Identification of protein binding partners of small molecules using label-free methods

Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions

With the emergence of next-generation nucleotide sequencing and mass spectrometry-based proteomics and metabolomics tools, we have comprehensive and scalable methods to analyze the genes, transcripts, proteins, and metabolites of a multitude of biological systems. Despite the fascinating new molecular insights at the genome, transcriptome, proteome and metabolome scale, we are still far from fully understanding cellular organization, cell cycles and biology at the molecular level. Significant advances in sensitivity and depth for both sequencing as well as mass spectrometry-based methods allow the analysis at the single cell and single molecule level. At the same time, new tools are emerging that enable the investigation of molecular interactions throughout the central dogma of molecular biology. In this review, we provide an overview of established and recently developed mass spectrometry-based tools to probe metabolite-protein interactions-from individual interaction pairs to interactions at the proteome-metabolome scale.

Sinomenine ameliorates collagen-induced arthritis in mice by targeting GBP5 and regulating the P2X7 receptor to suppress NLRP3-related signaling pathways

Sinomenine (SIN) is an isoquinoline alkaloid isolated from Sinomenii Caulis, a traditional Chinese medicine used to treat rheumatoid arthritis (RA). Clinical trials have shown that SIN has comparable efficacy to methotrexate in treating patients with RA but with fewer adverse effects. In this study, we explored the anti-inflammatory effects and therapeutic targets of SIN in LPS-induced RAW264.7 cells and in collagen-induced arthritis (CIA) mice. LPS-induced RAW264.7 cells were pretreated with SIN (160, 320, 640 µM); and CIA mice were administered SIN (25, 50 and 100 mg·kg-1·d-1, i.p.) for 30 days. We first conducted a solvent-induced protein precipitation (SIP) assay in LPS-stimulated RAW264.7 cells and found positive evidence for the direct binding of SIN to guanylate-binding protein 5 (GBP5), which was supported by molecular simulation docking, proteomics, and binding affinity assays (KD = 3.486 µM). More importantly, SIN treatment markedly decreased the expression levels of proteins involved in the GBP5/P2X7R-NLRP3 pathways in both LPS-induced RAW264.7 cells and the paw tissue of CIA mice. Moreover, the levels of IL-1β, IL-18, IL-6, and TNF-α in both the supernatant of inflammatory cells and the serum of CIA mice were significantly reduced. This study illustrates a novel anti-inflammatory mechanism of SIN; SIN suppresses the activity of NLRP3-related pathways by competitively binding GBP5 and downregulating P2X7R protein expression, which ultimately contributes to the reduction of IL-1β and IL-18 production. The binding specificity of SIN to GBP5 and its inhibitory effect on GBP5 activity suggest that SIN has great potential as a specific GBP5 antagonist.

Mutant p53 Depletion by Novel Inhibitors for HSP40/J-Domain Proteins Derived from the Natural Compound Plumbagin

Simple Summary

The tumor suppressor p53 is frequently mutated in human cancer. Accumulation of missense mutant p53 (mutp53) in tumors is crucial for malignant progression, and cancers are often addicted to oncogenic mutp53. However, strategies to deplete mutp53 have not yet been established. Recent studies have shown that misfolded or conformational mutp53 is stabilized by DNAJA1, a member of HSP40, also known as J-domain proteins (JDPs). However, no selective DNAJA1 inhibitor is clinically available. Through a molecular docking study, we identified a potential DNAJA1 inhibitor, called PLTFBH, derived from the natural compound plumbagin, as a compound that bound to and reduced protein levels of DNAJA1 and several other HSP40/JDPs. PLTFBH reduced the levels of conformational mutp53 and inhibited cancer cell migration in a manner dependent on DNAJA1 and mutp53.

Abstract

Accumulation of missense mutant p53 (mutp53) in cancers promotes malignant progression. DNAJA1, a member of HSP40 (also known as J-domain proteins: JDPs), is shown to prevent misfolded or conformational mutp53 from proteasomal degradation. Given frequent addiction of cancers to oncogenic mutp53, depleting mutp53 by DNAJA1 inhibition is a promising approach for cancer therapy. However, there is no clinically available inhibitor for DNAJA1. Our in silico molecular docking study with a natural compound-derived small molecule library identified a plumbagin derivative, PLIHZ (plumbagin–isoniazid analog), as a potential compound binding to the J domain of DNAJA1. PLIHZ efficiently reduced the levels of DNAJA1 and several conformational mutp53 with minimal impact on DNA contact mutp53 and wild-type p53 (wtp53). An analog, called PLTFBH, which showed a similar activity to PLIHZ in reducing DNAJA1 and mutp53 levels, inhibited migration of cancer cells specifically carrying conformational mutp53, but not DNA contact mutp53, p53 null, and wtp53, which was attenuated by depletion of DNAJA1 or mutp53. Moreover, PLTFBH reduced levels of multiple other HSP40/JDPs with tyrosine 7 (Y7) and/or tyrosine 8 (Y8) but failed to deplete DNAJA1 mutants with alanine substitution of these amino acids. Our study suggests PLTFBH as a potential inhibitor for multiple HSP40/JDPs.

Chip-DSF: A rapid screening strategy for drug protein targets

Identification of the drug target of lead compounds is an important means for rapid and efficient drug discovery. Protein chips are a high-throughput protein function analysis technology that has been widely used in screening drug protein targets in recent years. However, the verification of the results after high-throughput protein chip screening is still cumbersome. Based on our mature protein chip preparation platform, we prepared a protein chip containing 150 important high-frequency protein targets and used antibodies to prove the availability of the protein chip. To improve the accuracy of target screening, we combined the label-free differential scanning fluorimetry (DSF) with the protein chip, proposing the Chip-DSF strategy. Subsequently, we tested the method with small molecular ginsenoside-Rg2 (Rg2). The Chip-DSF strategy was used to successfully screen the potential target protein KRAS(G12C) of Rg2. Consistently, we found that Rg2 could inhibit NCI-H23 cell proliferation by inducing cell cycle arrest. Also, we found that Rg2 could reduce the amount of KRAS protein and inhibit the phosphorylation of KRAS downstream key signaling protein ERK1, RPS6, and P70S6K in NCI-H23 cells. Collectively, our Chip-DSF strategy could achieve rapid target verification which improved the accuracy and efficiency of target screening of protein chips.

Lessons in Organic Fluorescent Probe Discovery

Fluorescent probes have gained profound use in biotechnology, drug discovery, medical diagnostics, molecular and cell biology. The development of methods for the translation of fluorophores into fluorescent probes continues to be a robust field for medicinal chemists and chemical biologists, alike. Access to new experimental designs has enabled molecular diversification and led to the identification of new approaches to probe discovery. This review provides a synopsis of the recent lessons in modern fluorescent probe discovery.

Morphological profiling of small molecules

Profiling approaches such as gene expression or proteome profiling generate small-molecule bioactivity profiles that describe a perturbed cellular state in a rather unbiased manner and have become indispensable tools in the evaluation of bioactive small molecules. Automated imaging and image analysis can record morphological alterations that are induced by small molecules through the detection of hundreds of morphological features in high-throughput experiments. Thus, morphological profiling has gained growing attention in academia and the pharmaceutical industry as it enables detection of bioactivity in compound collections in a broader biological context in the early stages of compound development and the drug-discovery process. Profiling may be used successfully to predict mode of action or targets of unexplored compounds and to uncover unanticipated activity for already characterized small molecules. Here, we review the reported approaches to morphological profiling and the kind of bioactivity that can be detected so far and, thus, predicted.

The Natural Compound Oblongifolin C Exhibits Anticancer Activity by Inhibiting HSPA8 and Cathepsin B In Vitro

PPAPs (Polycyclic polyprenylated acylphloroglucinols) are a class of compounds with diverse bioactivities, including anticancer effects. Oblongifolin C (OC) is a PPAP isolated from the plant of Garcinia yunnanensis Hu. We previously discovered that OC induces apoptosis, inhibits autophagic flux, and attenuates metastasis in cancer cells. However, the protein targets and the detailed mechanism of action of OC remain unclear. To identify protein targets of OC, a non-labeled protein fishing assay was performed, and it was found that OC may interact with several proteins, including the heat shock 70 kDa protein 8 (HSPA8). Expanding on our previous studies on protein cathepsin B, this current study applied Surface Plasmon Resonance (SPR) and Isothermal Titration Calorimetry (ITC) to confirm the potential binding affinity between OC and two protein targets. This study highlights the inhibitory effect of OC on HSPA8 in cancer cells under heat shock stress, by specifically inhibiting the translocation of HSPA8. OC also enhanced the interaction between HSPA8, HSP90, and p53, upregulated the expression of p53 and significantly promoted apoptosis in cisplatin-treated cells. Additionally, a flow cytometry assay detected that OC sped up the apoptosis rate in HSPA8 knockdown A549 cells, while overexpression of HSPA8 delayed the OC-induced apoptosis rate. In summary, our results reveal that OC potentially interacts with HSPA8 and cathepsin B and inhibits HSPA8 nuclear translocation and cathepsin B activities, altogether suggesting the potential of OC to be developed as an anticancer drug.

Comparative Analysis of Mass-Spectrometry-Based Proteomic Methods for Protein Target Discovery Using a One-Pot Approach

Recently, several mass-spectrometry- and protein-denaturation-based proteomic methods have been developed to facilitate protein target discovery efforts in drug mode-of-action studies. These methods, which include the stability of proteins from rates of oxidation (SPROX), pulse proteolysis (PP), chemical denaturation and protein precipitation (CPP), and thermal proteome profiling (TPP) techniques, have been used in an increasing number of applications in recent years. However, while the advantages and disadvantages to using these different techniques have been reviewed, the analytical characteristics of these methods have not been directly compared. Reported here is such a direct comparison using the well-studied immunosuppressive drug, cyclosporine A (CsA), and the proteins in a yeast cell lysate. Also described is a one-pot strategy that can be utilized with each technique to streamline data acquisition and analysis. We find that there are benefits to utilizing all four strategies for protein target discovery including increased proteomic coverage and reduced false positive rates that approach 0%. Moreover, the one-pot strategy described here makes such an experiment feasible, because of the 10-fold reduction in reagent costs and instrument time it affords.

Screening Strategies and Methods for Better Off-Target Liability Prediction and Identification of Small-Molecule Pharmaceuticals

Pharmaceutical discovery and development is a long and expensive process that, unfortunately, still results in a low success rate, with drug safety continuing to be a major impedance. Improved safety screening strategies and methods are needed to more effectively fill this critical gap. Recent advances in informatics are now making it possible to manage bigger data sets and integrate multiple sources of screening data in a manner that can potentially improve the selection of higher-quality drug candidates. Integrated screening paradigms have become the norm in Pharma, both in discovery screening and in the identification of off-target toxicity mechanisms during later-stage development. Furthermore, advances in computational methods are making in silico screens more relevant and suggest that they may represent a feasible option for augmenting the current screening paradigm. This paper outlines several fundamental methods of the current drug screening processes across Pharma and emerging techniques/technologies that promise to improve molecule selection. In addition, the authors discuss integrated screening strategies and provide examples of advanced screening paradigms.

Polypharmacology by Design: A Medicinal Chemist's Perspective on Multitargeting Compounds

Multitargeting compounds comprising activity on more than a single biological target have gained remarkable relevance in drug discovery owing to the complexity of multifactorial diseases such as cancer, inflammation, or the metabolic syndrome. Polypharmacological drug profiles can produce additive or synergistic effects while reducing side effects and significantly contribute to the high therapeutic success of indispensable drugs such as aspirin. While their identification has long been the result of serendipity, medicinal chemistry now tends to design polypharmacology. Modern in vitro pharmacological methods and chemical probes allow a systematic search for rational target combinations and recent innovations in computational technologies, crystallography, or fragment-based design equip multitarget compound development with valuable tools. In this Perspective, we analyze the relevance of multiple ligands in drug discovery and the versatile toolbox to design polypharmacology. We conclude that despite some characteristic challenges remaining unresolved, designed polypharmacology holds enormous potential to secure future therapeutic innovation.

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

Opportunities and challenges in phenotypic drug discovery: an industry perspective

Phenotypic drug discovery (PDD) approaches do not rely on knowledge of the identity of a specific drug target or a hypothesis about its role in disease, in contrast to the target-based strategies that have been widely used in the pharmaceutical industry in the past three decades. However, in recent years, there has been a resurgence in interest in PDD approaches based on their potential to address the incompletely understood complexity of diseases and their promise of delivering first-in-class drugs, as well as major advances in the tools for cell-based phenotypic screening. Nevertheless, PDD approaches also have considerable challenges, such as hit validation and target deconvolution. This article focuses on the lessons learned by researchers engaged in PDD in the pharmaceutical industry and considers the impact of 'omics' knowledge in defining a cellular disease phenotype in the era of precision medicine, introducing the concept of a chain of translatability. We particularly aim to identify features and areas in which PDD can best deliver value to drug discovery portfolios and can contribute to the identification and the development of novel medicines, and to illustrate the challenges and uncertainties that are associated with PDD in order to help set realistic expectations with regard to its benefits and costs.