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Molecular glues are an intriguing therapeutic modality that harness small-molecules to induce interactions between proteins that typically do not interact. However, such molecules are rare and have been discovered fortuitously, thus limiting their potential as a general strategy for therapeutic intervention. We postulated that natural products bearing one or more electrophilic sites may be an unexplored source of new molecular glues, potentially acting through multi-covalent attachment. Using chemoproteomic platforms, we show that members of the manumycin family of polyketides, which bear multiple potentially reactive sites, target C374 of the putative E3 ligase UBR7 in breast cancer cells and engage in molecular glue interactions with the neo-substrate tumor-suppressor TP53, leading to p53 transcriptional activation and cell death. Our results reveal a novel anti-cancer mechanism of this natural product family and highlight the potential for combining chemoproteomics and multi-covalent natural products for the discovery of new molecular glues.

The protein–protein interaction assay is a key technology in various fields, being applicable in drug screening as well as in diagnosis and inspection, wherein the stability of assays is important. In a previous study, we developed a unique protein–protein interaction assay “FlimPIA” based on the functional complementation of mutant firefly luciferases (Fluc). The catalytic step of Fluc was divided into two half steps: D-luciferin was adenylated in the first step, while adenylated luciferin was oxidized in the second step. We constructed two mutants of Fluc from Photinus pyralis (Ppy); one mutant named Donor is defective in the second half reaction, while the other mutant named Acceptor exhibited low activity in the first half reaction. To date, Ppy has been used in the system; however, its thermostability is low. In this study, to improve the stability of the system, we applied Fluc from thermostabilized Luciola lateralis to FlimPIA. We screened suitable mutants as probes for FlimPIA and obtained Acceptor and Donor candidates. We detected the interaction of FKBP12-FRB with FlimPIA using these candidates. Furthermore, after the incubation of the probes at 37°C for 1 h, the luminescence signal of the new system was 2.4-fold higher than that of the previous system, showing significant improvement in the stability of the assay.

Using a coiled-coil peptide dimer as a model system to explore furan reactivity, we describe novel cross-link partners of furan warheads for site-specific cross-linking. We demonstrate that replacement of weak interhelical ionic contacts with a furan moiety and its potential cross-link partner affords covalently connected coiled-coil motifs upon furan activation. We describe for the first time the reaction of the activated furan warhead with cysteine and tyrosine, besides the previously reported lysine, thus enhancing the versatility of the furan cross-link methodology by the possibility to target different amino acids. The present in vitro validation of “furan-armed” α-helices provides further grounds for exploiting furan technology in the development of furan-modified ligands/proteins to target proteins in a covalent way through various amino acid side chains.

Bamboo is one of the most important non-timber forest resources worldwide. It has considerable economic value and unique flowering characteristics. The long juvenile phase in bamboo and unpredictable flowering time limit breeding and genetic improvement and seriously affect the productivity and application of bamboo forests. Members of SQUA-like subfamily genes play an essential role in controlling flowering time and floral organ identity. A comprehensive study was conducted to explain the functions of five SQUA-like subfamily genes in Phyllostachys edulis. Expression analysis revealed that all PeSQUAs have higher transcript levels in the reproductive period than in the juvenile phase. However, PeSQUAs showed divergent expression patterns during inflorescence development. The protein–protein interaction (PPI) patterns among PeSQUAs and other MADS-box members were analyzed by yeast two-hybrid (Y2H) experiments. Consistent with amino acid sequence similarity and phylogenetic analysis, the PPI patterns clustered into two groups. PeMADS2, 13, and 41 interacted with multiple PeMADS proteins, whereas PeMADS3 and 28 hardly interacted with other proteins. Based on our results, PeSQUA might possess different functions by forming protein complexes with other MADS-box proteins at different flowering stages. Furthermore, we chose PeMADS2 for functional analysis. Ectopic expression of PeMADS2 in Arabidopsis and rice caused early flowering, and abnormal phenotype was observed in transgenic Arabidopsis lines. RNA-seq analysis indicated that PeMADS2 integrated multiple pathways regulating floral transition to trigger early flowering time in rice. This function might be due to the interaction between PeMADS2 and homologous in rice. Therefore, we concluded that the five SQUA-like genes showed functional conservation and divergence based on sequence differences and were involved in floral transitions by forming protein complexes in P. edulis. The MADS-box protein complex model obtained in the current study will provide crucial insights into the molecular mechanisms of bamboo’s unique flowering characteristics.

Drug-likeness quantification is useful for screening drug candidates. Quantitative estimates of drug-likeness (QED) are commonly used to assess quantitative drug efficacy but are not suitable for screening compounds targeting protein-protein interactions (PPIs), which have recently gained attention. Therefore, we developed a quantitative estimate index for compounds targeting PPIs (QEPPI), specifically for early-stage screening of PPI-targeting compounds. QEPPI is an extension of the QED method for PPI-targeting drugs that models physicochemical properties based on the information available for drugs/compounds, specifically those reported to act on PPIs. FDA-approved drugs and compounds in iPPI-DB, which comprise PPI inhibitors and stabilizers, were evaluated using QEPPI. The results showed that QEPPI is more suitable than QED for early screening of PPI-targeting compounds. QEPPI was also considered an extended concept of the “Rule-of-Four” (RO4), a PPI inhibitor index. We evaluated the discriminatory performance of QEPPI and RO4 for datasets of PPI-target compounds and FDA-approved drugs using F-score and other indices. The F-scores of RO4 and QEPPI were 0.451 and 0.501, respectively. QEPPI showed better performance and enabled quantification of drug-likeness for early-stage PPI drug discovery. Hence, it can be used as an initial filter to efficiently screen PPI-targeting compounds.

Tau is a microtubule binding protein which plays an important role in physiological functions but it is also involved in the pathogenesis of Alzheimer's disease and related tauopathies. While insoluble and β‐sheet containing tau neurofibrillary tangles have been the histopathological hallmark of these diseases, recent studies suggest that soluble tau oligomers, which are formed prior to fibrils, are the primary toxic species. Substantial efforts have been made to generate tau oligomers using purified recombinant protein strategies to study oligomer conformations as well as their toxicity. However, no specific toxic tau species has been identified to date, potentially due to the lack of cellular environment. Hence, there is a need for cell‐based models for direct monitoring of tau oligomerization and aggregation. This review will summarize the recent advances in the cellular biosensor technology, with a focus on fluorescence resonance energy transfer, bimolecular fluorescence complementation, and split luciferase complementation approaches, to monitor formation of tau oligomers and aggregates in living cells. We will discuss the applications of the cellular biosensors in examining the heterogeneous tau conformational ensembles and factors affecting tau self‐assembly, as well as detecting cell‐to‐cell propagation of tau pathology. We will also compare the advantages and limitations of each type of tau biosensors, and highlight their translational applications in biomarker development and therapeutic discovery.

Simple Summary Breast cancer is the most common carcinoma and the leading cause of cancer-related death among women worldwide. Many kinases play important roles in the tumorigenesis of various cancers. IκBα phosphorylation is important for the regulation of NF-κB activity and is linked to the regulation of tumorigenesis. However, the kinase signaling network regulating IκBα phosphorylation in the context of cancer is not well understood. Herein, we report that RSK3 (RPS6KA2) is a novel binding partner of IκBα. RSK3 induces IκBα phosphorylation and NF-κB activation. Further, a chemical screening approach identified an inhibitor of RSK3/IκBα binding that impairs RSK3-mediated IκBα phosphorylation and decreases breast cancer cell survival, proliferation, and migration. Abstract Multiple cancer-related biological processes are mediated by protein-protein interactions (PPIs). Through interactions with a variety of factors, members of the ribosomal S6 kinase (RSK) family play roles in cell cycle progression and cell proliferation. In particular, RSK3 contributes to cancer viability, but the underlying mechanisms remain unknown. We performed a kinase library screen to find IκBα PPI binding partners and identified RSK3 as a novel IκBα binding partner using a cell-based distribution assay. In addition, we discovered a new PPI inhibitor using mammalian two-hybrid (MTH) analysis. We assessed the antitumor effects of the new inhibitor using cell proliferation and colony formation assays and monitored the rate of cell death by FACS apoptosis assay. IκBα is phosphorylated by the active form of the RSK3 kinase. A small-molecule inhibitor that targets the RSK3/IκBα complex exhibited antitumor activity in breast cancer cells and increased their rate of apoptosis. RSK3 phosphorylation and RSK3/IκBα complex formation might be functionally important in breast tumorigenesis. The RSK3/IκBα-specific binding inhibitor identified in this study represents a lead compound for the development of new anticancer drugs.

Cytosolic β-arrestins are key regulators of G protein-coupled receptors (GPCRs) by sterically uncoupling G protein activation, facilitating receptor internalization, and/or acting as G protein-independent signaling scaffolds. The current awareness that GPCR ligands may display bias toward G protein signaling or β-arrestin recruitment makes β-arrestin recruitment assays important additions to the drug discovery toolbox. This chapter describes two NanoLuc-based methods to monitor β-arrestin2 recruitment to the human histamine H1 receptor by measuring bioluminescence resonance energy transfer and enzyme-fragment complementation in real-time on living cells with reasonable high throughput. In addition to the detection of agonism, both assay formats can be used to qualitatively evaluate the binding kinetics of antihistamines on the human histamine H1 receptor.

Background Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating diseases affecting the pork industry globally. PRRS is caused by PRRS virus (PRRSV). Currently there are no effective treatments against this swine disease. Methods Through artificial intelligence molecular screening, we obtained a set of small molecule compounds predicted to target the scavenger receptor cysteine-rich domain 5 (SRCR5) of CD163, which is a cell surface receptor specific for PRRSV infection. These compounds were screened using a cell-based bimolecular fluorescence complementation (BiFC) assay, and the function of positive hit was further evaluated and validated by PRRSV-infection assay using porcine alveolar macrophages (PAMs). Results Using the BiFC assay, we identified one compound with previously unverified function, 4-Fluoro-2-methyl-N-[3-(3-morpholin-4-ylsulfonylanilino)quinoxalin-2-yl]benzenesulfonamide (designated here as B7), that significantly inhibits the interaction between the PRRSV glycoprotein (GP2a or GP4) and the CD163-SRCR5 domain. We further demonstrated that compound B7 inhibits PRRSV infection of PAMs, the primary target of PRRSV in a dose-dependent manner. B7 significantly inhibited the infection caused by both type I and type II PRRSV strains. Further comparison and functional evaluation of chemical compounds structurally related to B7 revealed that the 3-(morpholinosulfonyl)aniline moiety of B7 or the 3-(piperidinylsulfonyl)aniline moiety in a B7 analogue is important for the inhibitory function against PRRSV infection. Conclusions Our study identified a novel strategy to potentially prevent PRRSV infection in pigs by blocking the PRRSV-CD163 interaction with small molecules.

Background It was demonstrated in our previous research that trypsin scavenges superoxide anions. In this study, the mechanisms of storage quality improvement by trypsin were evaluated in H. undatus. Results Trypsin significantly delayed the weight loss and decreased the levels of ROS and membrane lipid peroxidation. Transcriptome profiles of H. undatus treated with trypsin revealed the pathways and regulatory mechanisms of ROS genes that were up- or downregulated following trypsin treatment by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses. The current results showed that through the regulation of the expression of hub redox enzymes, especially thioredoxin-related proteins, trypsin can maintain low levels of endogenous active oxygen species, reduce malondialdehyde content and delay fruit aging. In addition, the results of protein-protein interaction networks suggested that the downregulated NAD(P) H and lignin pathways might be the key regulatory mechanisms governed by trypsin. Conclusions Trypsin significantly prolonged the storage life of H. undatus through regulatory on the endogenous ROS metabolism. As a new biopreservative, trypsin is highly efficient, safe and economical. Therefore, trypsin possesses technical feasibility for the quality control of fruit storage. Graphical abstract

Bacterial proteins exhibiting two or more unrelated functions, referred to as moonlighting proteins, are suggested to contribute to full virulence manifestation in pathogens. An expanding number of published studies have revealed the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) to be a multitasking protein with virulence impact in a number of pathogenic bacteria. This protein can be detected on the bacterial surface or outside the bacterial cell, where it interacts with host proteins. In this way, GAPDH is able to modulate various pathogenic processes. Moreover, it has been shown to be involved in non-enzymatic processes inside the bacterial cell. In this mini review, we summarize main findings concerning the multiple localization and protein interactions of GAPDH derived from bacterial pathogens of humans. We also briefly discuss problems associated with using GAPDH as a vaccine antigen and endeavor to inspire further research to fill gaps in the existing knowledge.

It has been revealed by us that superoxide scavenging is a new activity of trypsin. In this study, the synergistic mechanisms of trypsin and superoxide dismutases (SODs) were evaluated in Hylocereus undatus (pitaya). Trypsin significantly improved the storage quality of H. undatus, including weight loss impediment and decrease of cellular injury. The regulatory mechanisms of 16 SOD genes by trypsin were revealed using transcriptomic analysis on H. undatus. Results revealed that important physiological metabolisms, such as antioxidant activities or metal ion transport were induced, and defense responses were inhibited by trypsin. Furthermore, the results of protein&ndash, protein interaction (PPI) networks showed that besides the entire ROS network, the tiny SODs sub-network was also a scale-free network. Cu/Zn SODs acted as the hub that SODs synergized with trypsin during the storage of H. undatus.

Gain-of-function mutations in PCSK9 (proprotein convertase subtilisin/kexin type 9) lead to reduced uptake of LDL (low density lipoprotein) cholesterol and, therefore, increased plasma LDL levels. However, the mechanism by which these mutants reduce LDL reuptake is not fully understood. Here, we have used molecular dynamics simulations, MM/PBSA (Molecular Mechanics/Poisson−Boltzmann Surface Area) binding affinity calculations, and residue interaction networks, to investigate the protein−protein interaction (PPI) disruptive effects of two of PCSK9′s gain-of-function mutations, Ser127Arg and Asp374Tyr on the PCSK9 and LDL receptor complex. In addition to these PPI disruptive mutants, a third, non-interface mutation (Arg496Trp) is included as a positive control. Our results indicate that Ser127Arg and Asp374Tyr confer significantly improved binding affinity, as well as different binding modes, when compared to the wild-type. These PPI disruptive mutations lie between the EGF(A) (epidermal growth factor precursor homology domain A) of the LDL receptor and the catalytic domain of PCSK9 (Asp374Tyr) and between the prodomain of PCSK9 and the β-propeller of the LDL receptor (Ser127Arg). The interactions involved in these two interfaces result in an LDL receptor that is sterically inhibited from entering its closed conformation. This could potentially implicate the prodomain as a target for small molecule inhibitors.

In silico binding site location and pose prediction for a molecule targeted at a large protein surface is a challenging task. We report a blind test with two peptidomimetic molecules that bind the flu virus hemagglutinin (HA) surface antigen, JNJ7918 and JNJ4796 (recently disclosed in van Dongen et al., Science, 2019, 363). Tests with a series of conventional approaches such as rigid (receptor) docking against available X-ray crystal structures or against an ensemble of structures generated by quick methodologies (NMA, homology modeling) gave mixed results, due to the shallowness and flexibility of the binding site and the sheer size of the target. However, tests with our Monte Carlo platform PELE in two protocols involving either exploration of the whole protein surface (global exploration), or the latter followed by refinement of best solutions (local exploration) yielded remarkably good results by locating the actual binding site and generating binding modes that recovered all native contacts found in the X-ray structures. Thus, the Monte Carlo scheme of PELE seems promising as a quick methodology to overcome the challenge of identifying entirely unknown binding sites and modes for protein–protein disruptors.

A theoretical scheme to systematically describe correlated (network-like) interactions between molecular fragments is proposed within the framework of the fragment molecular orbital (FMO) method. The method is mathematically based on the singular value decomposition (SVD) of the inter-fragment interaction energy (IFIE) matrix obtained by the FMO calculation, and can be applied to a comprehensive description of protein-protein interactions in the context of molecular recognition. In the present study we apply the proposed method to a complex of measles virus hemagglutinin and human SLAM receptor, thus finding a usefulness for efficiently eliciting the correlated interactions among the amino-acid residues involved in the two proteins. Additionally, collective interaction networks by amino-acid residues important for mutation experiments can be clearly visualized., Graphical abstract Image 1, Highlights • A new method to describe correlated molecular-fragment interactions is proposed. • Inter-fragment interaction energies (IFIEs) are calculated by the FMO method. • Singular value decomposition is applied to the IFIE matrix for protein complex. • Correlated inter-residue interactions in the complex are extracted systematically. • Complex of measles virus hemagglutinin and SLAM receptor is analyzed.

Intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) are functional proteins and domains that devoid stable secondary and/or tertiary structure. IDPs/IDPRs are abundantly present in various proteomes, where they are involved in regulation, signaling, and control, thereby serving as crucial regulators of various cellular processes. Various mechanisms are utilized to tightly regulate and modulate biological functions, structural properties, cellular levels, and localization of these important controllers. Among these regulatory mechanisms are precisely controlled degradation and different posttranslational modifications (PTMs). Many normal cellular processes are associated with the presence of the right amounts of precisely activated IDPs at right places and in right time. However, wrecked regulation of IDPs/IDPRs might be associated with various human maladies, ranging from cancer and neurodegeneration to cardiovascular disease and diabetes. Pathogenic transformations of IDPs/IDPRs are often triggered by altered PTMs. This review considers some of the aspects of IDPs/IDPRs and their normal and aberrant regulation by PTMs.

Conventional instruments for cancer diagnosis including magnetic resonance imaging, computed tomography scan, are expensive and require long-waiting time, whilst the outcomes have not approached to the successful early-stage diagnosis yet. Due to the special properties of graphene-based nanocomposites, e.g., good electrical and thermal conductivity, luminescence, and mechanic flexibility, these ultra-thin two-dimensional nanostructures have been extensively used as platforms for detecting biomolecules and cells. Herein, we discuss the development of two types of graphene and graphene oxide-based biosensors: electrochemical and optical, aimed for tumor detection and early diagnosis of cancer. Moreover, we highlight the challenges of their use as biosensors for cancer detection. Efficient surface modification and suitable bio-conjugation of graphene and graphene oxide is discussed, including key role in improvement of the biocompatibility, and improved performance in terms of selectivity and sensitivity towards the early diagnosis of cancer.

Cytochrome P450 enzymes, which catalyze oxygenation reactions of both exogenous and endogenous chemicals, are membrane bound proteins that require interaction with their redox partners in order to function. Those responsible for drug and foreign compound metabolism are localized primarily in the endoplasmic reticulum of liver, lung, intestine, and other tissues. More recently, the potential for P450 enzymes to exist as supramolecular complexes has been shown by the demonstration of both homomeric and heteromeric complexes. The P450 units in these complexes are heterogeneous with respect to their distribution and function, and the interaction of different P450s can influence P450-specific metabolism. The goal of this review is to examine the evidence supporting the existence of physical complexes among P450 enzymes. Additionally, the review examines the crystal lattices of different P450 enzymes derived from X-ray diffraction data to make assumptions regarding possible quaternary structures in membranes and in turn, to predict how the quaternary structures could influence metabolism and explain the functional effects of specific P450–P450 interactions.

Protein heterodimer complexes are often involved in catalysis, regulation, assembly, immunity and inhibition. This involves the formation of stable interfaces between the interacting partners. Hence, it is of interest to describe heterodimer interfaces using known structural complexes. We use a non-redundant dataset of 192 heterodimer complex structures from the protein databank (PDB) to identify interface residues and describe their interfaces using amino-acids residue property preference. Analysis of the dataset shows that the heterodimer interfaces are often abundant in polar residues. The analysis also shows the presence of two classes of interfaces in heterodimer complexes. The first class of interfaces (class A) with more polar residues than core but less than surface is known. These interfaces are more hydrophobic than surfaces, where protein-protein binding is largely hydrophobic. The second class of interfaces (class B) with more polar residues than core and surface is shown. These interfaces are more polar than surfaces, where binding is mainly polar. Thus, these findings provide insights to the understanding of protein-protein interactions.

Background Protein-protein interaction (PPI) is essential for molecular functions in biological cells. Investigation on protein interfaces of known complexes is an important step towards deciphering the driving forces of PPIs. Each PPI complex is specific, sensitive and selective to binding. Therefore, we have estimated the relative difference in percentage of polar residues between surface and the interface for each complex in a non-redundant heterodimer dataset of 278 complexes to understand the predominant forces driving binding. Results Our analysis showed ~60% of protein complexes with surface polarity greater than interface polarity (designated as class A). However, a considerable number of complexes (~40%) have interface polarity greater than surface polarity, (designated as class B), with a significantly different p-value of 1.66E-45 from class A. Comprehensive analyses of protein complexes show that interface features such as interface area, interface polarity abundance, solvation free energy gain upon interface formation, binding energy and the percentage of interface charged residue abundance distinguish among class A and class B complexes, while electrostatic visualization maps also help differentiate interface classes among complexes. Conclusions Class A complexes are classical with abundant non-polar interactions at the interface; however class B complexes have abundant polar interactions at the interface, similar to protein surface characteristics. Five physicochemical interface features analyzed from the protein heterodimer dataset are discriminatory among the interface residue-level classes. These novel observations find application in developing residue-level models for protein-protein binding prediction, protein-protein docking studies and interface inhibitor design as drugs.

Drug–drug interactions (DDIs) may lead to adverse effects and potentially result in drug withdrawal from the market. Predicting DDIs during drug development would help reduce development costs and time by rigorous evaluation of drug candidates. The primary mechanisms of DDIs are based on pharmacokinetics (PK) and pharmacodynamics (PD). This study examines the effects of 2D structural similarities of drugs on DDI prediction through interaction networks including both PD and PK knowledge. Our assumption was that a query drug (Dq) and a drug to be examined (De) likely have DDI if the drugs in the interaction network of De are structurally similar to Dq. A network of De describes the associations between the drugs and the proteins relating to PK and PD for De. These include target proteins, proteins interacting with target proteins, enzymes, and transporters for De. We constructed logistic regression models for DDI prediction using only 2D structural similarities between each Dq and the drugs in the network of De. The results indicated that our models could effectively predict DDIs. It was found that integrating structural similarity scores of the drugs relating to both PK and PD of De was crucial for model performance. In particular, the combination of the target- and enzyme-related scores provided the largest increase of the predictive power.Graphical abstract. Electronic supplementary material The online version of this article (doi:10.1186/s13321-017-0200-8) contains supplementary material, which is available to authorized users.