Target Binding Research Articles

MoPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models.

The ability to precisely target specific motifs on disease-related proteins, whether conserved epitopes on viral proteins, intrinsically disordered regions within transcription factors, or breakpoint junctions in fusion oncoproteins, is essential for modulating their function while minimizing off-target effects. Current methods struggle to achieve this specificity without reliable structural information. In this work, we introduce a motif-specific PPI targeting algorithm, moPPIt, for de novo generation of motif-specific peptide binders from the target protein sequence alone. At the core of moPPIt is BindEvaluator, a transformer-based model that interpolates protein language model embeddings of two proteins via a series of multi-headed self-attention blocks, with a key focus on local motif features. Trained on over 510,000 annotated PPIs, BindEvaluator accurately predicts target binding sites given protein-protein sequence pairs with a test AUC > 0.94, improving to AUC > 0.96 when fine-tuned on peptide-protein pairs. By combining BindEvaluator with our PepMLM peptide generator and genetic algorithm-based optimization, moPPIt generates peptides that bind specifically to user-defined residues on target proteins. We demonstrate moPPIt's efficacy in computationally designing binders to specific motifs, first on targets with known binding peptides and then extending to structured and disordered targets with no known binders. In total, moPPIt serves as a powerful tool for developing highly specific peptide therapeutics without relying on target structure or structure-dependent latent spaces.

Simulation-based optimization concept for integrated assessment models: Case study MEDEAS-world

Simulation based optimization concept has been so far presented at local and national energy systems planning levels. This method represents a systematic way of dealing with uncertainties and combinatorial complexity when using modelling tools of very large size with significant number of possible policy inputs, and could be useful to analyse policy recommendations in broader models integrating more dimensions than energy. For the first time, the concept is successfully demonstrated using a working integrated assessment model (IAM), although some attempts have been mentioned in literature previously. IAMs aim to link main features of society, economy and energy with the biosphere and atmosphere into one modelling framework. The concept has been demonstrated for the IAM MEDEAS-World using system dynamics platform Vensim (version 9.3.4.) for both simulation and optimization. For an optimization problem formulation, 12 decision variables are selected from numerous input model parameters, the gross domestic product per capita has been selected for a goal function from simulation result as quantifiable policy objective, while for the constraint CO2 emissions is selected as subject to binding targets. It is possible to compile the simulation code so that optimization running time is around 10 times shorter. Preliminary results show that it is possible to implement richer optimization problems without significant increases in the running time using personal computers. The main contribution of this work is to prove the concept of simulation-based optimization by a demonstration within a working IAM. This opens the way to promising future work to inform about optimal combinations of available policies within different storylines, as well as providing additional general understanding of the IAM which could allow to improve the model. The original Vensim code has been provided in the Appendix.

Revealing miRNAs patterns by employing matrix representations and energy analysis

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression. Despite their relatively short length (about 21 nucleotides), they can regulate thousands of transcripts within a cell. Due to their low complementarity to targets, studying their activity and binding region preferences (3′UTR, 5′UTR, or CDS) is challenging. In this paper, we analyzed a set of human miRNAs to uncover their general patterns. We began with a sequence logo to verify conservation at specific positions. To discover long-range correlations, we employed chaos game representation (CGR) and genomatrix, methods that enable both graphical and analytical analysis of sequence sets and are well-established in bioinformatics. Our results showed that miRNAs exhibit strongly non-random and characteristic patterns. To incorporate physicochemical properties into the analysis, we applied the electron-ion interaction potential (EIIP) parameter. An important part of our study was to validate the division of miRNAs into two parts—seed and puzzle. The seed region is responsible for target binding, while the puzzle region likely interacts with the RISC complex. We estimated duplex binding energy within the 3′UTR, 5′UTR, and CDS regions using the miRanda tool. Based on the median energy distribution, we divided the miRNAs into two subsets, reflecting different patterns in chaos game representation. Interestingly, one subset displayed significant similarity to conserved and highly confidential miRNAs. Our results confirm the low complementarity of miRNA/mRNA interactions and support the functional division of miRNA structure. Additionally, we present findings related to the localization of transcript target sites, which form the basis for further analyses.

Rational design approach to improve the solubility of the β-sandwich domain 1 of a thermophilic protein

The beta-sandwich domain 1 (SD1) of islandisin is a stable thermophilic protein with surface loops that can be redesigned for specific target binding, architecturally comparable to the variable domain of immunoglobulin (IgG). SD1's propensity to aggregate due to incorrect folding and subsequent accumulation in E. coli inclusion bodies limits its use in biotechnological applications. We rationally designed SD1 for improved variants that were expressed in soluble forms in E. coli while maintaining the intrinsic thermal stability of the protein (melting temperature (Tm) = 73). We used FoldX's ΔΔG predictions to find beneficial mutations and aggregation-prone regions (APRs) using Tango. The S26K substitution within protein core residues did not affect protein stability. Among the soluble mutants studied, the S26K/Q91P combination significantly improved the expression and solubility of SD1. We also examined the effects of the surface residue, pH, and concentration on the solubility of SD1. We showed that the surface polarity of proteins had little or no effect on solubility, whereas surface charges played a substantial role. The storage stability of several SD1 variants was impaired at pH values near their pI, and pH levels resulting in highly charged groups. We observed that mutations that create an uneven distribution of charged groups on the SD1 surface could enhance protein solubility by eliminating favorable protein-protein surface charge interactions. Our findings suggest that SD1 is mutationally tolerant to new functionalities, thus providing a novel perspective for the application of rational design to improve the solubility of targeted proteins.

Structure-based design, synthesis, and biological characterization of indolylarylsulfone derivatives as novel human immunodeficiency virus type 1 inhibitors with potent antiviral activities and favorable drug-like profiles.

In the current antiretroviral landscape, continuous efforts are still needed to search for novel chemotypes of human immunodeficiency virus type 1(HIV-1) inhibitors with improved drug resistance profiles and favorable drug-like properties. Herein, we report the design, synthesis, biological characterization, and druggability evaluation of a class of non-nucleoside reverse transcriptase inhibitors. Guided by the available crystallographic information, a series of novel indolylarylsulfone derivatives were rationally discovered via the substituent decorating strategy to fully explore the chemical space of the entrance channel. Among them, compound 11h bearing the cyano-substituted benzyl moiety proved to be the most effective inhibitor against HIV-1 wild-type and mutant strains (EC50 = 0.0039-0.338 μM), being far more potent than or comparable to etravirine and doravirine. Besides, 11h did not exhibit cytotoxicity at the maximum test concentration. Meanwhile, the binding target of 11h was further confirmed to be reverse transcriptase (IC50 = 0.055 μM). Preliminary structure-activity relationship were discussed to guide further optimization work. Molecular docking and dynamics simulation studies were investigated in detail to rationalize the biological evaluation results. Further drug-likeness assessment indicated that 11h possessed excellent physicochemical properties. Moreover, no apparent hERG blockade liability and cytochrome P450 inhibition were observed for 11h. Notably, 11h was characterized by favorable in vitro metabolic stability with moderate clearance rates and long half-lives in human plasma and liver microsomes. Overall, 11h holds great promise as an ideal Anti-HIV-1 lead compound due to its potent antiviral efficacy, low toxicity, and favorable drug-like profiles.

Development of in vitro and in vivo c-Met targeted dual-modal nanoprobes for NIR II fluorescent bioimaging and magnetic resonance imaging of breast carcinoma metastasis

Because of the conventional bioimaging methods, including ultrasound and X-ray examinations often lack accuracy and sensitivity in the early diagnosis, as a heterogeneous subtype of breast cancer, it remains an urgent need to develop efficaciously and sensitively diagnostic drivers of triple negative breast cancer (TNBC). The overexpression of c-mesenchymal epithelial transition-factor (c-Met) is associated with the basal subtype of breast carcinoma and linked with decreased survival rate of TNBC patients. Here, we have synthesized a dual-modal nanoprobe with luminescence imaging in the bio-window of near infrared II region (NIR II, 1000–1700) and magnetic resonance imaging (MRI) performances. After c-Met targeting binding protein decoration, this Fe3O4@mSiO2-ICG/cMBP had outstanding size stability and preeminent biocompatibility. Meaningfully, it presented effective TNBC cells recognition in vitro. Besides, after caudal-vein injection of this nanoprobe, both NIR II luminescence imaging and MRI demonstrated that it can more efficiently concentrated in metastatic TNBC tumors in comparison with Fe3O4@mSiO2-ICG and clinical used Gd-DTPA. Meanwhile, the core–shell nanoprobes also showed negligible toxicity in vivo. All results suggested that our cMBP modified nanocomposite could provide a fascinating and efficient non-invasive diagnostic tool for TNBC detection in clinic.

Methylome-proteome integration after late-life voluntary exercise training reveals regulation and target information for improved skeletal muscle health.

Exercise is a potent stimulus for combatting skeletal muscle ageing. To study the effects of exercise on muscle in a preclinical setting, we developed a combined endurance-resistance training stimulus for mice called progressive weighted wheel running (PoWeR). PoWeR improves molecular, biochemical, cellular and functional characteristics of skeletal muscle and promotes aspects of partial epigenetic reprogramming when performed late in life (22-24months of age). In this investigation, we leveraged pan-mammalian DNA methylome arrays and tandem mass-spectrometry proteomics in skeletal muscle to provide detailed information on late-life PoWeR adaptations in female mice relative to age-matched sedentary controls (n=7-10 per group). Differential CpG methylation at conserved promoter sites was related to transcriptional regulation genes as well as Nr4a3, Hes1 and Hox genes after PoWeR. Using a holistic method of -omics integration called binding and expression target analysis (BETA), methylome changes were associated with upregulated proteins related to global and mitochondrial translation after PoWeR (P=0.03). Specifically, BETA implicated methylation control of ribosomal, mitoribosomal, and mitochondrial complex I protein abundance after training. DNA methylation may also influence LACTB, MIB1 and UBR4 protein induction with exercise - all are mechanistically linked to muscle health. Computational cistrome analysis predicted several transcription factors including MYC as regulators of the exercise trained methylome-proteome landscape, corroborating prior late-life PoWeR transcriptome data. Correlating the proteome to muscle mass and fatigue resistance revealed positive relationships with VPS13A and NPL levels, respectively. Our findings expose differential epigenetic and proteomic adaptations associated with translational regulation after PoWeR that could influence skeletal muscle mass and function in aged mice. KEY POINTS: Late-life combined endurance-resistance exercise training from 22-24months of age in mice is shown to improve molecular, biochemical, cellular and in vivo functional characteristics of skeletal muscle and promote aspects of partial epigenetic reprogramming and epigenetic age mitigation. Integration of DNA CpG 36k methylation arrays using conserved sites (which also contain methylation ageing clock sites) with exploratory proteomics in skeletal muscle extends our prior work and reveals coordinated and widespread regulation of ribosomal, translation initiation, mitochondrial ribosomal (mitoribosomal) and complex I proteins after combined voluntary exercise training in a sizeable cohort of female mice (n=7-10 per group and analysis). Multi-omics integration predicted epigenetic regulation of serine β-lactamase-like protein (LACTB - linked to tumour resistance in muscle), mind bomb 1 (MIB1 - linked to satellite cell and type 2 fibre maintenance) and ubiquitin protein ligase E3 component N-recognin 4 (UBR4 - linked to muscle protein quality control) after training. Computational cistrome analysis identified MYC as a regulator of the late-life training proteome, in agreement with prior transcriptional analyses. Vacuolar protein sorting 13homolog A (VPS13A) was positively correlated to muscle mass, and the glycoprotein/glycolipid associated sialylation enzyme N-acetylneuraminate pyruvate lyase (NPL) was associated to in vivo muscle fatigue resistance.

In Silico Evaluation of Molecular Docking, Molecular Dynamic, and ADME Study of New Nabumetone Schiff Base Derivatives (1,3,4-oxadiazole or 1,3,4-thiadiazole ring) Promising Antiproliferation Action Against Lung Cancer

A total of eight novel Nabumetone Schiff Base Derivatives with 1,3,4-oxadiazole or 1,3,4-thiadiazole rings have been proposed to evaluate their potential effectiveness against the epidermal growth factor receptor (EGFR). Molecular docking was conducted with the crystalline structure of EGFR (code: 4HJO), wherein the eight compounds of Nabumetone Schiff Base Derivatives with 1,3,4-oxadiazole or 1,3,4-thiadiazole ring derivatives docked to determine their binding affinity to the target binding site. Using GOLD software (CCDC) version 5.43, computer predictions were made, and the compounds were designed using ChemDraw version 22.2 (professional version). Subsequently, their selectivity with EGFR was assessed, with erlotinib selected as a control for comparison. In silico ADME studies were conducted, revealing the significant potential for binding, and drug-likeness was assessed using the Swiss ADME website. Additionally, Molecular Dynamic simulations of compound N3 complexes with EGFR were performed using Schrodinger Suite 2023 software for 50 ns, estimating RMSD, RMSF, Ligand-Protein Contacts, and Ligand Torsion Profile results. Result Showing the best binding energy within receptor pocket with a promising activity against EGFR protein receptor. The highest PLP fitness levels were found in compounds N1, N2, and N3 for lung cancer cell protein (89.1, 89.02, and 87.95, respectively, average value), All compounds were found to adhere to Lipinski's rule of five, with high absorption from the gastrointestinal tract (except N4), and none of the proposed compounds were able to pass through the blood-brain barrier. Molecular dynamic result, Mean Protein RMSD 1.8 Å, ligand RMSD 1.6 Å, and RMSF reveals that the protein amino acids interacting with the ligand remain within a distance of less than 1 Å. In conclusion, these findings offer a promising direction for the development of effective treatments for lung cancer

DPPA as a Potential Cell Membrane Component Responsible for Binding Amyloidogenic Protein Human Cystatin C.

A phospholipid bilayer is a typical structure that serves crucial functions in various cells and organelles. However, it is not unusual for it to take part in pathological processes. The cell membrane may be a binding target for amyloid-forming proteins, becoming a factor modulating the oligomerization process leading to amyloid deposition-a hallmark of amyloidogenic diseases-e.g., Alzheimer's disease. The information on the mechanisms governing the oligomerization influenced by the protein-membrane interactions is scarce. Therefore, our study aims to describe the interactions between DPPA, a cell membrane mimetic, and amyloidogenic protein human cystatin C. Circular dichroism spectroscopy and differential scanning calorimetry were used to monitor (i) the secondary structure of the human cystatin C and (ii) the phase transition temperature of the DPPA, during the protein-membrane interactions. NMR techniques were used to determine the protein fragments responsible for the interactions, and molecular dynamics simulations were applied to provide a molecular structure representing the interaction. The obtained data indicate that the protein interacts with DPPA, submerging itself into the bilayer via the AS region. Additionally, the interaction increases the content of α-helix within the protein's secondary structure and stabilizes the whole molecule against denaturation.

Virtual screening and molecular dynamics simulation of natural compounds as potential inhibitors of serine/threonine kinase 16 for anticancer drug discovery.

Serine/threonine kinase 16 (STK 16) is involved in many facets of cellular regulation; activation of STK 16 plays a crucial role in the migration of cancer cells. Therefore, it is a novel target for the discovery of anticancer agents. Herein, virtual screening and dynamics simulation were used to screen a large library of natural compounds against STK 16 using Schrodinger suit 2021-2 and GROMACS 2021.6. The results predicted five molecules with high binding affinity against the target, with NPC132329 (Arcyriaflavin C) and NPC160898 having higher binding affinity and molecular mechanics generalized born surface area (MM/GBSA), suggesting that it is better than the standard inhibitor. The molecular dymanics (MD) simulation studies showed that the STK 16-NPC132329 complex has the lowest root mean square deviation, and STK 16-NPC160898 was the most stable compared with the standard drug and selective STK 16 inhibitor. The minimal fluctuation was observed in the STK 16-NPC132329 and STK 16-NPC160898 complexes based on the root mean square fluctuation trajectory with NPC132329 and NPC160898 forming 2 and 3 hydrogen bonds respectively with the amino acid residue of the target's binding site. Overall, NPC132329 and NPC160898 are better STK 16 inhibitors than the standard drug and selective inhibitor, which can be further studied to discover novel anticancer drugs.

The dual role of CCND1 in heterotopic ossification: A Non-canonical Pathway for Celecoxib treatment

ObjectiveTo explore the effective targets of Celecoxib in the treatment of heterotopic ossification using network pharmacology methods. MethodsPotential molecules related to heterotopic ossification were obtained by retrieving the GEO and CTD databases and intersecting them. Potential binding targets of Celecoxib were acquired from the STITCH database. A protein-protein interaction network was constructed between potential binding targets of Celecoxib and potential related molecules of heterotopic ossification using the STRING database. Molecules in the protein-protein interaction network were further analyzed using GO and KEGG enrichment analysis in R software, followed by enrichment analysis of active molecules in the Celecoxib-heterotopic ossification target dataset. Hub genes were selected based on the “degree” value and enrichment within the protein-protein interaction network. The binding affinity of hub genes to Celecoxib was observed using molecular docking techniques. Finally, in vitro experiments were conducted to validate the effectiveness of hub genes and explore their regulatory role in the progression of heterotopic ossification. Additionally, the therapeutic effect of Celecoxib, which modulates the expression of the hub genes, was investigated in the treatment of heterotopic ossification. Results568 potential molecules related to heterotopic ossification and 76 potential binding targets of Celecoxib were identified. After intersection, 13 potential functional molecules in Celecoxib's treatment of heterotopic ossification were obtained. KEGG analysis suggested pathways such as Rheumatoid arthritis, NF-kappa B signaling pathway, Pathways in cancer, Antifolate resistance, MicroRNAs in cancer play a role in the treatment of heterotopic ossification by Celecoxib. Further enrichment analysis of the 13 potential functional molecules identified 5 hub genes: IL6, CCND1, PTGS2, IGFBP3, CDH1. Molecular docking results indicated that Celecoxib displayed excellent binding affinity with CCND1 among the 5 hub genes. Experimental validation found that CCND1 is highly expressed in the progression of heterotopic ossification, promoting heterotopic ossification in the early stages and inhibiting it in the later stages, with Celecoxib's treatment of heterotopic ossification depending on CCND1. ConclusionIn the process of treating heterotopic ossification with Celecoxib, immune and inflammatory signaling pathways play a significant role. The therapeutic effect of Celecoxib on heterotopic ossification depends on the hub gene CCND1, which plays different roles at different stages of the progression of heterotopic ossification, ultimately inhibiting the occurrence of heterotopic ossification.

VP1 of human and murine noroviruses recognizes glycolipid sulfatide via the P domain.

Noroviruses are a prevalent cause of human viral gastroenteritis, yet the precise mechanisms underlying their infection cycle, particularly their interactions with and entry into cells, remain poorly understood. Human norovirus (HuNoV) primarily targets human small intestinal epithelial cells, within which 3-O-sulfogalactosylceramide (sulfatide) ranks among the most abundant glycosphingolipids (GSLs). While sulfatide involvement in the binding and infection mechanism of several viruses has been documented, its interaction with noroviruses remains underexplored. This study investigated whether noroviruses interact with sulfatide. We found that the recombinant viral capsid protein VP1 of HuNoV (genogroups I and II) and murine norovirus (genogroup V) exhibited robust binding to sulfatide compared with other tested GSLs using enzyme-linked immunosorbent assay, thin-layer chromatography binding assay and real-time quantitative reverse transcription polymerase chain reaction binding assay. VP1 also bound 3-O-sulfated lactosylceramide, which shares the 3-O-sulfated galactose moiety with sulfatide. However, both VP1 and its P domain, identified as the sulfatide-binding domain, exhibited limited binding to structural analogues of sulfatide and other sulfated compounds. These findings suggest a specific recognition of the 3-O-sulfated galactose moiety. Notably, we found that sulfatide is a novel binding target for norovirus particles. Overall, our findings reveal a previously unknown norovirus-sulfatide interaction, proposing sulfatide as a potential candidate for norovirus infection receptors.

Harnessing virus flexibility to selectively capture and profile rare circulating target cells for precise cancer subtyping

The effective isolation of rare target cells, such as circulating tumor cells, from whole blood is still challenging due to the lack of a capturing surface with strong target-binding affinity and non-target-cell resistance. Here we present a solution leveraging the flexibility of bacterial virus (phage) nanofibers with their sidewalls displaying target circulating tumor cell-specific aptamers and their ends tethered to magnetic beads. Such flexible phages, with low stiffness and Young’s modulus, can twist and adapt to recognize the cell receptors, energetically enhancing target cell capturing and entropically discouraging non-target cells (white blood cells) adsorption. The magnetic beads with flexible phages can isolate and count target cells with significant increase in cell affinity and reduction in non-target cell absorption compared to magnetic beads having rigid phages. This differentiates breast cancer patients and healthy donors, with impressive area under the curve (0.991) at the optimal detection threshold (>4 target cells mL−1). Immunostaining of captured circulating tumor cells precisely determines breast cancer subtypes with a diagnostic accuracy of 91.07%. Our study reveals the power of viral mechanical attributes in designing surfaces with superior target binding and non-target anti-fouling.

Affinity-Resolved Size Exclusion Chromatography Coupled to Mass Spectrometry: A Novel Tool to Study the Attribute-and-Function Relationship in Therapeutic Monoclonal Antibodies.

Assessment of critical quality attributes (CQAs) is an important aspect during the development of therapeutic monoclonal antibodies (mAbs). Attributes that affect either the target binding or Fc receptor engagement may have direct impacts on the drug safety and efficacy and thus are considered as CQAs. Native size exclusion chromatography (SEC)-based competitive binding assay has recently been reported and demonstrated significant benefits compared to conventional approaches for CQA identification, owing to its faster turn-around and higher multiplexity. Expanding on the similar concept, we report the development of a novel affinity-resolved size exclusion chromatography-mass spectrometry (AR-SEC-MS) method for rapid CQA evaluation in therapeutic mAbs. This method features wide applicability, fast turn-around, high multiplexity, and easy implementation. Using the well-studied Fc gamma receptor III-A (FcγRIIIa) and Fc interaction as a model system, the effectiveness of this method in studying the attribute-and-function relationship was demonstrated. Further, two case studies were detailed to showcase the application of this method in assessing CQAs related to antibody target binding, which included unusual N-linked glycosylation in a bispecific antibody and Met oxidation in a monospecific antibody, both occurring within the complementarity-determining regions (CDRs).

SARS-CoV-2 spike protein potentiates platelet aggregation via upregulating integrin αIIbβ3 outside-in signaling pathway.

Platelet hyperreactivity is one of the crucial causes of coagulative disorders in patients with COVID-19. Few studies have indicated that integrin αIIbβ3 may be a potential target for spike protein binding to platelets. This study aims to investigate whether spike protein interacts with platelet integrin αIIbβ3 and upregulates outside-in signaling to potentiate platelet aggregation. In this study, we found that spike protein significantly potentiated platelet aggregation induced by different agonists and platelet spreading in vitro. Mechanism studies revealed that spike protein upregulated the outside-in signaling, such as increased thrombin-induced phosphorylation of β3, c-Src. Moreover, using tirofiban to inhibit spike protein binding to αIIbβ3 or using PP2 to block outside-in signaling, we found that the potentiating effect of spike protein on platelet aggregation was abolished. These results demonstrate that SARS-CoV-2 spike protein directly enhances platelet aggregation via integrin αIIbβ3 outside-in signaling, and suggest a potential target for platelet hyperreactivity in patients with COVID-19. HIGHLIGHTS: •Spike protein potentiates platelet aggregation and upregulates αIIbβ3 outside-in signaling. •Spike protein interacts with integrin αIIbβ3 to potentiate platelet aggregation. •Blocking outside-in signaling abolishes the effect of spike protein on platelets.

Comparative Analysis Highlights Uniconazole's Efficacy in Enhancing the Cold Stress Tolerance of Mung Beans by Targeting Photosynthetic Pathways.

Soybean (Glycine max) and mung bean (Vigna radiata) are key legumes with global importance, but their mechanisms for coping with cold stress-a major challenge in agriculture-have not been thoroughly investigated, especially in a comparative study. This research aimed to fill this gap by examining how these two major legumes respond differently to cold stress and exploring the role of uniconazole, a potential stress mitigator. Our comprehensive approach involved transcriptomic and metabolomic analyses, revealing distinct responses between soybean and mung bean under cold stress conditions. Notably, uniconazole was found to significantly enhance cold tolerance in mung bean by upregulating genes associated with photosynthesis, while its impact on soybean was either negligible or adverse. To further understand the molecular interactions, we utilized advanced machine learning algorithms for protein structure prediction, focusing on photosynthetic pathways. This enabled us to identify LOC106780309 as a direct binding target for uniconazole, confirmed through isothermal titration calorimetry. This research establishes a new comparative approach to explore how soybean and mung bean adapt to cold stress, offers key insights to improve the hardiness of legumes against environmental challenges, and contributes to sustainable agricultural practices and food security.

Rational Design, Synthesis And Characterization Of Some Novel Isatin Derivatives As Antitubercular Agents

Drugs are small organic molecules compared to their binding target. They stimulate or inhibit the action of biomolecules, like proteins, providing therapeutic benefits. Drugdesign is the process of developing novel drugs based on understanding biological targets.

Power Through Pressure: How Interconnection Became Part of the EU's Overarching Climate and Energy Policy

AbstractInterconnection is important to attain several important EU climate and energy targets. Drawing on data from 56 stakeholder interviews, stakeholder event participation and document studies, this study enquires as to why electricity interconnection became a part of the EU's overarching climate and energy policy in 2014. The theoretical approaches liberal intergovernmentalism (LI) and the advocacy coalition framework (ACF) are tested complementarily. LI received support: member states, particularly Portugal and Spain, were essential for the outcome. These successfully played the veto card in the high‐level negotiations for the 2030 Climate and Energy Policy Framework, leading to the first inclusion of concrete interconnection targets in it and interconnection becoming a European Commission priority. ACF received partial support: a ‘green’ long‐term, multi‐level advocacy coalition consisting of the renewables industry, environmental organisations and others promoted a binding target for electricity interconnection. This ‘green’ advocacy coalition was instrumental in aiding Portugal and Spain.

Exploring the immune landscape of disulfidptosis in ulcerative colitis and the role of modified gegen qinlian decoction in mediating disulfidptosis to alleviate colitis in mice

Ethnopharmacological relevanceUlcerative colitis (UC), a recurrent inflammatory bowel disease, continues to challenge effective pharmacologic management. Disulfidptosis, a recently identified form of cell death, appears implicated in the progression of various diseases. Scientific studies have demonstrated that Modified Gegen Qinlian decoction (MGQD) alleviates UC symptoms. However, the underlying mechanisms remain inadequately elucidated. Aim of the studyThis study investigated the role of disulfidptosis in UC and explored the potential of MGQD to ameliorate UC by mediating disulfidptosis. MethodsMicroarray data were utilized to identify disulfidptosis-related genes stably expressed in UC, and integrated genomic analyses were conducted to elucidate the landscape of disulfidptosis in UC. Subsequently, C57BL/6J mice were administered 3% dextran sodium sulfate (DSS) to induce experimental colitis and treated with MGQD. Quantitative real-time polymerase chain reaction and immunohistochemical analysis of colonic tissues from colitis mice were performed to validate the microarray data findings. Finally, molecular docking was employed to explore the binding interactions between MGQD components and disulfidptosis biomarkers. ResultsMyosin heavy chain 10 (MYH10) and filamin A (FLNA) were identified as stably expressed in UC, demonstrating high diagnostic value for the disease. Correlation analysis indicated that disulfidptosis-related genes are associated with elevated levels of immune cells in UC. Single gene set enrichment analysis further clarified that these genes might be involved in the pathological processes of UC via immune-related pathways. Subsequent animal experiments revealed that MYH10 and FLNA were significantly upregulated in mice with colitis, a condition reversed by MGQD treatment. Molecular docking results showed that MYH10 and FLNA serve as stable binding targets for the primary components of MGQD. ConclusionsThe study identified a connection between the disulfidptosis-related landscape and immune infiltration in UC, suggesting that MGQD may modulate disulfidptosis by inhibiting MYH10 and FLNA, thereby alleviating UC.

Aptasensors and Advancement in Molecular Recognition Technology

AbstractSynthetic oligonucleic acids known as aptamers exhibit remarkable selectivity and affinity for target recognition and binding. Selected via an iterative process known as “selective evolution of ligands by exponential enrichment” (SELEX), aptamers fold into defined 3D conformations to interact with their targets. The incorporation of aptamers as recognition elements has driven notable progress in biosensors, giving rise to the development of aptasensors. Here, the process of aptamer discovery and the development of various types of aptasensors are summarized. The fundamental design principles of aptasensors are elaborated along with the superiority of aptamers compared to antibodies. The various modes employed by aptasensors, such as structure‐switching design, hybridization chain reaction amplification, enzyme‐assisted recycling, and split aptamer design are examined. Further light is shed on the diverse landscape of aptasensors, their adaptability to different analytes aptasensors as well as their potential to propel advancements in modern biosensor technology. As a nucleic acids‐based biosensor platform, aptasensors poise to become a next generation of sensitive and cost‐effective technology to shape the future of molecular recognition in biosensing.