Discovery of Small‐Molecule Interleukin‐2 Inhibitors from a DNA‐Encoded Chemical Library

Libraries of chemical compounds individually coupled to encoding DNA tags (DNA‐encoded chemical libraries) hold promise to facilitate exceptionally efficient ligand discovery. We constructed a high‐quality DNA‐encoded chemical library comprising 30 000 drug‐like compounds; this was screened in 170 different affinity capture experiments. High‐throughput sequencing allowed the evaluation of 120 million DNA codes for a systematic analysis of selection strategies and statistically robust identification of binding molecules. Selections performed against the tumor‐associated antigen carbonic anhydrase IX (CA IX) and the pro‐inflammatory cytokine interleukin‐2 (IL‐2) yielded potent inhibitors with exquisite target specificity. The binding mode of the revealed pharmacophore against IL‐2 was confirmed by molecular docking. Our findings suggest that DNA‐encoded chemical libraries allow the facile identification of drug‐like ligands principally to any protein of choice, including molecules capable of disrupting high‐affinity protein–protein interactions.     

20 years of DNA-encoded chemical libraries

The identification of specific binding molecules is a central problem in chemistry, biology and medicine. Therefore, technologies, which facilitate ligand discovery, may substantially contribute to a better understanding of biological processes and to drug discovery. DNA-encoded chemical libraries represent a new inexpensive tool for the fast and efficient identification of ligands to target proteins of choice. Such libraries consist of collections of organic molecules, covalently linked to a unique DNA tag serving as an amplifiable identification bar code. DNA-encoding enables the in vitro selection of ligands by affinity capture at sub-picomolar concentrations on virtually any target protein of interest, in analogy to established selection methodologies like antibody phage display. Multiple strategies have been investigated by several academic and industrial laboratories for the construction of DNA-encoded chemical libraries comprising up to millions of DNA-encoded compounds. The implementation of next generation high-throughput sequencing enabled the rapid identification of binding molecules from DNA-encoded libraries of unprecedented size. This article reviews the development of DNA-encoded library technology and its evolution into a novel drug discovery tool, commenting on challenges, perspectives and opportunities for the different experimental approaches.     

Affinity Selections of DNA-Encoded Chemical Libraries on Carbonic Anhydrase IX-Expressing Tumor Cells Reveal a Dependence on Ligand Valence

DNA-encoded chemical libraries are typically screened against purified protein targets. Recently, cell-based selections with encoded chemical libraries have been described, commonly revealing suboptimal performance due to insufficient recovery of binding molecules. We used carbonic anhydrase IX (CAIX)-expressing tumor cells as a model system to optimize selection procedures with code-specific quantitative polymerase chain reaction (qPCR) as selection readout. Salt concentration and performing PCR on cell suspension had the biggest impact on selection performance, leading to 15-fold enrichment factors for high-affinity monovalent CAIX binders (acetazolamide; K_D=8.7 nM). Surprisingly, the homobivalent display of acetazolamide at the extremities of both complementary DNA strands led to a substantial improvement of both ligand recovery and enrichment factors (above 100-fold). The optimized procedures were used for selections with a DNA-encoded chemical library comprising 1 million members against tumor cell lines expressing CAIX, leading to a preferential recovery of known and new ligands against this validated tumor-associated target. This work may facilitate future affinity selections on cells against target proteins which might be difficult to express otherwise.     

Second-generation DNA-encoded multiple display on a constant macrocyclic scaffold enabled by an orthogonal protecting group strategy

DNA-encoded chemical library(DEL) represents an emerging drug discovery technology to construct compound libraries with abundant chemical combinations. While drug-like small molecule DELs facilitate the discovery of binders against targets with defined pockets, macrocyclic DELs harboring extended scaffolds enable targeting of the protein–protein interaction(PPI) interface. We previously demonstrated the design of the first-generation DNA-encoded multiple display based on a constant macrocyclic s...     

Diversified strategy for the synthesis of DNA-encoded oxindole libraries

DNA-encoded library technology (DELT) employs DNA as a barcode to track the sequence of chemical reactions and enables the design and synthesis of libraries with billions of small molecules through combinatorial expansion. This powerful technology platform has been successfully demonstrated for hit identification and target validation for many types of diseases. As a highly integrated technology platform, DEL is capable of accelerating the translation of synthetic chemistry by using on-DNA compatible reactions or off-DNA scaffold synthesis. Herein, we report the development of a series of novel on-DNA transformations based on oxindole scaffolds for the design and synthesis of diversity-oriented DNA-encoded libraries for screening. Specifically, we have developed 1,3-dipolar cyclizations, cyclopropanations, ring-opening of reactions of aziridines and Claisen–Schmidt condensations to construct diverse oxindole derivatives. The majority of these transformations enable a diversity-oriented synthesis of DNA-encoded oxindole libraries which have been used in the successful hit identification for three protein targets. We have demonstrated that a diversified strategy for DEL synthesis could accelerate the application of synthetic chemistry for drug discovery.

Constructing DNA-encoded oxindole libraries by a diversified strategy.     

Design and characterization of libraries of molecular fragments for use in NMR screening against protein targets

We have designed four generations of a low molecular weight fragment library for use in NMR-based screening against protein targets. The library initially contained 723 fragments which were selected manually from the Available Chemicals Directory. A series of in silico filters and property calculations were developed to automate the selection process, allowing a larger database of 1.79 M available compounds to be searched for a further 357 compounds that were added to the library. A kinase binding pharmacophore was then derived to select 174 kinase-focused fragments. Finally, an additional 61 fragments were selected to increase the number of different pharmacophores represented within the library. All of the fragments added to the library passed quality checks to ensure they were suitable for the screening protocol, with appropriate solubility, purity, chemical stability, and unambiguous NMR spectrum. The successive generations of libraries have been characterized through analysis of structural properties (molecular weight, lipophilicity, polar surface area, number of rotatable bonds, and hydrogen-bonding potential) and by analyzing their pharmacophoric complexity. These calculations have been used to compare the fragment libraries with a drug-like reference set of compounds and a set of molecules that bind to protein active sites. In addition, an analysis of the overall results of screening the library against the ATP binding site of two protein targets (HSP90 and CDK2) reveals different patterns of fragment binding, demonstrating that the approach can find selective compounds that discriminate between related binding sites.     

Toward designing drug-like libraries: a novel computational approach for prediction of drug feasibility of compounds

Prediction of the degree of drug-like character in small molecules is of great industrial interest. The major barrier, however, is the lack of a definition for drug-like character. We used the concept of the multilevel chemical compatibility (MLCC) between a compound and a drug library as a measure of the drug-like character of a compound. The rationale is that the local chemical environment of each atom or group of atoms in a compound largely contributes to the stability, toxicity, and metabolism in vivo. A systematic comparison of the local environments within a compound and those within the existing drugs provides a basis for determining whether and how much a compound is drug-like. We applied the MLCC calculations to four test sets: top selling drugs, compounds under biological testing prior to the preclinical test, anticancer drugs, and compounds known to have poor drug-like character. The following conclusions were obtained: (1) A convergent number of unique local structure types were found in the analysis of the library of the existing drugs. It suggests that the current drug library contains about 80% of all the viable types; therefore, discovery of a drug with new local structures is only an event of relatively small probability. (2) The method is highly selective in discerning drug-like compounds: most of the top drugs are predicted to be drug-like, about one-quarter of the biological testing compounds are drug-like, and about one-fifth of the anticancer drugs are drug-like. (3) The method also correctly predicted that none of the known problematic compounds are drug-like. (4) The method is fast enough for computational screening of virtual combinatorial chemistry libraries and databases of available compounds.     

Small-molecule discovery from DNA-encoded chemical libraries

Researchers seeking to improve the efficiency and cost effectiveness of the bioactive small-molecule discovery process have recently embraced selection-based approaches, which in principle offer much higher throughput and simpler infrastructure requirements compared with traditional small-molecule screening methods. Since selection methods benefit greatly from an information-encoding molecule that can be readily amplified and decoded, several academic and industrial groups have turned to DNA as the basis for library encoding and, in some cases, library synthesis. The resulting DNA-encoded synthetic small-molecule libraries, integrated with the high sensitivity of PCR and the recent development of ultra high-throughput DNA sequencing technology, can be evaluated very rapidly for binding or bond formation with a target of interest while consuming minimal quantities of material and requiring only modest investments of time and equipment. In this tutorial review we describe the development of two classes of approaches for encoding chemical structures and reactivity with DNA: DNA-recorded library synthesis, in which encoding and library synthesis take place separately, and DNA-directed library synthesis, in which DNA both encodes and templates library synthesis. We also describe in vitro selection methods used to evaluate DNA-encoded libraries and summarize successful applications of these approaches to the discovery of bioactive small molecules and novel chemical reactivity.     

Selection of DNA-Encoded Dynamic Chemical Libraries for Direct Inhibitor Discovery

Dynamic combinatorial libraries (DCLs) is a powerful tool for ligand discovery in biomedical research; however, the application of DCLs has been hampered by their low diversity. Recently, the concept of DNA encoding has been employed in DCLs to create DNA-encoded dynamic libraries (DEDLs); however, all current DEDLs are limited to fragment identification, and a challenging process of fragment linking is required after selection. We report an anchor-directed DEDL approach that can identify full ligand structures from large-scale DEDLs. This method is also able to convert unbiased libraries into focused ones targeting specific protein classes. We demonstrated this method by selecting DEDLs against five proteins, and novel inhibitors were identified for all targets. Notably, several selective BD1/BD2 inhibitors were identified from the selections against bromodomain 4 (BRD4), an important anti-cancer drug target. This work may provide a broadly applicable method for inhibitor discovery.     

DNA-Encoded Libraries: Towards Harnessing their Full Power with Darwinian Evolution

DNA-encoded library (DEL) technologies are transforming the drug discovery process, enabling the identification of ligands at unprecedented speed and scale. DEL makes use of libraries that are orders of magnitude larger than traditional high-throughput screens. While a DNA tag alludes to a genotype–phenotype connection that is exploitable for molecular evolution, most of the work in the field is performed with libraries where the tag serves as an amplifiable barcode but does not allow “translation” into the synthetic product it is linked to. In this Review, we cover technologies that enable the “translation” of the genetic tag into synthetic molecules, both biochemically and chemically, and explore how it can be used to harness Darwinian evolutionary pressure.     

In silico strategies for the selection of chelating compounds with potential application in metal-promoted neurodegenerative diseases

The development of new strategies to find commercial molecules with promising biochemical features is a main target in the field of biomedicine chemistry. In this work we present an in silico-based protocol that allows identifying commercial compounds with suitable metal coordinating and pharmacokinetic properties to act as metal-ion chelators in metal-promoted neurodegenerative diseases (MpND). Selection of the chelating ligands is done by combining quantum chemical calculations with the search of commercial compounds on different databases via virtual screening. Starting from different designed molecular frameworks, which mainly constitute the binding site, the virtual screening on databases facilitates the identification of different commercial molecules that enclose such scaffolds and, by imposing a set of chemical and pharmacokinetic filters, obey some drug-like requirements mandatory to deal with MpND. The quantum mechanical calculations are useful to gauge the chelating properties of the selected candidate molecules by determining the structure of metal complexes and evaluating their stability constants. With the proposed strategy, commercial compounds containing N and S donor atoms in the binding sites and capable to cross the BBB have been identified and their chelating properties analyzed.     

Microwave-Assisted Soluble Polymer-supported Synthesis of Peptoids

Libraries of peptide-like compounds are attractive sources of binding agents for proteomics applications. The synthesis of oligomeric combinatorial libraries of peptidomimetics is usually more straightforward than the creation of large libraries of more "drug-like" molecules. Herein we report synthesis of peptoids on soluble high loading Noncross-linked polystyrene. The synthesis route consists of: (a) preparation "soluble wang resin" from non-crosslinked polystyrene and 4-hydroxybenzyl alcohol via ether linkage, (b) an esterification step performed by the addition of bromoacetyl bromide to "soluble wang resin" and (c) a nucleophilic displacement of bromide with a primary amine.     

Virtual screening using protein-ligand docking: avoiding artificial enrichment

This study addresses a number of topical issues around the use of protein-ligand docking in virtual screening. We show that, for the validation of such methods, it is key to use focused libraries (containing compounds with one-dimensional properties, similar to the actives), rather than "random" or "drug-like" libraries to test the actives against. We also show that, to obtain good enrichments, the docking program needs to produce reliable binding modes. We demonstrate how pharmacophores can be used to guide the dockings and improve enrichments, and we compare the performance of three consensus-ranking protocols against ranking based on individual scoring functions. Finally, we show that protein-ligand docking can be an effective aid in the screening for weak, fragment-like binders, which has rapidly become a popular strategy for hit identification. All results presented are based on carefully constructed virtual screening experiments against four targets, using the protein-ligand docking program GOLD.     

Designing Novel Compounds for the Treatment and Management of RET-Positive Non-Small Cell Lung Cancer—Fragment Based Drug Design Strategy

Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. These inhibitors exhibit high toxicity, less efficacy, and specificity against RET. The development of drug-resistant mutations in RET protein further deteriorates this situation. Hence, in the present study, we aimed to design novel drug-like compounds using a fragment-based drug designing strategy to overcome these issues. About 18 known inhibitors from diverse chemical classes were fragmented and bred to form novel compounds against RET proteins. The inhibitory activity of the resultant 115 hybrid molecules was evaluated using molecular docking and RF-Score analysis. The binding free energy and chemical reactivity of the compounds were computed using MM-GBSA and density functional theory analysis, respectively. The results from our study revealed that the developed hybrid molecules except for LF21 and LF27 showed higher reactivity and stability than Pralsetinib. Ultimately, the process resulted in three hybrid molecules namely LF1, LF2, and LF88 having potent inhibitory activity against RET proteins. The scrutinized molecules were then subjected to molecular dynamics simulation for 200 ns and MM-PBSA analysis to eliminate a false positive design. The results from our analysis hypothesized that the designed compounds exhibited significant inhibitory activity against multiple RET variants. Thus, these could be considered as potential leads for further experimental studies.     

Privileged structures: applications in drug discovery

Over the past 15 years the privileged structure concept has emerged as a fruitful approach to the discovery of novel biologically active molecules. Privileged structures are molecular scaffolds with versatile binding properties, such that a single scaffold is able to provide potent and selective ligands for a range of different biological targets through modification of functional groups. In addition, privileged structures typically exhibit good drug-like properties, which in turn leads to more drug-like compound libraries and leads. The net result is the production of high quality leads that provide a solid foundation for further development. The identification of privileged structures will be discussed, emphasizing the importance of understanding the structure-target relationships that confer "privileged" status. This understanding allows privileged structure based libraries to be targeted at distinct target families (e.g. GPCRs, LGIC, enzymes/kinases). Privileged structures have been successfully exploited across and within different target families and promises to be an effective approach to the discovery and optimization of novel bioactive molecules. The application of the privileged structure approach, both in traditional medicinal chemistry and in the design of focused libraries, will be discussed with the aid of illustrative examples.     

Identification of Structure–Activity Relationships from Screening a Structurally Compact DNA‐Encoded Chemical Library

Methods for the rapid and inexpensive discovery of hit compounds are essential for pharmaceutical research and DNA‐encoded chemical libraries represent promising tools for this purpose. We here report on the design and synthesis of DAL‐100K, a DNA‐encoded chemical library containing 103 200 structurally compact compounds. Affinity screening experiments and DNA‐sequencing analysis provided ligands with nanomolar affinities to several proteins, including prostate‐specific membrane antigen and tankyrase 1. Correlations of sequence counts with binding affinities and potencies of enzyme inhibition were observed and enabled the identification of structural features critical for activity. These results indicate that libraries of this type represent a useful source of small‐molecule binders for target proteins of pharmaceutical interest and information on structural features important for binding.     

Structure-based de novo drug design using 3D deep generative models

Deep generative models are attracting much attention in the field of de novo molecule design. Compared to traditional methods, deep generative models can be trained in a fully data-driven way with little requirement for expert knowledge. Although many models have been developed to generate 1D and 2D molecular structures, 3D molecule generation is less explored, and the direct design of drug-like molecules inside target binding sites remains challenging. In this work, we introduce DeepLigBuilder, a novel deep learning-based method for de novo drug design that generates 3D molecular structures in the binding sites of target proteins. We first developed Ligand Neural Network (L-Net), a novel graph generative model for the end-to-end design of chemically and conformationally valid 3D molecules with high drug-likeness. Then, we combined L-Net with Monte Carlo tree search to perform structure-based de novo drug design tasks. In the case study of inhibitor design for the main protease of SARS-CoV-2, DeepLigBuilder suggested a list of drug-like compounds with novel chemical structures, high predicted affinity, and similar binding features to those of known inhibitors. The current version of L-Net was trained on drug-like compounds from ChEMBL, which could be easily extended to other molecular datasets with desired properties based on users'' demands and applied in functional molecule generation. Merging deep generative models with atomic-level interaction evaluation, DeepLigBuilder provides a state-of-the-art model for structure-based de novo drug design and lead optimization.

DeepLigBuilder, a novel deep generative model for structure-based de novo drug design, directly generates 3D structures of drug-like compounds in the target binding site.     

Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery

Fragment-based drug discovery (FBDD) is a powerful strategy for the identification of new bioactive molecules. FBDD relies on fragment libraries, generally of modest size, but of high chemical diversity. Although good chemical diversity in FBDD libraries has been achieved in many respects, achieving shape diversity – particularly fragments with three-dimensional (3D) structures – has remained challenging. A recent analysis revealed that >75% of all conventional, organic fragments are predominantly 1D or 2D in shape. However, 3D fragments are desired because molecular shape is one of the most important factors in molecular recognition by a biomolecule. To address this challenge, the use of inert metal complexes, so-called ‘metallofragments’ (mFs), to construct a 3D fragment library is introduced. A modest library of 71 compounds has been prepared with rich shape diversity as gauged by normalized principle moment of inertia (PMI) analysis. PMI analysis shows that these metallofragments occupy an area of fragment space that is unique and highly underrepresented when compared to conventional organic fragment libraries that are comprised of orders of magnitude more molecules. The potential value of this metallofragment library is demonstrated by screening against several different types of proteins, including an antiviral, an antibacterial, and an anticancer target. The suitability of the metallofragments for future hit-to-lead development was validated through the determination of IC₅₀ and thermal shift values for select fragments against several proteins. These findings demonstrate the utility of metallofragment libraries as a means of accessing underutilized 3D fragment space for FBDD against a variety of protein targets.

Fragment-based drug discovery (FBDD) using 3-dimensional metallofragments is a new strategy for the identification of bioactive molecules.     

Design and characterization of a functional library for NMR screening against novel protein targets

In the past few years, NMR has been extensively utilized as a screening tool for drug discovery using various types of compound libraries. The designs of NMR specific chemical libraries that utilize a fragment-based approach based on drug-like characteristics have been previously reported. In this article, a new type of compound library will be described that focuses on aiding in the functional annotation of novel proteins that have been identified from various ongoing genomics efforts. The NMR functional chemical library is comprised of small molecules with known biological activity such as: co-factors, inhibitors, metabolites and substrates. This functional library was developed through an extensive manual effort of mining several databases based on known ligand interactions with protein systems. In order to increase the efficiency of screening the NMR functional library, the compounds are screened as mixtures of 3-4 compounds that avoids the need to deconvolute positive hits by maintaining a unique NMR resonance and function for each compound in the mixture. The functional library has been used in the identification of general biological function of hypothetical proteins identified from the Protein Structure Initiative.