Secondary Sites of the C-type Lectin-Like Fold

C-type lectins are a large superfamily of proteins involved in a multitude of biological processes. In particular, their involvement in immunity and homeostasis has rendered them attractive targets for diverse therapeutic interventions. They share a characteristic C-type lectin-like domain whose adaptability enables them to bind a broad spectrum of ligands beyond the originally defined canonical Ca2+-dependent carbohydrate binding. Together with variable domain architecture and high-level conformational plasticity, this enables C-type lectins to meet diverse functional demands. Secondary sites provide another layer of regulation and are often intricately linked to functional diversity. Located remote from the canonical primary binding site, secondary sites can accommodate ligands with other physicochemical properties and alter protein dynamics, thus enhancing selectivity and enabling fine-tuning of the biological response. In this review, we outline the structural determinants allowing C-type lectins to perform a large variety of tasks and to accommodate the ligands associated with it. Using the six well-characterized Ca2+-dependent and Ca2+-independent C-type lectin receptors DC-SIGN, langerin, MGL, dectin-1, CLEC-2 and NKG2D as examples, we focus on the characteristics of non-canonical interactions and secondary sites and their potential use in drug discovery endeavors.

Druggable Allosteric Sites in β-Propeller Lectins

Carbohydrate‐binding proteins (lectins) are auspicious targets in drug discovery to combat antimicrobial resistance; however, their non‐carbohydrate drug‐like inhibitors are still unavailable. Here, we present a druggable pocket in a β‐propeller lectin BambL from Burkholderia ambifaria as a potential target for allosteric inhibitors. This site was identified employing ¹⁹F NMR fragment screening and a computational pocket prediction algorithm SiteMap. The structure–activity relationship study revealed the most promising fragment with a dissociation constant of 0.3±0.1 mM and a ligand efficiency of 0.3 kcal mol⁻¹ HA⁻¹ that affected the orthosteric site. This effect was substantiated by site‐directed mutagenesis in the orthosteric and secondary pockets. Future drug‐discovery campaigns that aim to develop small molecule inhibitors can benefit from allosteric sites in lectins as a new therapeutic approach against antibiotic‐resistant pathogens.

Medicinal chemistry of the myeloid C-type lectin receptors Mincle, Langerin, and DC-SIGN

In their role as pattern-recognition receptors on cells of the innate immune system, myeloid C-type lectin receptors (CLRs) assume important biological functions related to immunity, homeostasis, and cancer. As such, this family of receptors represents an appealing target for therapeutic interventions for modulating the outcome of many pathological processes, in particular related to infectious diseases. This review summarizes the current state of research into glycomimetic or drug-like small molecule ligands for the CLRs Mincle, Langerin, and DC-SIGN, which have potential therapeutic applications in vaccine research and anti-infective therapy.

A Remote Secondary Binding Pocket Promotes Heteromultivalent Targeting of DC-SIGN

Dendritic cells (DC) are antigen-presenting cells coordinating the interplay of the innate and the adaptive immune response. The endocytic C-type lectin receptors DC-SIGN and Langerin display expression profiles restricted to distinct DC subtypes and have emerged as prime targets for next-generation immunotherapies and anti-infectives. Using heteromultivalent liposomes copresenting mannosides bearing aromatic aglycones with natural glycan ligands, we serendipitously discovered striking cooperativity effects for DC-SIGN⁺ but not for Langerin⁺ cell lines. Mechanistic investigations combining NMR spectroscopy with molecular docking and molecular dynamics simulations led to the identification of a secondary binding pocket for the glycomimetics. This pocket, located remotely of DC-SIGN’s carbohydrate bindings site, can be leveraged by heteromultivalent avidity enhancement. We further present preliminary evidence that the aglycone allosterically activates glycan recognition and thereby contributes to DC-SIGN-specific cell targeting. Our findings have important implications for both translational and basic glycoscience, showcasing heteromultivalent targeting of DCs to improve specificity and supporting potential allosteric regulation of DC-SIGN and CLRs in general.

Application of Fragment-Based Drug Discovery to Versatile Targets

Fragment-based drug discovery (FBDD) is a powerful method to develop potent small-molecule compounds starting from fragments binding weakly to targets. As FBDD exhibits several advantages over high-throughput screening campaigns, it becomes an attractive strategy in target-based drug discovery. Many potent compounds/inhibitors of diverse targets have been developed using this approach. Methods used in fragment screening and understanding fragment-binding modes are critical in FBDD. This review elucidates fragment libraries, methods utilized in fragment identification/confirmation, strategies applied in growing the identified fragments into drug-like lead compounds, and applications of FBDD to different targets. As FBDD can be readily carried out through different biophysical and computer-based methods, it will play more important roles in drug discovery.

Computational and Experimental Druggability Assessment of Human DNA Glycosylases

Due to a polar or even charged binding interface, DNA-binding proteins are considered extraordinarily difficult targets for development of small-molecule ligands and only a handful of proteins have been targeted successfully to date. Recently, however, it has been shown that development of selective and efficient inhibitors of 8-oxoguanine DNA glycosylase is possible. Here, we describe the initial druggability assessment of DNA glycosylases in a computational setting and experimentally investigate several methods to target endonuclease VIII-like 1 (NEIL1) with small-molecule inhibitors. We find that DNA glycosylases exhibit good predicted druggability in both DNA-bound and -unbound states. Furthermore, we find catalytic sites to be highly flexible, allowing for a range of interactions and binding partners. One flexible catalytic site was rationalized for NEIL1 and further investigated experimentally using both a biochemical assay in the presence of DNA and a thermal shift assay in the absence of DNA.

Elucidating the druggability of the human proteome with eFindSite

Identifying the viability of protein targets is one of the preliminary steps of drug discovery. Determining the ability of a protein to bind drugs in order to modulate its function, termed the druggability, requires a non-trivial amount of time and resources. Inability to properly measure druggability has accounted for a significant portion of failures in drug discovery. This problem is only further exacerbated by the large sample space of proteins involved in human diseases. With these barriers, the druggability space within the human proteome remains unexplored and has made it difficult to develop drugs for numerous diseases. Hence, we present a new feature developed in eFindSite that employs supervised machine learning to predict the druggability of a given protein. Benchmarking calculations against the Non-Redundant data set of Druggable and Less Druggable binding sites demonstrate that an AUC for druggability prediction with eFindSite is as high as 0.88. With eFindSite, we elucidated the human druggability space to be 10,191 proteins. Considering the disease space from the Open Targets Platform and excluding already known targets from the predicted data set reveal 2731 potentially novel therapeutic targets. eFindSite is freely available as a stand-alone software at https://github.com/michal-brylinski/efindsite .

CellFy: A Cell-Based Fragment Screen against C-Type Lectins

Fragment-based drug discovery is a powerful complement to conventional high-throughput screening, especially for difficult targets. Screening low-molecular-weight fragments usually requires highly sensitive biophysical methods, because of the generally low affinity of the identified ligands. Here, we developed a cell-based fragment screening assay (cellFy) that allows sensitive identification of fragment hits in a physiologically more relevant environment, in contrast to isolated target screenings in solution. For this, a fluorescently labeled multivalent reporter was employed, enabling direct measurement of displacement by low-molecular-weight fragments without requiring enzymatic reactions or receptor activation. We applied this technique to identify hits against two challenging targets of the C-type lectin receptor (CLR) family: Dendritic Cell-Specific Intercellular adhesion molecule-3-Grabbing Nonintegrin (DC-SIGN) and Langerin. Both receptors are involved in pathogen recognition and initiation of an immune response, which renders them attractive targets for immune modulation. Because of their shallow and hydrophilic primary binding site, hit identification for CLRs is challenging and druglike ligands for CLRs are sparse. Screening of a fragment library followed by hit validation identified several promising candidates for further fragment evolution for DC-SIGN. In addition, a multiplexed assay format was developed for simultaneous screening against multiple CLRs, allowing a selectivity counterscreening. Overall, this sensitive cell-based fragment screening assay provides a powerful tool for rapid identification of bioactive fragments, even for difficult targets.

Quantitative metrics for drug-target ligandability

Ligandability is a prerequisite for druggability and is a much easier concept to understand, model and predict because it does not depend on the complex pharmacodynamic and pharmacokinetic mechanisms in the human body. In this review, we consider a metric for quantifying ligandability from experimental data. We discuss ligandability in terms of the balance between effort and reward. The metric is evaluated for a standard set of well-studied drug targets - some traditionally considered to be ligandable and some regarded as difficult. We suggest that this metric should be used to systematically improve computational predictions of ligandability, which can then be applied to novel drug targets to predict their tractability.

Identification of Multiple Druggable Secondary Sites by Fragment Screening against DC-SIGN

DC-SIGN is a cell-surface receptor for several pathogenic threats, such as HIV, Ebola virus, or Mycobacterium tuberculosis. Multiple attempts to develop inhibitors of the underlying carbohydrate-protein interactions have been undertaken in the past fifteen years. Still, drug-like DC-SIGN ligands are sparse, which is most likely due to its hydrophilic, solvent-exposed carbohydrate-binding site. Herein, we report on a parallel fragment screening against DC-SIGN applying SPR and a reporter displacement assay, which complements previous screenings using ¹⁹ F NMR spectroscopy and chemical fragment microarrays. Hit validation by SPR and ¹ H-¹⁵ N HSQC NMR spectroscopy revealed that although no fragment bound in the primary carbohydrate site, five secondary sites are available to harbor drug-like molecules. Building on key interactions of the reported fragment hits, these pockets will be targeted in future approaches to accelerate the development of DC-SIGN inhibitors.

Global vision of druggability issues: applications and perspectives

During the preliminary stage of a drug discovery project, the lack of druggability information and poor target selection are the main causes of frequent failures. Elaborating on accurate computational druggability prediction methods is a requirement for prioritizing target selection, designing new drugs and avoiding side effects. In this review, we describe a survey of recently reported druggability prediction methods mainly based on networks, statistical pocket druggability predictions and virtual screening. An application for a frequent mutation of p53 tumor suppressor is presented, illustrating the complementarity of druggability prediction approaches, the remaining challenges and potential new drug development perspectives.