Well-characterized Interaction Research Articles

SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein-Protein Interfaces.

Protein-protein interactions mediate most molecular processes in the cell, offering a significant opportunity to expand the set of known druggable targets. Unfortunately, targeting these interactions can be challenging due to their typically flat and featureless interaction surfaces, which often change as the complex forms. Such surface changes may reveal hidden (cryptic) druggable pockets. Here, we analyze a set of well-characterized protein-protein interactions harboring cryptic pockets and investigate the predictive power of current computational methods. Based on our observations, we developed a new computational strategy, SWISH-X (SWISH Expanded), which combines the established cryptic pocket identification capabilities of SWISH with the rapid temperature range exploration of OPES MultiThermal. SWISH-X is able to reliably identify cryptic pockets at protein-protein interfaces while retaining its predictive power for revealing cryptic pockets in isolated proteins, such as TEM-1 β-lactamase.

Rapid depletion of target proteins in plants by an inducible protein degradation system.

Inducible protein knockdowns are excellent tools to test the function of essential proteins in short time scales and to capture the role of proteins in dynamic events. Current approaches destroy or sequester proteins by exploiting plant biological mechanisms such as the activity of photoreceptors for optogenetics or auxin-mediated ubiquitination in auxin degrons. It follows that these are not applicable for plants as light and auxin are strong signals for plant cells. We describe here an inducible protein degradation system in plants named E3-DART for E3-targeted Degradation of Plant Proteins. The E3-DART system is based on the specific and well-characterized interaction between the Salmonella-secreted protein H1 (SspH1) and its human target protein kinase N1 (PKN1). This system harnesses the E3 catalytic activity of SspH1 and the SspH1-binding activity of the homology region 1b (HR1b) domain from PKN1. Using Nicotiana benthamiana and Arabidopsis (Arabidopsis thaliana), we show that a chimeric protein containing the leucine-rich repeat and novel E3 ligase domains of SspH1 efficiently targets protein fusions of varying sizes containing HR1b for degradation. Target protein degradation was induced by transcriptional control of the chimeric E3 ligase using a glucocorticoid transactivation system, and target protein depletion was detected as early as 3 h after induction. This system could be used to study the loss of any plant protein with high-temporal resolution and may become an important tool in plant cell biology.

Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning.

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailability. Here we show that the interaction profiles between drugs and intestinal drug transporters can be obtained by modulating transporter expression in intact porcine tissue explants via the ultrasound-mediated delivery of small interfering RNAs and that the interaction profiles can be classified via a random forest model trained on the drug-transporter relationships. For 24 drugs with well-characterized drug-transporter interactions, the model achieved 100% concordance. For 28 clinical drugs and 22 investigational drugs, the model identified 58 unknown drug-transporter interactions, 7 of which (out of 8 tested) corresponded to drug-pharmacokinetic measurements in mice. We also validated the model's predictions for interactions between doxycycline and four drugs (warfarin, tacrolimus, digoxin and levetiracetam) through an ex vivo perfusion assay and the analysis of pharmacologic data from patients. Screening drugs for their interactions with the intestinal transportome via tissue explants and machine learning may help to expedite drug development and the evaluation of drug safety.

Abstract B098: Unbiased in vitro and in vivo drug anchor screens identify mechanisms of resistance and sensitization for MTA-cooperative PRMT5 inhibitors in MTAP-deleted cancer models

Abstract Homozygous deletion of the MTAP gene is one of the most common genetic alterations in cancer, affecting 10-15% of all human cancer. Clinical MTA-cooperative PRMT5 inhibitors, including TNG908 and TNG462, were developed to leverage the well-characterized synthetic lethal interaction between PRMT5 inhibition and MTAP deletion. Indeed, the first disclosed clinical data for an MTA-cooperative PRMT5 inhibitor demonstrated the ability of TNG908 to selectively inhibit PRMT5 in MTAP-deleted tumors while sparing adjacent normal, MTAP-proficient cells in patients. To further explore the mechanism of action of MTA-cooperative PRMT5 inhibitors in MTAP-deleted cells, we employed multiple CRISPR-based editing platforms (CRISPRn, CRISPRi and CRISPRa) to conduct unbiased MTA-cooperative PRMT5 inhibitor anchor screens in vitro and in vivo. A panel of cancer models representing multiple histologies revealed potential PRMT5 inhibitor sensitization and resistance pathways that also include mechanisms that are specific to MTA-cooperative inhibitors. Specifically, the results of these screens identify 1) the effect of MTA/SAM metabolism on MTA-cooperative PRMT5 inhibitors, and 2) identification of potential sub-stratification strategies for patients with MTAP-deleted cancer, and 3) the activity of PRMT5 in anti-apoptotic pathways and synergy between PRMT5 and BCLxL inhibition. Citation Format: Steven Lombardo, Matthew R Tonini, Lauren Grove, Silvia Fenoglio, James Tepper, Binzhang Shen, Hannah Stowe, Shangtao Liu, Samuel R Meier, Ashley H Choi, Tenzing Khendu, Yi Yu, Kevin M Cottrell, John P Maxwell, Jannik N Andersen, Alan Huang, Kimberly J Briggs, Teng Teng. Unbiased in vitro and in vivo drug anchor screens identify mechanisms of resistance and sensitization for MTA-cooperative PRMT5 inhibitors in MTAP-deleted cancer models [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B098.

Guidelines for Optimizing Type S Nonribosomal Peptide Synthetases.

Bacterial biosynthetic assembly lines, such as nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), play a crucial role in the synthesis of natural products that have significant therapeutic potential. The ability to engineer these biosynthetic assembly lines offers opportunities to produce artificial nonribosomal peptides, polyketides, and their hybrids with improved properties. In this study, we introduced a synthetic NRPS variant, termed type S NRPS, which simplifies the engineering process and enables biocombinatorial approaches for generating nonribosomal peptide libraries in a parallelized high-throughput manner. However, initial generations of type S NRPSs exhibited a bottleneck that led to significantly reduced production yields. To address this challenge, we employed two optimization strategies. First, we truncated SYNZIPs from the N- and/or C-terminus of the NRPS. SYNZIPs comprise a large set of well-characterized synthetic protein interaction reagents. Second, we incorporated a structurally flexible glycine-serine linker between the NRPS protein and the attached SYNZIP, aiming to improve dynamic domain-domain interactions. Through an iterative optimization process, we achieved remarkable improvements in production yields, with titer increases of up to 55-fold compared to the nonoptimized counterparts. These optimizations successfully restored production levels of type S NRPSs to those observed in wild-type NRPSs and even surpassed them. Overall, our findings demonstrate the potential of engineering bacterial biosynthetic assembly lines for the production of artificial nonribosomal peptides. In addition, optimizing the SYNZIP toolbox can have valuable implications for diverse applications in synthetic biology, such as metabolic engineering, cell signaling studies, or engineering of other multienzyme complexes, such as PKSs.

How Histone Deacetylase 3 Controls Hepcidin Expression and Hepatitis C Virus Replication

The key role of histone deacetylases (HDACs) in the regulation of the cellular response to infection with the hepatitis C virus (HCV) was first demonstrated in 2008. Studying the metabolism of iron in the liver tissues of patients with chronic hepatitis C, the authors found that the expression of the hepcidin gene (HAMP), a hormone regulator of iron export, is markedly reduced in hepatocytes under conditions of oxidative stress caused by viral infection. HDACs were involved in the regulation of hepcidin expression through the control of acetylation level of histones and transcription factors, primarily STAT3, associated with the HAMP promoter. The purpose of this review is to summarize current data on the functioning of the HCV-HDAC3-STAT3-HAMP regulatory circuit as an example of a well-characterized interaction between the virus and the epigenetic apparatus of the host cell.

Cryo-EM structure supports a role of AQP7 as a junction protein

Aquaglyceroporin 7 (AQP7) facilitates glycerol flux across the plasma membrane with a critical physiological role linked to metabolism, obesity, and associated diseases. Here, we present the single-particle cryo-EM structure of AQP7 determined at 2.55 Å resolution adopting two adhering tetramers, stabilized by extracellularly exposed loops, in a configuration like that of the well-characterized interaction of AQP0 tetramers. The central pore, in-between the four monomers, displays well-defined densities restricted by two leucine filters. Gas chromatography mass spectrometry (GC/MS) results show that the AQP7 sample contains glycerol 3-phosphate (Gro3P), which is compatible with the identified features in the central pore. AQP7 is shown to be highly expressed in human pancreatic α- and β- cells suggesting that the identified AQP7 octamer assembly, in addition to its function as glycerol channel, may serve as junction proteins within the endocrine pancreas.

Label-free biosensing of lignans for therapeutics using engineered model surfaces

The label-free interaction analysis of macromolecules and small molecules has increasing importance nowadays, both in diagnostics and therapeutics. In the blood vascular system, human serum albumin (HSA) is a vital globular transport protein with potential multiple ligand binding sites. Characterizing the binding affinity of compounds to HSA is essential in pharmaceutics and in developing new compounds for clinical application. Aryltetralin lignans from the roots of Anthriscus sylvestris are potential antitumor therapeutic candidates, but their molecular scale interactions with specific biomolecules are unrevealed. Here, we applied the label-free grating-coupled interferometry (GCI) biosensing method with a polycarboxylate-based hydrogel layer with immobilized HSA on top of it. With this engineered model surface, we could determine the binding parameters of two novel aryltetralin lignans, deoxypodophyllotoxin (DPT), and angeloyl podophyllotoxin (APT) to HSA. Exploiting the multi-channel referencing ability, the unique surface sensitivity, and the throughput of GCI, we first revealed the specific biomolecular interactions. Traditional label-free kinetic measurements were also compared with a novel, fast way of measuring affinity kinetics using less sample material (repeated analyte pulses of increasing duration (RAPID)). Experiments with well-characterized molecular interactions (furosemide to carbonic-anhydrase (CAII) and warfarin, norfloxacin to HSA) were performed to prove the reliability of the RAPID method. In all investigated cases, the RAPID and traditional measurement gave similar affinity values. In the case of DPT, the measurements and relevant modeling suggested two binding sites on HSA, with dissociation constant values of Kd1 = 1.8 ± 0.01 μM, Kd2 = 3 ± 0.02 μM. In the case of APT, the experiments resulted in Kd1 = 9 ± 1.7 μM, Kd2 = 28 ± 0.3 μM. The obtained binding values might suggest the potential medical application of DPT and APT without further optimization of their binding affinity to HSA. These results could be also adapted to other biomolecules and applications where sample consumption and the rapidity of the measurements are critical.

Optimization of RiPCA for the Live-Cell Detection of Pre-MicroRNA-Protein Interactions.

Advancements in methods for identifying RNA-protein interactions (RPIs) on a large scale has necessitated the development of assays for validation of these interactions, particularly in living cells. We previously reported the development of RiPCA (RNA interaction with protein-mediated complementation assay) to enable the cellular detection of the well-characterized interaction between the pre-microRNA, pre-let-7, and its RNA-binding protein (RBP) partner Lin28. In this study, the applicability of RiPCA for the detection of putative pre-miRNA-protein interactions was explored using an improved RiPCA protocol, termed RiPCA 2.0. RiPCA 2.0 was adapted to detect the sequence specificity of the RBPs hnRNP A1, Msi1, and Msi2 for reported pre-microRNA binding partners. Additionally, the ability of RiPCA 2.0 to detect site-specific binding was explored. Collectively, this work highlights the versatility of RiPCA 2.0 in detecting cellular RPIs.

T cell and B cell antigen receptors share a conserved core transmembrane structure

The B cell and T cell antigen receptors (BCR and TCR) share a common architecture in which variable dimeric antigen-binding modules assemble with invariant dimeric signaling modules to form functional receptor complexes. In the TCR, a highly conserved T cell receptor αβ (TCRαβ) transmembrane (TM) interface forms a rigid structure around which its three dimeric signaling modules assemble through well-characterized polar interactions. Noting that the key features stabilizing this TCRαβ TM interface also appear with high evolutionary conservation in the TM sequences of the membrane immunoglobulin (mIg) heavy chains that form the BCR's homodimeric antigen-binding module, we asked whether the BCR contained an analogous TM structure. Using an unbiased biochemical and computational modeling approach, we found that the mouse IgM BCR forms a core TM structure that is remarkably similar to that of the TCR. This structure is reinforced by a network of interhelical hydrogen bonds, and our model is nearly identical to the arrangement observed in the just-released cryo-electron microscopy (cryo-EM) structures of intact human BCRs. Our biochemical analysis shows that the integrity of this TM structure is vital for stable assembly with the BCR signaling module CD79AB in the B cell endoplasmic reticulum, and molecular dynamics simulations indicate that BCRs of all five isotypes can form comparable structures. These results demonstrate that, despite their many differences in composition, complexity, and ligand type, TCRs and BCRs rely on a common core TM structure that has been shaped by evolution for optimal receptor assembly and stability in the cell membrane.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements.

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Quantifying the impact of ecological memory on the dynamics of interacting communities.

Ecological memory refers to the influence of past events on the response of an ecosystem to exogenous or endogenous changes. Memory has been widely recognized as a key contributor to the dynamics of ecosystems and other complex systems, yet quantitative community models often ignore memory and its implications. Recent modeling studies have shown how interactions between community members can lead to the emergence of resilience and multistability under environmental perturbations. We demonstrate how memory can be introduced in such models using the framework of fractional calculus. We study how the dynamics of a well-characterized interaction model is affected by gradual increases in ecological memory under varying initial conditions, perturbations, and stochasticity. Our results highlight the implications of memory on several key aspects of community dynamics. In general, memory introduces inertia into the dynamics. This favors species coexistence under perturbation, enhances system resistance to state shifts, mitigates hysteresis, and can affect system resilience both ways depending on the time scale considered. Memory also promotes long transient dynamics, such as long-standing oscillations and delayed regime shifts, and contributes to the emergence and persistence of alternative stable states. Our study highlights the fundamental role of memory in communities, and provides quantitative tools to introduce it in ecological models and analyse its impact under varying conditions.

A coarse-grained approach to model the dynamics of the actomyosin cortex

BackgroundThe dynamics of the actomyosin machinery is at the core of many important biological processes. Several relevant cellular responses such as the rhythmic compression of the cell cortex are governed, at a mesoscopic level, by the nonlinear interaction between actin monomers, actin crosslinkers, and myosin motors. Coarse-grained models are an optimal tool to study actomyosin systems, since they can include processes that occur at long time and space scales, while maintaining the most relevant features of the molecular interactions.ResultsHere, we present a coarse-grained model of a two-dimensional actomyosin cortex, adjacent to a three-dimensional cytoplasm. Our simplified model incorporates only well-characterized interactions between actin monomers, actin crosslinkers and myosin, and it is able to reproduce many of the most important aspects of actin filament and actomyosin network formation, such as dynamics of polymerization and depolymerization, treadmilling, network formation, and the autonomous oscillatory dynamics of actomyosin.ConclusionsWe believe that the present model can be used to study the in vivo response of actomyosin networks to changes in key parameters of the system, such as alterations in the attachment of actin filaments to the cell cortex.

Regulatory subunit NEMO promotes polyubiquitin-dependent induction of NF-κB through a targetable second interaction with upstream activator IKK2

Canonical NF-κB signaling through the inhibitor of κB kinase (IKK) complex requires induction of IKK2/IKKβ subunit catalytic activity via specific phosphorylation within its activation loop. This process is known to be dependent upon the accessory ubiquitin (Ub)-binding subunit NF-κB essential modulator (NEMO)/IKKγ as well as poly-Ub chains. However, the mechanism through which poly-Ub binding serves to promote IKK catalytic activity is unclear. Here, we show that binding of NEMO/IKKγ to linear poly-Ub promotes a second interaction between NEMO/IKKγ and IKK2/IKKβ, distinct from the well-characterized interaction of the NEMO/IKKγ N terminus to the “NEMO-binding domain” at the C terminus of IKK2/IKKβ. We mapped the location of this second interaction to a stretch of roughly six amino acids immediately N-terminal to the zinc finger domain in human NEMO/IKKγ. We also showed that amino acid residues within this region of NEMO/IKKγ are necessary for binding to IKK2/IKKβ through this secondary interaction in vitro and for full activation of IKK2/IKKβ in cultured cells. Furthermore, we identified a docking site for this segment of NEMO/IKKγ on IKK2/IKKβ within its scaffold-dimerization domain proximal to the kinase domain–Ub-like domain. Finally, we showed that a peptide derived from this region of NEMO/IKKγ is capable of interfering specifically with canonical NF-κB signaling in transfected cells. These in vitro biochemical and cell culture–based experiments suggest that, as a consequence of its association with linear poly-Ub, NEMO/IKKγ plays a direct role in priming IKK2/IKKβ for phosphorylation and that this process can be inhibited to specifically disrupt canonical NF-κB signaling.

Split-HaloTag imaging assay for sophisticated microscopy of protein–protein interactions in planta

An ever-increasing number of intracellular multi-protein networks have been identified in plant cells. Split-GFP-based protein–protein interaction assays combine the advantages of in vivo interaction studies in a native environment with additional visualization of protein complex localization. Because of their simple protocols, they have become some of the most frequently used methods. However, standard fluorescent proteins present several drawbacks for sophisticated microscopy. With the HaloTag system, these drawbacks can be overcome, as this reporter forms covalent irreversible bonds with synthetic photostable fluorescent ligands. Dyes can be used in adjustable concentrations and are suitable for advanced microscopy methods. Therefore, we have established the Split-HaloTag imaging assay in plants, which is based on the reconstitution of a functional HaloTag protein upon protein–protein interaction and the subsequent covalent binding of an added fluorescent ligand. Its suitability and robustness were demonstrated using a well-characterized interaction as an example of protein–protein interaction at cellular structures: the anchoring of the molybdenum cofactor biosynthesis complex to filamentous actin. In addition, a specific interaction was visualized in a more distinctive manner with subdiffractional polarization microscopy, Airyscan, and structured illumination microscopy to provide examples of sophisticated imaging. Split-GFP and Split-HaloTag can complement one another, as Split-HaloTag represents an alternative option and an addition to the large toolbox of in vivo methods. Therefore, this promising new Split-HaloTag imaging assay provides a unique and sensitive approach for more detailed characterization of protein–protein interactions using specific microscopy techniques, such as 3D imaging, single-molecule tracking, and super-resolution microscopy.

SNF1-related protein kinase 1: the many-faced signaling hub regulating developmental plasticity in plants.

The Snf1-related protein kinase 1 (SnRK1) is the plant homolog of the heterotrimeric AMP-activated protein kinase/sucrose non-fermenting 1 (AMPK/Snf1), which works as a major regulator of growth under nutrient-limiting conditions in eukaryotes. Along with its conserved role as a master regulator of sugar starvation responses, SnRK1 is involved in controlling the developmental plasticity and resilience under diverse environmental conditions in plants. In this review, through mining and analyzing the interactome and phosphoproteome data of SnRK1, we are highlighting its role in fundamental cellular processes such as gene regulation, protein synthesis, primary metabolism, protein trafficking, nutrient homeostasis, and autophagy. Along with the well-characterized molecular interaction in SnRK1 signaling, our analysis highlights several unchartered regions of SnRK1 signaling in plants such as its possible communication with chromatin remodelers, histone modifiers, and inositol phosphate signaling. We also discuss potential reciprocal interactions of SnRK1 signaling with other signaling pathways and cellular processes, which could be involved in maintaining flexibility and homeostasis under different environmental conditions. Overall, this review provides a comprehensive overview of the SnRK1 signaling network in plants and suggests many novel directions for future research.

FAK displacement from focal adhesions: a promising strategy to target processes implicated in cancer progression and metastasis

BackgroundFocal adhesion kinase (FAK) is a non-receptor tyrosine kinase that is overexpressed or activated in several advanced-stage solid cancers. It is known to play both kinase-dependent and -independent roles in promoting tumor progression and metastasis. Numerous inhibitors, targeting either the enzymatic or scaffolding activities of FAK have been generated, with varying degree of success. Here, we describe a novel approach to site-specifically target both kinase-dependent and -independent FAK functions at focal adhesions (FAs), the primary sites at which the kinase exerts its activity.MethodsWe took advantage of the well-characterized interactions between the paxillin LD motifs and the FAK FAT domain and generated a polypeptide (LD2-LD3-LD4) expected to compete with interactions with paxillin. Co-immunoprecipitation experiments were performed to examine the interaction between the LD2-LD3-LD4 polypeptide and FAK. The effects of LD2-LD3-LD4 in the localization and functions of FAK, as well as FA composition, were evaluated using quantitative immunofluorescence, cell fractionation, FA isolation and Western Blot analysis. Live cell imaging, as well as 2-D migration and cell invasion assays were used to examine the effects on FA turnover and tumor cell migration and invasion.ResultsExpression of the LD2-LD3-LD4 polypeptide prevents FAK localization at FAs, in a controlled and dose-dependent manner, by competing with endogenous paxillin for FAK binding. Importantly, the LD2-LD3-LD4 peptide did not otherwise affect FA composition or integrin activation. LD2-LD3-LD4 inhibited FAK-dependent downstream integrin signaling and, unlike existing inhibitors, also blocked FAK’s scaffolding functions. We further show that LD2-LD3-LD4 expression markedly reduces FA turnover and inhibits tumor cell migration and invasion. Finally, we show that dimers of a single motif, linked through a flexible linker of the proper size, are sufficient for the displacement of FAK from FAs and for inhibition of tumor cell migration. This work raises the possibility of using a synthetic peptide as an antimetastatic agent, given that effective displacement of FAK from FAs only requires dimers of a single LD motif linked by a short flexible linker.ConclusionIn conclusion, these results suggest that FAK displacement from FAs is a promising new strategy to target critical processes implicated in cancer progression and metastasis.BafrBk9CYavjRzuXSGmQcGVideo abstract.Graphical abstract

Long non-coding RNAs associate with jasmonate-mediated plant defence against herbivores.

Long non-coding RNA (lncRNA) are important regulators of many biological processes in plants, including defence against pathogens; whether lncRNAs mediate defence against herbivore attack is yet to be explored. With wild tobacco, Nicotiana attenuata, and its well-characterized interactions with herbivores, we identified a total of 1,290 significantly up- or down-regulated lncRNAs in response to a precise herbivore elicitation treatment. Of these, long intergenic non-coding RNAs (lincRNAs) were the most abundant. Based on their expression patterns, these up-regulated lincRNAs were classified as early (<1 hr) or late (>3 hr) responders. The early responding lincRNAs had accumulation patterns that tracked the herbivore-elicited burst of bioactive jasmonates (JAs) and the expression of regulator genes in JA signalling which regulate plant defences against herbivores. Silencing two of these early responders in N. attenuata (JAL1 and JAL3) significantly attenuated the accumulation of JAs, JA-mediated defensives and the plant's resistance to M. sexta attack, suggesting roles in regulating JA-mediated plant defence. By lincRNA sequencing of JA-deficient lines, many late responder lincRNAs were found to be transcriptionally regulated by JA signalling. This study uncovers a new role of lncRNAs in JA-mediated herbivore resistance.

Elucidation of the mechanisms underlying the anticholecystitis effect of the Tibetan medicine “Dida” using Network pharmacology

Purpose: To study the mechanism involved in the anti-cholecystitis effect the Tibetan medicine “Dida”, using network pharmacology-integrated molecular docking simulationsMethods: In this investigation, the bioactive compounds of Dida were collected, network pharmacology methods to predict their targets, and networks were constructed through GO and KEGG pathway analyses. The potential binding between the bioactive compounds and the targets were demonstrated using molecular docking simulations.Results: A total of 12 bioactive compounds and 50 key targets of Dida were identified. Two networks, namely, protein-protein interaction (PPI) network of cholecystitis targets, and compound-target-pathway network, were established. Network analysis showed that 10 targets (GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1) may be the therapeutic targets of Dida in cholecystitis. Analysis of the KEGG pathway indicated that the anti-cholecystitis effect of Dida may its regulation of a few crucial pathways, such as apoptosis, as well as toll-like receptor, T cell receptor, NOD-like receptor, and MAPK signaling pathways. Furthermore, molecular docking simulation revealed that CASP3, CAPDH, HSP90AA1, MAPK3, MAPK1, and STAT3 had well-characterized interactions with the corresponding compounds.Conclusion: The mechanism underlying the anti-cholecystitis effect of Dida was successfully predicted and verified using a combination of network pharmacology and molecular docking simulation. This provides a firm basis for the experimental verification of the use of Dida in the treatment of cholecystitis, and enhances its rational application in clinical medication.&#x0D; Keywords: Tibetan medicine, Dida, Cholecystitis, Mechanism of effect, Network pharmacology, Molecular docking simulation

Elucidation of the mechanism of action of the anticholecystitis effect of the Tibetan medicine “Dida” using network pharmacology

Purpose: To study the mechanism involved in the anti-cholecystitis effect the Tibetan medicine “Dida”, using network pharmacology-integrated molecular docking simulationsMethods: In this investigation, the bioactive compounds of Dida were collected, network pharmacology methods to predict their targets, and networks were constructed through GO and KEGG pathway analyses. The potential binding between the bioactive compounds and the targets were demonstrated using molecular docking simulations.Results: A total of 12 bioactive compounds and 50 key targets of Dida were identified. Two networks, namely, protein–protein interaction (PPI) network of cholecystitis targets, and compound–target– pathway network, were established. Network analysis showed that 10 targets (GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1) may be the therapeutic targets of Dida in cholecystitis. Analysis of the KEGG pathway indicated that the anti-cholecystitis effect of Dida may its regulation of a few crucial pathways, such as apoptosis, as well as toll-like receptor, T cell receptor, NOD-like receptor, and MAPK signaling pathways. Furthermore, molecular docking simulation revealed that CASP3, CAPDH, HSP90AA1, MAPK3, MAPK1, and STAT3 had well-characterized interactions with the corresponding compounds.Conclusion: The mechanism underlying the anti-cholecystitis effect of Dida has been successfully predicted and verified using a combination of network pharmacology and molecular docking simulation. This provides a firm basis for the experimental verification of the use of Dida in the treatment of cholecystitis, and enhances its rational application in clinical practice.&#x0D; Keywords: Tibetan medicine, Dida, Cholecystitis, Mechanism, Network pharmacology, Molecular docking simulation