Recent advances on the encoding and selection methods of DNA-encoded chemical library

DNA-encoded chemical library (DEL) has emerged as a powerful and versatile tool for ligand discovery in chemical biology research and in drug discovery. Encoding and selection methods are two of the most important technological aspects of DEL that can dictate the performance and utilities of DELs. In this digest, we have summarized recent advances on the encoding and selection strategies of DEL and also discussed the latest developments on DNA-encoded dynamic library, a new frontier in DEL research.     

Selection of streptavidin binders from a DNA-encoded chemical library

DNA-encoded libraries of small organic molecules facilitate the construction of large, encoded self-assembling chemical libraries for the identification of high-affinity binders to protein targets. We have constructed a library of 477 chemical compounds, coupled to 48mer-oligonucleotides, each containing a unique six-base sequence serving as "bar-code" for the identification of the chemical moiety. The functionality of the library was confirmed by selection and amplification of both high- and low-affinity binding molecules specific to streptavidin.     

Design and synthesis of a novel DNA-encoded chemical library using Diels-Alder cycloadditions

DNA-encoded chemical libraries are increasingly being employed for the identification of binding molecules to protein targets of pharmaceutical relevance. Here, we describe the synthesis and characterization of a DNA-encoded chemical library, consisting of 4000 compounds generated by Diels-Alder cycloaddition reactions. The compounds were encoded with unique DNA fragments which were generated through a stepwise assembly process and serve as amplifiable bar codes for the identification and relative quantification of library members.     

Expanding the DNA-encoded library toolbox: identifying small molecules targeting RNA

DNA-encoded library (DEL) technology is a powerful tool for small molecule identification in drug discovery, yet the reported DEL selection strategies were applied primarily on protein targets in either purified form or in cellular context. To expand the application of this technology, we employed DEL selection on an RNA target HIV-1 TAR (trans-acting responsive region), but found that the majority of signals were resulted from false positive DNA–RNA binding. We thus developed an optimized selection strategy utilizing RNA patches and competitive elution to minimize unwanted DNA binding, followed by k-mer analysis and motif search to differentiate false positive signal. This optimized strategy resulted in a very clean background in a DEL selection against Escherichia coli FMN Riboswitch, and the enriched compounds were determined with double digit nanomolar binding affinity, as well as similar potency in functional FMN competition assay. These results demonstrated the feasibility of small molecule identification against RNA targets using DEL selection. The developed experimental and computational strategy provided a promising opportunity for RNA ligand screening and expanded the application of DEL selection to a much wider context in drug discovery.     

Advances in Lead Generation

Lead Generation represents a critical drug discovery phase where chemical starting points and their respective mechanism of action, quality, and potential liabilities are largely predefined. Recent advances such as DNA-encoded libraries or fragment-, chemical biology-, and virtual screening-based approaches are today as common as traditional High Throughput Screening. Innovations in characterizing lead quality have allowed more informed decision-making by discovery teams. The key challenge today is to individually tailor the right mix of methods for each project to facilitate data integration with the purpose of creating multiple high-quality lead series, ultimately translating to reduced chemistry-related pipeline attrition.     

DNA display II. Genetic manipulation of combinatorial chemistry libraries for small-molecule evolution

Biological in vitro selection techniques, such as RNA aptamer methods and mRNA display, have proven to be powerful approaches for engineering molecules with novel functions. These techniques are based on iterative amplification of biopolymer libraries, interposed by selection for a desired functional property. Rare, promising compounds are enriched over multiple generations of a constantly replicating molecular population, and subsequently identified. The restriction of such methods to DNA, RNA, and polypeptides precludes their use for small-molecule discovery. To overcome this limitation, we have directed the synthesis of combinatorial chemistry libraries with DNA "genes," making possible iterative amplification of a nonbiological molecular species. By differential hybridization during the course of a traditional split-and-pool combinatorial synthesis, the DNA sequence of each gene is read out and translated into a unique small-molecule structure. This "chemical translation" provides practical access to synthetic compound populations 1 million-fold more complex than state-of-the-art combinatorial libraries. We carried out an in vitro selection experiment (iterated chemical translation, selection, and amplification) on a library of 10(6) nonnatural peptides. The library converged over three generations to a high-affinity protein ligand. The ability to genetically encode diverse classes of synthetic transformations enables the in vitro selection and potential evolution of an essentially limitless collection of compound families, opening new avenues to drug discovery, catalyst design, and the development of a materials science "biology."     

High-throughput sequencing for the identification of binding molecules from DNA-encoded chemical libraries

DNA-encoded chemical libraries are large collections of small organic molecules, individually coupled to DNA fragments that serve as amplifiable identification bar codes. The isolation of specific binders requires a quantitative analysis of the distribution of DNA fragments in the library before and after capture on an immobilized target protein of interest. Here, we show how Illumina sequencing can be applied to the analysis of DNA-encoded chemical libraries, yielding over 10 million DNA sequence tags per flow-lane. The technology can be used in a multiplex format, allowing the encoding and subsequent sequencing of multiple selections in the same experiment. The sequence distributions in DNA-encoded chemical library selections were found to be similar to the ones obtained using 454 technology, thus reinforcing the concept that DNA sequencing is an appropriate avenue for the decoding of library selections. The large number of sequences obtained with the Illumina method now enables the study of very large DNA-encoded chemical libraries (>500,000 compounds) and reduces decoding costs.     

Integrating DNA-encoded chemical libraries with virtual combinatorial library screening: Optimizing a PARP10 inhibitor

Two critical steps in drug development are 1) the discovery of molecules that have the desired effects on a target, and 2) the optimization of such molecules into lead compounds with the required potency and pharmacokinetic properties for translation. DNA-encoded chemical libraries (DECLs) can nowadays yield hits with unprecedented ease, and lead-optimization is becoming the limiting step. Here we integrate DECL screening with structure-based computational methods to streamline the development of lead compounds. The presented workflow consists of enumerating a virtual combinatorial library (VCL) derived from a DECL screening hit and using computational binding prediction to identify molecules with enhanced properties relative to the original DECL hit. As proof-of-concept demonstration, we applied this approach to identify an inhibitor of PARP10 that is more potent and druglike than the original DECL screening hit.     

Establishment of the platform for reverse chemical genetics targeting novel protein-protein interactions

In the "drug discovery" era, protein-protein interaction modules are becoming the most exciting group of targets for study. Although combinatorial libraries and active natural products are rapidly and systemically being equipped by both for-profit and not-for-profit organizations, complete drug-screening systems have not been achieved. There is a growing need for the establishment of drug discovery assays for highly effective utilization of the collected small molecules on a large scale. To generate drug-screening systems, we plan to identify novel protein-protein interactions that may participate in human diseases. The interactions have been identified by MS/MS analysis following immunoprecipitation using antibodies prepared from our cDNA projects. The intracellular pathway involving the identified interaction is computationally constructed, which then clarifies its relationship to the candidate disease. The development of reverse chemical genetics based on such information should help us to realize a significant increment in the number of drug discovery assays available for use. In this article, I describe our strategy for drug discovery and then introduce the applicability of fluorescence intensity distribution analysis (FIDA) and the expression-ready constructs called "ORF trap clones" to reverse chemical genetics.     

Navigating large chemical spaces in early-phase drug discovery

The size of actionable chemical spaces is surging, owing to a variety of novel techniques, both computational and experimental. As a consequence, novel molecular matter is now at our fingertips that cannot and should not be neglected in early-phase drug discovery. Huge, combinatorial, make-on-demand chemical spaces with high probability of synthetic success rise exponentially in content, generative machine learning models go hand in hand with synthesis prediction, and DNA-encoded libraries offer new ways of hit structure discovery. These technologies enable to search for new chemical matter in a much broader and deeper manner with less effort and fewer financial resources.These transformational developments require new cheminformatics approaches to make huge chemical spaces searchable and analyzable with low resources, and with as little energy consumption as possible. Substantial progress has been made in the past years with respect to computation as well as organic synthesis. First examples of bioactive compounds resulting from the successful use of these novel technologies demonstrate their power to contribute to tomorrow's drug discovery programs. This article gives a compact overview of the state-of-the-art.     

Aptamers as reagents for high-throughput screening

The identification of new drug candidates from chemical libraries is a major component of discovery research in many pharmaceutical companies. Given the large size of many conventional and combinatorial libraries and the rapid increase in the number of possible therapeutic targets, the speed with which efficient high-throughput screening (HTS) assays can be developed can be a rate-limiting step in the discovery process. We show here that aptamers, nucleic acids that bind other molecules with high affinity, can be used as versatile reagents in competition binding HTS assays to identify and optimize small-molecule ligands to protein targets. To illustrate this application, we have used labeled aptamers to platelet-derived growth factor B-chain and wheat germ agglutinin to screen two sets of potential small-molecule ligands. In both cases, binding affinities of all ligands tested (small molecules and aptamers) were strongly correlated with their inhibitory potencies in functional assays. The major advantages of using aptamers in HTS assays are speed of aptamer identification, high affinity of aptamers for protein targets, relatively large aptamer-protein interaction surfaces, and compatibility with various labeling/detection strategies. Aptamers may be particularly useful in HTS assays with protein targets that have no known binding partners such as orphan receptors. Since aptamers that bind to proteins are often specific and potent antagonists of protein function, the use of aptamers for target validation can be coupled with their subsequent use in HTS.     

Natural product-like synthetic libraries

There is a paucity of chemical matter suitably poised for effective drug development. Improving the quality and efficiency of research early on in the drug discovery process has been a long standing objective for the drug industry and improvements to the accessibility and quality of compound screening decks might have a significant and positive impact. In the absence of specific molecular information that can be modeled and used predicatively we are far from identifying which small molecules are most relevant to emerging biological targets such as protein-protein interactions. Natural products have been historically successful as an entry point for drug discovery and recently screening libraries are being synthesized to emulate natural product like features.     

High affinity targets of protein kinase inhibitors have similar residues at the positions energetically important for binding

Inhibition of protein kinase activity is a focus of intense drug discovery efforts in several therapeutic areas. Major challenges facing the field include understanding of the factors determining the selectivity of kinase inhibitors and the development of compounds with the desired selectivity profile. Here, we report the analysis of sequence variability among high and low affinity targets of eight different small molecule kinase inhibitors (BIRB796, Tarceva, NU6102, Gleevec, SB203580, balanol, H89, PP1). It is observed that all high affinity targets of each inhibitor are found among a relatively small number of kinases, which have similar residues at the specific positions important for binding. The findings are highly statistically significant, and allow one to exclude the majority of kinases in a genome from a list of likely targets for an inhibitor. The findings have implications for the design of novel inhibitors with a desired selectivity profile (e.g. targeted at multiple kinases), the discovery of new targets for kinase inhibitor drugs, comparative analysis of different in vivo models, and the design of "a-la-carte" chemical libraries tailored for individual kinases.     

In silico screening of quadruplex-binding ligands

Recent advances in computational processing power and molecular docking algorithms have facilitated the development of computer-aided methods for the rapid and efficient discovery of G-quadruplex-interacting molecules. In this article, we provide an introductory framework for the methodology of in silico screening for the identification of novel DNA G-quadruplex ligands from chemical libraries. We discuss aspects of model construction, database selection and molecular docking techniques, and highlight representative examples from this field. Finally, we offer a perspective on the potential application of in silico techniques for the discovery of RNA G-quadruplex-binding ligands in the future.     

Exploring the chemogenomic knowledge space with annotated chemical libraries

The recent human genome initiatives have led to the discovery of a multitude of genes that are potentially associated with various pathologic conditions and, thus, have opened new horizons in drug discovery. Simultaneously, annotated chemical libraries have emerged as information-rich databases to integrate biological and chemical data. They can be useful for the discovery of new pharmaceutical leads, the validation of new biotargets and the determination of the structural basis of ligand selectivity within target families. Annotated libraries provide a strong information basis for computational design of target-directed combinatorial libraries, which are a key component of modern drug discovery. Today, the rational design of chemical libraries enhanced with chemogenomics data is a new area of progressive research.     

Lead compounds discovered from libraries: part 2

Many lead compounds with the potential to progress to viable drug candidates have been identified from libraries during the past two years. There are two key strategies most often employed to find leads from libraries: first, high-throughput biological screening of corporate compound collections; and second, synthesis and screening of project-directed libraries (i.e. target-based libraries). Numerous success stories, including the discovery of several clinical candidates, testify to the utility of chemical library collections as proven sources of new leads for drug development.     

Drug discovery in academia

Drug discovery and development is generally done in the commercial rather than the academic realm. Drug discovery involves target discovery and validation, lead identification by high-throughput screening, and lead optimization by medicinal chemistry. Follow-up preclinical evaluation includes analysis in animal models of compound efficacy and pharmacology (ADME: administration, distribution, metabolism, elimination) and studies of toxicology, specificity, and drug interactions. Notwithstanding the high-cost, labor-intensive, and non-hypothesis-driven aspects of drug discovery, the academic setting has a unique and expanding niche in this important area of investigation. For example, academic drug discovery can focus on targets of limited commercial value, such as third-world and rare diseases, and on the development of research reagents such as high-affinity inhibitors for pharmacological "gene knockout" in animal models ("chemical genetics"). This review describes the practical aspects of the preclinical drug discovery process for academic investigators. The discovery of small molecule inhibitors and activators of the cystic fibrosis transmembrane conductance regulator is presented as an example of an academic drug discovery program that has yielded new compounds for physiology research and clinical development. high-throughput screening; drug development; pharmacology; fluorescence; cystic fibrosis transmembrane conductance regulator     

Marcel Faber Roundtable: Is our antibiotic pipeline unproductive because of starvation, constipation or lack of inspiration?

There are few new antibiotics in the pipeline today. The reasons may include starvation at the front of the pipeline due to inadequate sources of suitable compounds to screen coupled with poorly validated discovery methodologies. A successful antibiotic discovery approach in the past, based upon whole cell antibiotic screening of natural products from actinomycetes and fungi, eventually suffered from constipation in the middle of the pipeline due to rediscovery of known compounds, even though low throughput methodology was employed at the front end. The current lack of productivity may be attributed to the poor choice of strategies to address the discovery of new antibiotics. Recent applications of high throughput in vitro screening of individual antibacterial targets to identify lead compounds from combinatorial chemical libraries, traditional chemical libraries, and partially purified natural product extracts has not produced any significant clinical candidates. The solution to the current dilemma may be to return to natural product whole cell screening. For this approach to work in the current millennium, the process needs to be miniaturized to increase the throughput by orders of magnitude over traditional screening, and the rediscovery of known antibiotics needs to be minimized by methods that can be readily monitored and improved over time.     

Small and lethal: searching for new antibacterial compounds with novel modes of action.

The discovery of drugs used to combat infectious diseases is in the process of constant change to address the ever-worsening problem of antibiotic resistance in pathogens and a lack of recent success in discovering new antibacterial drugs. In the past 2 decades, research in both academia and industry has made use of molecular biology, genetics, and comparative genomics, which has led to the development of key technologies for the discovery of novel antibacterial agents. Genome-scale efforts have led to the identification of numerous molecular targets. Chemical diversity from synthetic combinatorial libraries and natural products is being used to screen for new molecules. A wide variety of approaches are being used in the search for novel antibiotics, and these can be categorized as being either biochemically focused or cell based. The over-riding goal of all methods in use today is to discover new chemical matter with novel mechanisms of action against drug-resistant pathogens.