RESUMO

Genomic technologies have led to massive gains in our understanding of human gene function and disease relevance. Chemical biologists are a primary beneficiary of this information, which can guide the prioritization of proteins for chemical probe and drug development. The vast functional and structural diversity of disease-relevant proteins, however, presents challenges for conventional small molecule screening libraries and assay development that in turn raise questions about the broader "druggability" of the human proteome. Here, we posit that activity-based protein profiling (ABPP), by generating global maps of small molecule-protein interactions in native biological systems, is well positioned to address major obstacles in human biology-guided chemical probe and drug discovery. We will support this viewpoint with case studies highlighting a range of small molecule mechanisms illuminated by ABPP that include the disruption and stabilization of biomolecular (protein-protein/nucleic acid) interactions and underscore allostery as a rich source of chemical tools for historically "undruggable" protein classes.

Assuntos

Assuntos

RESUMO

Quantifying small molecule uptake across a biological membrane of a target cell is crucial for the development of efficacious and selective drugs. However, current methods to obtaining such data are not trivial. Herein, we present an accessible, higher-throughput (20 minutes), 1H NMR spectroscopy assay, which enables the quantification of small molecule phospholipid passive membrane permeation and membrane adhesion parameters.

Assuntos

RESUMO

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown the hit lists can become dominated by rare artifacts that cheat our scoring functions. Here, we investigate rescoring top-ranked docked molecules with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation as cross-filters. In retrospective studies, this approach deprioritized high-ranking nonbinders for nine targets while leaving true ligands relatively unaffected. We tested the method prospectively against hits from docking against AmpC ß-lactamase. We prioritized 128 high-ranking molecules for synthesis and testing, a mixture of 39 molecules flagged as likely cheaters and 89 that were plausible inhibitors. None of the predicted cheating compounds inhibited AmpC detectably, while 57% of the 89 plausible compounds did so. As our libraries continue to grow, deprioritizing docking artifacts by rescoring with orthogonal methods may find wide use.

Assuntos

RESUMO

RNA molecules, similar to proteins, fold into complex structures to confer diverse functions in cells. The intertwining of functions with RNA structures offers a new therapeutic opportunity for small molecules to bind and manipulate disease-relevant RNA pathways, thus creating a therapeutic realm of RNA-binding small molecules. The ongoing interest in RNA targeting and subsequent screening campaigns have led to the identification of numerous compounds that can regulate RNAs from splicing, degradation to malfunctions, with therapeutic benefits for a variety of diseases. Moreover, along with the rise of RNA-based therapeutics, RNA-binding small molecules have expanded their application to the modification, regulation, and delivery of RNA drugs, leading to the burgeoning interest in this field. This Perspective overviews the emerging roles of RNA-binding small molecules in drug discovery and delivery, covering aspects from their action fundamentals to therapeutic applications, which may inspire researchers to advance the field.

Assuntos

RESUMO

Accurate in silico predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3-0.4 kcal/mol) and the average replicate spread by over 25% (0.2-0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.

Assuntos

RESUMO

RNA small molecule interactions play a crucial role in drug discovery and inhibitor design. Identifying RNA small molecule binding nucleotides is essential and requires methods that exhibit a high predictive ability to facilitate drug discovery and inhibitor design. Existing methods can predict the binding nucleotides of simple RNA structures, but it is hard to predict binding nucleotides in complex RNA structures with junctions. To address this limitation, we developed a new deep learning model based on spatial correlation, ZHmolReSTasite, which can accurately predict binding nucleotides of small and large RNA with junctions. We utilize RNA surface topography to consider the spatial correlation, characterizing nucleotides from sequence and tertiary structures to learn a high-level representation. Our method outperforms existing methods for benchmark test sets composed of simple RNA structures, achieving precision values of 72.9% on TE18 and 76.7% on RB9 test sets. For a challenging test set composed of RNA structures with junctions, our method outperforms the second best method by 11.6% in precision. Moreover, ZHmolReSTasite demonstrates robustness regarding the predicted RNA structures. In summary, ZHmolReSTasite successfully incorporates spatial correlation, outperforms previous methods on small and large RNA structures using RNA surface topography, and can provide valuable insights into RNA small molecule prediction and accelerate RNA inhibitor design.

Assuntos

RESUMO

AIMS: Nonalcoholic steatohepatitis (NASH) is the severe subtype of nonalcoholic fatty diseases (NAFLD) with few options for treatment. Patients with NASH exhibit partial responses to the current therapeutics and adverse effects. Identification of the binding proteins for the drugs is essential to understanding the mechanism and adverse effects of the drugs and fuels the discovery of potent and safe drugs. This paper aims to critically discuss recent advances in covalent and noncovalent approaches for identifying binding proteins that mediate NASH progression, along with an in-depth analysis of the mechanisms by which these targets regulate NASH. MATERIALS AND METHODS: A literature search was conducted to identify the relevant studies in the database of PubMed and the American Chemical Society. The search covered articles published from January 1990 to July 2024, using the search terms with keywords such as NASH, benzophenone, diazirine, photo-affinity labeling, thermal protein profiling, CETSA, target identification. KEY FINDINGS: The covalent approaches utilize drugs modified with diazirine and benzophenone to covalently crosslink with the target proteins, which facilitates the purification and identification of target proteins. In addition, they map the binding sites in the target proteins. By contrast, noncovalent approaches identify the binding targets of unmodified drugs in the intact cell proteome. The advantages and limitations of both approaches have been compared, along with a comprehensive analysis of recent innovations that further enhance the efficiency and specificity. SIGNIFICANCE: The analyses of the applicability of these approaches provide novel tools to delineate NASH pathogenesis and promote drug discovery.

Assuntos

RESUMO

Targeted protein degradation through the lysosomal pathway has attracted increasing attention and expanded the scope of degradable proteins. However, the endogenous lysosomal degradation strategies are mainly based on antibodies or nanobodies. Effective small molecule lysosomal degraders are still rather rare. Herein, a new lysosomal degradation approach, termed peptide-mediated small molecule lysosome-targeting chimeras (PSMLTACs), was developed by the incorporation of small molecule ligands with a lysosome-sorting NPGY motif containing the cell-penetrating peptide. PSMLTACs were successfully applied to degrade both membrane and intracellular targets. In particular, the PSMLTAC strategy demonstrated higher degradation efficiency on membrane target PD-L1 and intracellular target PDEδ than corresponding PROTAC degraders. Taken together, this proof-of-concept provides a convenient and effective strategy for targeted protein degradation.

Assuntos

RESUMO

Type I melanoma antigen (MAGE) family members are detected in numerous tumor types, and expression is correlated with poor prognosis, high tumor grade, and increased metastasis. Type I MAGE proteins are typically restricted to reproductive tissues, but expression can recur during tumorigenesis. Several biochemical functions have been elucidated for them, and notably, MAGEs regulate proteostasis by serving as substrate recognition modules for E3 ligase complexes. The repertoire of E3 ligase complexes that can be hijacked for targeted protein degradation continues to expand, and MAGE-E3 complexes are an especially attractive platform given their cancer-selective expression. Additionally, type I MAGE-derived peptides are presented on cancer cell surfaces, so targeted MAGE degradation may increase antigen presentation and improve immunotherapy outcomes. Motivated by these applications, we developed novel, small-molecule ligands for MAGE-A3, a type I MAGE that is widely expressed in tumors and associates with TRIM28, a RING E3 ligase. Chemical matter was identified through DNA-encoded library (DEL) screening, and hit compounds were validated for in vitro binding to MAGE-A3. We obtained a cocrystal structure with a DEL analog and hypothesize that the small molecule binds at a dimer interface. We utilized this ligand to develop PROTAC molecules that induce MAGE-A3 degradation through VHL recruitment and inhibit the proliferation of MAGE-A3 positive cell lines. These ligands and degraders may serve as valuable probes for investigating MAGE-A3 biology and as foundations for the ongoing development of tumor-specific PROTACs.

Assuntos

RESUMO

We present a computational scheme for predicting the ligands that bind to a pocket of a known structure. It is based on the generation of a general abstract representation of the molecules, which is invariant to rotations, translations, and permutations of atoms, and has some degree of isometry with the space of conformations. We use these representations to train a nondeep machine learning algorithm to classify the binding between pockets and molecule pairs and show that this approach has a better generalization capability than existing methods.

Assuntos

RESUMO

Interactions between proteins and small organic compounds play a crucial role in regulating protein functions. These interactions can modulate various aspects of protein behavior, including enzymatic activity, signaling cascades, and structural stability. By binding to specific sites on proteins, small organic compounds can induce conformational changes, alter protein-protein interactions, or directly affect catalytic activity. Therefore, many drugs available on the market today are small molecules (72% of all approved drugs in the last 5 years). Proteins are composed of one or more domains: evolutionary units that convey function or fitness either singly or in concert with others. Understanding which domain(s) of the target protein binds to a drug can lead to additional opportunities for discovering novel targets. The evolutionary classification of protein domains (ECOD) classifies domains into an evolutionary hierarchy that focuses on distant homology. Previously, no structure-based protein domain classification existed that included information about both the interaction between small molecules or drugs and the structural domains of a target protein. This data is especially important for multidomain proteins and large complexes. Here, we present the DrugDomain database that reports the interaction between ECOD of human target proteins and DrugBank molecules and drugs. The pilot version of DrugDomain describes the interaction of 5160 DrugBank molecules associated with 2573 human proteins. It describes domains for all experimentally determined structures of these proteins and incorporates AlphaFold models when such structures are unavailable. The DrugDomain database is available online: http://prodata.swmed.edu/DrugDomain/.

Assuntos

RESUMO

As organoids and organ-on-chip (OoC) systems move toward preclinical and clinical applications, there is an increased need for method validation. Using a liquid chromatography-mass spectrometry (LC-MS)-based approach, we developed a method for measuring small-molecule drugs and metabolites in the cell medium directly sampled from liver organoids/OoC systems. The LC-MS setup was coupled to an automatic filtration and filter flush system with online solid-phase extraction (SPE), allowing for robust and automated sample cleanup/analysis. For the matrix, rich in, e.g., protein, salts, and amino acids, no preinjection sample preparation steps (protein precipitation, SPE, etc.) were necessary. The approach was demonstrated with tolbutamide and its liver metabolite, 4-hydroxytolbutamide (4HT). The method was validated for analysis of cell media of human stem cell-derived liver organoids cultured in static conditions and on a microfluidic platform according to Food and Drug Administration (FDA) guidelines with regards to selectivity, matrix effects, accuracy, precision, etc. The system allows for hundreds of injections without replacing chromatography hardware. In summary, drug/metabolite analysis of organoids/OoCs can be performed robustly with minimal sample preparation.

Assuntos

RESUMO

Hydrogen-deuterium eXchange mass spectrometry (HDX-MS) is increasingly used in drug development to locate binding sites and to identify allosteric effects in drug/target interactions. However, the potential of this technique to quantitatively analyze drug candidate libraries remains largely unexplored. Here, a collection of 13 WDR5-targeting small molecules with surface plasmon resonance (SPR) dissociation coefficients (KD) ranging from 20 nM to ∼116 µM were characterized using differential HDX-MS (ΔHDX-MS). Conventional qualitative analysis of the ΔHDX-MS data set revealed the binding interfaces for all compounds and allosteric effects where present. We then demonstrated that ΔHDX-MS signal-to-noise (S/N) not only can rank library-relative affinity but also can accurately predict KD from a calibration curve constructed from high-quality SPR data. Three methods for S/N calculation are explored, each suitable for libraries with different characteristics. Our results demonstrate the potential for ΔHDX-MS use in drug candidate library affinity validation and/or determination while simultaneously characterizing structure.

Assuntos

RESUMO

Recent advances in chemical proteomics have focused on developing chemical probes that react with nucleophilic amino acid residues. Although histidine is an attractive candidate due to its importance in enzymatic catalysis, metal binding and protein-protein interaction, its moderate nucleophilicity poses challenges. Its modification is frequently influenced by cysteine and lysine, which results in poor selectivity and narrow proteome coverage. Here we report a singlet oxygen and chemical probe relay labelling method that achieves high selectivity towards histidine. Libraries of small-molecule photosensitizers and chemical probes were screened to optimize histidine labelling, enabling histidine profiling in live cells with around 7,200 unique sites. Using NMR spectroscopy and X-ray crystallography, we characterized the reaction mechanism and the structures of the resulting products. We then applied this method to discover unannotated histidine sites key to enzymatic activity and metal binding in select metalloproteins. This method also revealed the accessibility change of histidine mediated by protein-protein interaction that influences select protein subcellular localization, underscoring its capability in discovering functional histidines.

Assuntos

RESUMO

Ligand binding hotspots are regions of protein surfaces that form particularly favourable interactions with small molecule pharmacophores. Targeting interactions with these hotspots maximises the efficiency of ligand binding. Existing methods are capable of identifying hotspots but often lack assays to quantify ligand binding and direct elaboration at these sites. Herein, we describe a fragment-based competitive 19F Ligand Based NMR (LB-NMR) screening platform that enables routine, quantitative ligand profiling focused at ligand-binding hotspots. As a proof of concept, the method was applied to 4'-phosphopantetheine adenylyltransferase (PPAT) from Mycobacterium abscessus (Mabs). X-ray crystallographic characterisation of the hits from a 960-member fragment screen identified three ligand-binding hotspots across the PPAT active site. From the fragment hits a collection of 19F reporter candidates were designed and synthesised. By rigorous prioritisation and use of optimisation workflows, a single 19F reporter molecule was generated for each hotspot. Profiling the binding of a set of structurally characterised ligands by competitive 19F LB-NMR with this suite of 19F reporters recapitulated the binding affinity and site ID assignments made by ITC and X-ray crystallography. This quantitative mapping of ligand binding events at hotspot level resolution establishes the utility of the fragment-based competitive 19F LB-NMR screening platform for hotspot-directed ligand profiling.

Assuntos

RESUMO

Comprehensive characterization of small-molecule degraders, including binary and ternary complex formation and degradation efficiency, is critical for bifunctional ligand development and understanding structure-activity relationships. Here, we present a protocol for the biochemical and cellular profiling of small-molecule degraders based on CoraFluor time-resolved fluorescence resonance energy transfer (TR-FRET) technology. We describe steps for labeling antibodies and proteins, tracer saturation binding, binary target engagement, ternary complex profiling, and off-rate determination. We then detail procedures for the quantification of endogenous and GFP fusion proteins in cell lysates. For complete details on the use and execution of this protocol, please refer to Ichikawa et al.1.

Assuntos

RESUMO

We present a novel and interpretable approach for assessing small-molecule binding using context explanation networks. Given the specific structure of a protein/ligand complex, our CENsible scoring function uses a deep convolutional neural network to predict the contributions of precalculated terms to the overall binding affinity. We show that CENsible can effectively distinguish active vs inactive compounds for many systems. Its primary benefit over related machine-learning scoring functions, however, is that it retains interpretability, allowing researchers to identify the contribution of each precalculated term to the final affinity prediction, with implications for subsequent lead optimization.

Assuntos

RESUMO

ß-Glucocerebrosidase (GBA/GCase) mutations leading to misfolded protein cause Gaucher's disease and are a major genetic risk factor for Parkinson's disease and dementia with Lewy bodies. The identification of small molecule pharmacological chaperones that can stabilize the misfolded protein and increase delivery of degradation-prone mutant GCase to the lysosome is a strategy under active investigation. Here, we describe the first use of fragment-based drug discovery (FBDD) to identify pharmacological chaperones of GCase. The fragment hits were identified by using X-ray crystallography and biophysical techniques. This work led to the discovery of a series of compounds that bind GCase with nM potency and positively modulate GCase activity in cells.

Assuntos

RESUMO

The determination of kon and koff values through kinetic analysis is crucial for understanding the intricacies of aptamer-target binding interactions. By employing kinetic ITC, we systematically analyzed a range of ITC data of various aptamers. Upon plotting their kon and koff values as a function of their Kd values, a notable trend emerged. Across a range of Kd values spanning from 28 nM to 864 µM, the kon value decreased from 2×105 M-1 s-1 to 96 M-1 s-1, whereas the koff value increased from 1.03×10-3 s-1 to 0.012 s-1. Thus, both kon and koff contributed to the change of Kd in the same direction, although the range of kon change was larger. Since experiments are often run at close to the Kd value, this concentration effect also played an important role in the observed binding kinetics. The effect of these kinetic parameters on two common sensing mechanisms, including aptamer beacons and strand-displacement assays, are discussed. This work has provided the kinetic values of small molecule binding aptamers and offered insights into aptamer-based biosensors.

Assuntos