asn-Leu-Lys-Arg-Tyr(3-NO2)-NH2 peptide to study ADAM10 activity in urine samples collected from patients diagnosed with type 2 diabetes, compared to urine samples from healthy volunteers. The proteolytically active enzyme was present in diabetes samples, while in the case of healthy people we did not observe any activity. In conclusion, our study provides a possible basis for further research into the potential role of ADAM10 in the diagnosis of type 2 diabetes.

Toward tryptathionine-stapled one-bead-one-compound (OBOC) libraries: solid phase synthesis of a bioactive octretoate analog.

New somatostatin analogs are highly desirable for diagnosing and treating neuroendocrine tumors (NETs). Here we describe the solid-phase synthesis of a new octreotate (TATE) analog where the disulfide bond is replaced with a tryptathionine (Ttn) staple as part of an effort to prototyping a one-bead-one-compound (OBOC) library of Ttn-stapled peptides. Library design provides the potential for on- and off-bead screening. To validate our method, we labelled Ttn-TATE with a fluorescent dye to demonstrate binding to soluble somatostatin receptor subtype-2 and staining of Ar42J rat prostate cancer cells. By exploring this staple in the context of a ligand of known affinity, this method paves the way for an OBOC library construction of bioactive octreotate analogs and, more broadly speaking, tryptathionine-staped peptide macrocycles.

DNA-compatible combinatorial synthesis of functionalized 2-thiobenzazole scaffolds.

2-Thiobenzazole is among the privileged heterocyclic scaffolds in medicinal chemistry. Constructing such structural components in DNA-encoded libraries (DELs) may promote related bioactive hit discovery in a high-throughput fashion. Herein, we reported a DNA-compatible mild-condition synthetic methodology to efficiently forge functionalized 2-thiobenzazole scaffolds, realizing on-DNA sulfhydryl incorporation with broad substrate scope, thereby expanding the scope of 2-thiobenzazole-focused DNA-encoded chemical libraries.

Mixture-Based Screening of Focused Combinatorial Libraries by NMR: Application to the Antiapoptotic Protein hMcl-1.

We report on an innovative ligand discovery strategy based on protein NMR-based screening of a combinatorial library of ∼125,000 compounds that was arranged in 96 distinct mixtures. Using sensitive solution protein NMR spectroscopy and chemical perturbation-based screening followed by an iterative synthesis, deconvolutions, and optimization strategy, we demonstrate that the approach could be useful in the identification of initial binding molecules for difficult drug targets, such as those involved in protein-protein interactions. As an application, we will report novel agents targeting the Bcl-2 family protein hMcl-1. The approach is of general applicability and could be deployed as an effective screening strategy for de novo identification of ligands, particularly when tackling targets involved in protein-protein interactions.

Nucleic acids as templates and catalysts in chemical reactions: target-guided dynamic combinatorial chemistry and in situ click chemistry and DNA/RNA induced enantioselective reactions.

Nucleic acids play crucial roles in transferring cellular information and gene regulations. DNA and RNA molecules have been associated with multiple human diseases and thus offer opportunities for exploring small molecule-based therapeutics. However, developing target-selective molecules possessing well-defined biological activity, has always been challenging. In the current scenario, where the world is continuously experiencing outbreaks of new infectious diseases, it is always important to expand the scope of chemical toolsets to override conventional drug discovery strategies for developing therapeutically relevant drug candidates. The template-directed synthetic approach has emerged as a promising tool for rapid drug discovery. It allows a biological target to template the selection or synthesis of its ligands from a pool of reactive fragments. There are two main template-directed synthetic strategies: thermodynamically controlled dynamic combinatorial chemistry (DCC) and kinetically controlled target-guided in situ click chemistry. Though discovered only two decades ago, these techniques have proven their usefulness for nucleic acid targets, as exemplified by the increasing number of applications with therapeutically important DNA and RNA targets. However, nucleic acid templated synthetic techniques are relatively unexplored in drug discovery compared to protein targets. In this review article, we have presented a detailed discussion of all the reported nucleic acid templated synthetic studies to portray the great potential of this strategy for efficient hit discovery and lead optimisation. This article would assist in expanding the scope and utility of this strategy through a summary of the advancements and emerging applications. Additionally, a brief overview of the catalytic potential of nucleic acids in asymmetric synthesis has been provided to give a valuable vision of the use of nucleic acids to induce enantioselectivity in chiral drug-like candidates.

Low-Abundance Protein Enrichment for Medical Applications: The Involvement of Combinatorial Peptide Library Technique.

The discovery of low- and very low-abundance proteins in medical applications is considered a key success factor in various important domains. To reach this category of proteins, it is essential to adopt procedures consisting of the selective enrichment of species that are present at extremely low concentrations. In the past few years pathways towards this objective have been proposed. In this review, a general landscape of the enrichment technology situation is made first with the presentation and the use of combinatorial peptide libraries. Then, a description of this peculiar technology for the identification of early-stage biomarkers for well-known pathologies with concrete examples is given. In another field of medical applications, the determination of host cell protein traces potentially present in recombinant therapeutic proteins, such as antibodies, is discussed along with their potentially deleterious effects on the health of patients on the one hand, and on the stability of these biodrugs on the other hand. Various additional applications of medical interest are disclosed for biological fluids investigations where the target proteins are present at very low concentrations (e.g., protein allergens).