Binding Affinity Research Articles

Anti-methanogenic effect of pyrogallol in Spirulina platensis – molecular docking and dynamics simulation on methyl-coenzyme M reductase

Methane, along with carbon dioxide and nitrogen oxides, is a key greenhouse gas contributing significantly to the global concern over climate change. This study investigated the anti-methanogenic properties of pyrogallol in Spirulina platensis using molecular docking and dynamics simulation on methyl-coenzyme M reductase (MCR). The Swiss ADME web server was used to identify pyrogallol's absorption, distribution, metabolism, and excretion (ADME) properties. Molecular docking studies were conducted using UCSF Chimera with the Vina script as the executor. The docking results were further analyzed through molecular dynamics simulation using Gromacs-2024. ADME analysis indicated that pyrogallol meets Lipinski’s Rule of Five. Docking studies revealed that pyrogallol has a binding affinity of 4.6 kJ/mol with 2 hydrogen bonds and 1 hydrophobic interaction. Additionally, the MCR-pyrogallol simulation results showed fluctuating root mean square deviation (RMSD) values that stabilized at t = 26,200 until the end of the simulation with an average value of 2.50 nm. Moreover, the hydrogen bonds formed during the simulation fluctuated, with no bonds observed for more than 75% of the simulation time. The energy released during the simulation reached –300.24 kJ/mol with an average of –5.19 kJ/mol. In conclusion, the pyrogallol compound in Spirulina plantensis can potentially inhibit the MCR enzyme, thereby reducing methane production and mitigating the impact of climate change.

Biological characterisation and computational conformation dynamics of putative L-glutaminase YLaM identified from Bacillus licheniformis

ABSTRACT Glutaminases are a unique group of hydrolytic enzymes with potential applications in cancer therapy and the food industry. This study focused on the biological characterisation and computational conformation dynamics of YLaM, a potential L-glutaminase from a halothermotolerant Bacillus licheniformis. The research integrated experimental and computational methods to identify the YLaM sequence and predict its structural and functional properties. YLaM was amplified using a polymerase chain reaction, cloned into a pET-22b(+) vector, sequenced, and submitted to BankIt/NCBI. This experimental work was complemented by in silico analysis, including structural modelling via the I-TASSER web server, molecular docking using AutoDockTools 1.5.6, and molecular dynamic (MD) simulations using GROMACS v5.1.4. The study resulted in the development of a high-quality 3D model of YLaM through homology modelling and structural refinement, enabling a detailed exploration of its binding affinity with L-glutamine (L-Gln). By identifying active site residues using the homotetramer structure of human glutaminase, crucial interactions with L-Gln were validated, confirming its catalytic function. Finally, MD simulations confirmed the stability of the complex under physiological conditions. This combined molecular identification and functional simulations provide comprehensive insights into the physicochemical properties of the enzyme, offering valuable information for subsequent assessments, including recombinant production and biological impact evaluations.

Alzheimer’s Disease Immunotherapy and Mimetic Peptide Design for Drug Development: Mutation Screening, Molecular Dynamics, and a Quantum Biochemistry Approach Focusing on Aducanumab::Aβ2–7 Binding Affinity

Alzheimer’s Disease Immunotherapy and Mimetic Peptide Design for Drug Development: Mutation Screening, Molecular Dynamics, and a Quantum Biochemistry Approach Focusing on Aducanumab::Aβ2–7 Binding Affinity

Synthesis and in Vitro Antileishmanial Efficacy of Novel Ethylene Glycol Analogues of Benzothiadiazine‐1,1‐dioxide

Leishmaniasis is a vector‐borne, parasitic disease affecting millions of people and animals worldwide. Current therapeutic options have proven to be ineffective in both treating the disease and preventing its spread. As a result, new drugs must be developed to effectively combat this disease. In this study, a series of 14 ethylene glycol analogues of benzothiadiazine‐1,1‐dioxide were synthesised to investigate their antileishmanial potential and cytotoxicity. Analogue 9, 2‐(2‐phenoxyethyl)‐2H‐benzo[e][1,2,4]thiadiazine‐1,1‐dioxide, was identified as the most inhibitory compound as it was observed to moderately inhibit the growth of L. major (IC50 103 µM) and L. donovani (IC50 153 µM) promastigotes. However, in general, the series presented with low biological activity, which may be attributed to reduced target affinity and/or undesired cell culture protein binding.

Identification of New Angiotensin-Converting Enzyme Inhibitory Peptides Isolated from the Hydrolysate of the Venom of Nemopilema nomurai Jellyfish

Recently, jellyfish venom has gained attention as a promising reservoir of pharmacologically active compounds, with potential applications in new drug development. In this investigation, novel peptides, isolated from the hydrolysates of Nemopilema nomurai jellyfish venom (NnV), demonstrate potent inhibitory activities against angiotensin-converting enzyme (ACE). Proteolytic enzymes—specifically, papain and protamex—were utilized for the hydrolysis under optimized enzymatic conditions, determined by assessing the degree of hydrolysis through the ninhydrin test. Comparative analyses revealed that papain treatment exhibited a notably higher degree of NnV hydrolysis compared to protamex treatment. ACE inhibitory activity was quantified using ACE kit-WST, indicating a substantial inhibitory effect of 76.31% for the papain-digested NnV crude hydrolysate, which was validated by captopril as a positive control. The separation of the NnV-hydrolysate using DEAE sepharose weak-anion-exchange chromatography revealed nine peaks under a 0–1 M NaCl stepwise gradient, with peak no. 3 displaying the highest ACE inhibition of 96%. The further purification of peak no. 3 through ODS-C18 column reverse-phase high-performance liquid chromatography resulted in five sub-peaks (3.1, 3.2, 3.3, 3.4, and 3.5), among which 3.2 exhibited the most significant inhibitory activity of 95.74%. The subsequent analysis of the active peak (3.2) using MALDI–TOF/MS identified two peptides with distinct molecular weights of 896.48 and 1227.651. The peptide sequence determined by MS/MS analysis revealed them as IVGRPLANG and IGDEPRHQYL. The docking studies of the two ACE-inhibitory peptides for ACE molecule demonstrated a binding affinity of −51.4 ± 2.5 and −62.3 ± 3.3 using the HADDOCK scoring function.

Mayer-homology learning prediction of protein-ligand binding affinities

Mayer-homology learning prediction of protein-ligand binding affinities

An in silico molecular docking and simulation study to identify potential anticancer phytochemicals targeting the RAS signaling pathway

The dysregulation of the rat sarcoma (RAS) signaling pathway, particularly the MAPK/ERK cascade, is a hallmark of many cancers, leading to uncontrolled cellular proliferation and resistance to apoptosis-inducing treatments. Dysregulation of the MAPK/ERK pathway is common in various cancers including pancreatic, lung, and colon cancers, making it a critical target for therapeutic intervention. Natural compounds, especially phytochemicals, offer a promising avenue for developing new anticancer therapies due to their potential to interfere with these signaling pathways. This study investigates the potential of anticancer phytochemicals to inhibit the MAPK/ERK pathway through molecular docking and simulation techniques. A total of 26 phytochemicals were screened from an initial set of 340 phytochemicals which were retrieved from Dr. Duke’s database using in silico methods for their binding affinity and stability. Molecular docking was performed to identify key interactions with ERK2, followed by molecular dynamics (MD) simulations to evaluate the stability of these interactions. The study identified several phytochemicals, including luteolin, hispidulin, and isorhamnetin with a binding score of -10.1±0 Kcal/mol, -9.86±0.15 Kcal/mol, -9.76±0.025 Kcal/mol, respectively as promising inhibitors of the ERK2 protein. These compounds demonstrated significant binding affinities and stable interactions with ERK2 in MD simulation studies up to 200ns, particularly at the active site. The radius of gyration analysis confirmed the stability of these phytochemical-protein complexes’ compactness, indicating their potential to inhibit ERK activity. The stability and binding affinity of these compounds suggest that they can effectively inhibit ERK2 activity, potentially leading to more effective and less toxic cancer treatments. The findings underscore the therapeutic promise of these phytochemicals, which could serve as a basis for developing new cancer therapies.

Designing of a chimeric multiepitope vaccine against bancroftian lymphatic filariasis through immunoinformatics approaches

The filarial worms of Wuchereria bancrofti are the primary cause of lymphatic filariasis (LF), a mosquito-borne disease among the neglected tropical parasitic diseases. Considering the global endemic consequences of the disease, there is a need to develop a successful vaccine candidate against LF. Using advanced immunoinformatics approaches, we designed two multiepitope vaccines targeting W. bancrofti’s glutathione S-transferase and thioredoxin. Therefore, we predicted several MHC-1, MHC-2, and B-cell epitopes from these proteins and mapped two vaccine candidates (V1 and V2). The vaccines were subsequently employed for physicochemical analysis, structural prediction and validation, docking and normal mode analysis, codon optimization, and immune simulation. The selected MHC-1, MHC-2, and B-cell epitopes were antigenic without allergenicity or toxicity. The designed vaccines were expected to be soluble, stable proteins under physiological conditions. Compared to V2, V1’s secondary and tertiary structures were simultaneously favorable, with Ramachandran plot analysis revealing 95.6% residues in favored areas. Subsequently, the molecular docking analysis indicated that the V1 had a high binding affinity for the TLR-2, TLR-4 and TLR-5, as suggested by the docking scores of -1248.7, -1038.5 and -1562.8, respectively. The NMA of these complexes further indicated their structural flexibility. Molecular dynamics simulations of V1-TLR complexes revealed V1-TLR-4 as the most stable, with the lowest free energy and minimal fluctuations, indicating the strongest binding affinity. The results of the codon optimization showed high levels of expression, with a favorable CAI score (<1.0). A three-dose vaccination analysis showed significant and persistent immunological responses, including adaptive and innate immune responses. The findings emphasize the potential of the V1 against W. bancrofti, but further validation is required through in vitro, in vivo, and clinical trials.

Chemical Profiling, In Silico Pharmacokinetics Analysis and Molecular Docking Study of Phytocompounds of Homeopathy Medicine Echinacea angustifolia Q against Suppurative Bacterial Proteins

Background Computer-aided drug design is the emerging field for identification of drug action on its target organs. The pharmacokinetic study helps find out drug ADMET (absorption, distribution, metabolism, excretion, and toxicity) and drug likeness properties. PyRx software helps with molecular docking of the bioactive compounds on their target organ within a short period of time. In homeopathy, Echinacea angustifolia is one of the most commonly used drugs for microbial infective skin lesions used in internal administration as well as an external application. Objective This study was aimed at identifying the compounds present in Echinacea angustifolia Q through liquid chromatography mass spectrometry (LC-MS), ADMET, and drug likeness properties, followed by molecular docking by PyRx software to recognize the interaction between drug compounds against 12 target microbial proteins of commonly infective suppurative bacteria. Materials and Methods An analysis of the phytoconstituents of Echinacea angustifolia Q was performed using the Agilent 1290 Infinity LC system coupled to the Agilent 6545 Accurate Mass Quadrupole Time-of-Flight (QTOF) with Agilent Jet Stream Thermal Gradient Technology. In silico ADMET and drug likeness properties were assessed by free online tools, followed by a detailed docking study by PyRx software. The drug compounds with the lower glide docking score are considered to have the best binding affinity. Result The five compounds of Echinacea angustifolia Q satisfy all properties of ADMET and drug likeness. The three compounds of Echinacea angustifolia Q have low glide score of >-7.0 kcal/mol against the three microbial target proteins of Salmonella enterica, Proteus mirabilis, and Staphylococcus aureus. Conclusion Echinacea angustifolia Q has fulfilled the ADMET and drug-likeness properties for internal administration as well as external application for various suppurative bacterial infective disorders, which were confirmed through molecular docking. Therefore, Echinacea angustifolia Q may function as a potential therapeutic agent for the treatment of illnesses associated with antimicrobial resistance.

Emerging severe acute respiratory syndrome coronavirus 2 variants and their impact on immune evasion and vaccine-induced immunity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants harboring mutations in the structural protein, especially in the receptor binding domain (RBD) of spike protein, have raised concern about potential immune escape. The spike protein of SARS-CoV-2 plays a vital role in infection and is an important target for neutralizing antibodies. The mutations that occur in the structural proteins, especially in the spike protein, lead to changes in the virus attributes of transmissibility, an increase in disease severity, a notable reduction in neutralizing antibodies generated and thus a decreased response to vaccines and therapy. The observed multiple mutations in the RBD of the spike protein showed immune escape because it increases the affinity of spike protein binding with the ACE-2 receptor of host cells and increases resistance to neutralizing antibodies. Cytotoxic T-cell responses are crucial in controlling SARS-CoV-2 infections from the infected tissues and clearing them from circulation. Cytotoxic Tcells efficiently recognized the infected cells and killed them by releasing soluble mediator's perforin and granzymes. However, the overwhelming response of Tcells and, subsequently, the overproduction of inflammatory mediators during severe infections with SARS-CoV-2 may lead to poor outcomes. This review article summarizes the impact of mutations in the spike protein of SARS-CoV-2, especially mutations of RBD, on immunogenicity, immune escape and vaccine-induced immunity, which could contribute to future studies focusing on vaccine design and immunotherapy.

An in vitro and machine learning framework for quantifying serum albumin binding of per- and polyfluoroalkyl substances

Abstract Per- and polyfluoroalkyl substances (PFAS) are a diverse class of anthropogenic chemicals; many are persistent, bioaccumulative, and mobile in the environment. Worldwide, PFAS bioaccumulation causes serious adverse health impacts, yet the physiochemical determinants of bioaccumulation and toxicity for most PFAS are not well understood, largely due to experimental data deficiencies. As most PFAS are proteinophilic, protein binding is a critical parameter for predicting PFAS bioaccumulation and toxicity. Among these proteins, human serum albumin (HSA) is the predominant blood transport protein for many PFAS. We previously demonstrated the utility of an in vitro differential scanning fluorimetry assay for determining relative HSA binding affinities for 24 PFAS. Here, we report HSA affinities for 65 structurally diverse PFAS from 20 chemical classes. We leverage these experimental data, and chemical/molecular descriptors of PFAS, to build 7 machine learning classifier algorithms and 9 regression algorithms, and evaluate their performance to identify the best predictive binding models. Evaluation of model accuracy revealed that the top performing classifier model, logistic regression, had an AUROC statistic of 0.936. The top performing regression model, support vector regression, had an R2 of 0.854. These top performing models were then used to predict HSA-PFAS binding for chemicals in the EPAPFASINV list of 430 PFAS. These developed in vitro and in silico methodologies represent a high-throughput framework for predicting protein-PFAS binding based on empirical data, and generate directly comparable binding data of potential use in predictive modeling of PFAS bioaccumulation and other toxicokinetic endpoints.

Development of Biolayer Interferometry (BLI)-Based Double-Stranded RNA Detection Method with Application in mRNA-Based Therapeutics and Vaccines

Background: In vitro-transcribed (IVT) mRNA has been established as a promising platform for therapeutics and vaccine development. Double-stranded RNA (dsRNA) is a major impurity of IVT mRNA and can trigger unfavored immune responses, potentially causing adverse events in patients. Existing dsRNA detection and quantitation methods, such as gel electrophoresis, ELISA, or homogeneous time-resolved fluorescence (HTRF), have low sensitivity or are time-consuming. A recently published lateral flow immunoassay (LFSA) was shown to be fast, but it lacks the sensitivity for dsRNA with uridine modifications. Methods: In this study, we provided a possible explanation for the reduced sensitivity of existing quantitation methods for dsRNA with modified uridines by characterizing the binding affinities of commonly used anti-dsRNA antibodies. Then, a rapid and sensitive biolayer interferometry (BLI) dsRNA detection assay utilizing Flock House Virus (FHV) B2 protein was developed to overcome the challenges in dsRNA detection and the reduced sensitivity. Results: This assay allows the detection of dsRNA with different uridine modifications (ψ, m1ψ, 5 moU) with similar sensitivity as dsRNA without modification. Furthermore, we demonstrated this method can be used to quantify both short and long dsRNA, as well as hairpin-structured dsRNA, providing a more comprehensive detection for dsRNA impurities. Moreover, we applied this assay to monitor dsRNA removal through a purification process. Conclusions: Taken together, this BLI method could enable real-time monitoring of impurities in IVT mRNA production to prevent immunogenicity stemming from dsRNA.

Network Pharmacology and Molecular Docking Analysis of Morinda citrifolia Fruit Metabolites Suggest Anxiety Modulation through Glutamatergic Pathways

The fruit of Morinda citrifolia, also known as the noni tree, has been extensively used in Polynesian culture as an alternative medicine to various diseases. Recent studies have pointed out its anxiolytic activity in vitro and in mouse models. Despite the effectiveness of developed anxiolytic drugs in the market, the potential side effects of these medications have led people to resort to traditional medicine such as M. citrifolia. However, evidence regarding its anti-anxiety characteristics is still lacking to this day. Hence, this preliminary study implemented combined network pharmacology and molecular docking to validate its anti-anxiety claims. This study highlighted the bioactive compounds of the M. citrifolia fruit part to have excellent absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, particularly their outstanding oral bioavailability and blood–brain barrier penetration, both of which are essential considerations to ensure the effectiveness of anxiolytic drugs to arrive at the site of action. Moreover, noni fruit metabolites target genes involved in glutamatergic synapse pathways, which have been significantly associated with anxiety. Through molecular docking, selected compounds exhibited a strong binding affinity towards GRIA2 and PRKCA, both of which have connections with glutamatergic pathways. With all things considered, the results established that the noni fruit potentially contains therapeutic agents that elicit anti-anxiety potential. Through this, the promotion of a more sustainable, accessible, and affordable treatment of anxiety could be developed.

Structure-inclusive similarity based directed GNN: A method that can control information flow to predict drug-target binding affinity.

Exploring the association between drugs and targets is essential for drug discovery and repurposing. Comparing with the traditional methods that regard the exploration as a binary classification task, predicting the drug-target binding affinity can provide more specific information. Many studies work based on the assumption that similar drugs may interact with the same target. These methods constructed a symmetric graph according to the undirected drug similarity or target similarity. Although these similarities can measure the difference between two molecules, it is unable to analyze the inclusion relationship of their substructure. For example, if drug A contains all the substructures of drug B, then in the message-passing mechanism of the graph neural network, drug A should acquire all the properties of drug B, while drug B should only obtain some of the properties of A. To this end, we proposed a structure-inclusive similarity (SIS) which measures the similarity of two drugs by considering the inclusion relationship of their substructures. Based on SIS, we constructed a drug graph and a target graph, respectively, and predicted the binding affinities between drugs and targets by a graph convolutional network-based model. Experimental results show that considering the inclusion relationship of the substructure of two molecules can effectively improve the accuracy of the prediction model. The performance of our SIS-based prediction method outperforms several state-of-the-art methods for drug-target binding affinity prediction. The case studies demonstrate that our model is a practical tool to predict the binding affinity between drugs and targets. Source codes and data are available at https://github.com/HuangStomach/SISDTA. Supplementary data are available at Bioinformatics online.

Rotaxane Formation from Borate Ion-Containing Crown Ether and Ammonium Ion: Enhancement of Their Association through Ion-Pairing.

We synthesized [2]rotaxanes featuring a catechol borate ion-containing crown ether and secondary ammonium ions. These rotaxane components show both ion-ion interactions and hydrogen bonds. X-ray crystallography and NMR spectroscopy allowed elucidation of the rotaxane structure. Moreover, 1H NMR spectroscopy revealed the rotaxane synthesis can be thermodynamically controlled. The binding affinity between the borate-containing crown ether and ammonium ions is enhanced by ion-pairing.

Discovery of novel MLK4 inhibitors against colorectal cancer through computational approaches

Colorectal cancer (CRC) is a significant health issue globally, affecting approximately 10 % of the world's population. The prevalence of CRC highlights the need for effective treatments and prevention strategies. The current therapeutic option, such as chemotherapy, has significant side effects. Thus, this study investigated the anticancer properties of Sanguinarine derivatives, an alkaloid found in traditional herbs via chemoinformatic approaches. Six Sanguinarine derivatives were discovered through virtual screening and molecular docking to determine their binding affinities against the mixed lineage kinase (MLK4) protein which is responsible for CRC. All the compounds were found to be more effective than standard drug used for colorectal cancer treatment, with Sanguinarine derivative 11 showing the highest affinity. The stability of the drug was confirmed through molecular dynamics simulations at 500 ns. This suggests that compound 11 has a higher chance of replacing 5-Fluorouracil, which is currently a widely used chemotherapy drug. Before molecular dynamics simulations, the pharmacokinetic and chemical properties of Sanguinarine derivatives were determined using pkCSM server and DFT method, respectively. The results support that compound 11 is a good drug candidate, as evidenced by Lipinski's Rule of Five. Therefore, compound 11 is recommended for further analysis via in vivo and in vitro studies to confirm its efficacy and safety.

Manifold Fluorescence Enhancement of a Styryl(pyridinium)-chromene Hybrid Dye upon Binding with an Elongated β-Cyclodextrin Cavity.

The interaction of a styryl(pyridinium)-chromene hybrid dye (DSP-C) with the 2-hydroxypropyl-β-cyclodextrin (HPβCD) macrocycle leads to a remarkably large increase (∼310-fold) in its fluorescence intensity, in contrast to the relatively smaller (∼45-fold) enhancement observed with native β-cyclodextrin (βCD). Both macrocycles (βCD and HPβCD) bind with the styryl(pyridinium) as well as the chromene fragments of the hybrid dye, with the simultaneous formation of 1:1 and 2:1 host:guest complexes. However, the binding constant (Keq1) is more than an order of magnitude higher for HPβCD than for βCD. The improved binding affinity of HPβCD is attributed to its elongated and deeper hydrophobic cavity. This is supported well by the optimized geometries of the host-guest complexes. Theoretical calculations also reveal that the energy change due to the release of high-energy water molecules from the host nanocavity is more favorable for HPβCD than βCD, resulting in greater stability of the HPβCD:DSP-C complex. Interestingly, though the fluorescence of DSP-C arises from its styryl(pyridinium) fragment, the complexation of the chromene unit with the host plays a major role in augmenting the fluorescence enhancement of the hybrid dye. The large fluorescence change in the HPβCD:DSP-C system has been utilized for the detection of bile salts by the indicator displacement strategy.

Downregulation of APN1 and ABCC2 mutation in Bt Cry1Ac-resistant Trichoplusia ni are genetically independent.

The resistance to the insecticidal protein Cry1Ac from the bacterium Bacillus thuringiensis (Bt) in the cabbage looper, Trichoplusia ni, has previously been identified to be associated with a frameshift mutation in the ABC transporter ABCC2 gene and with altered expression of the aminopeptidase N (APN) genes APN1 and APN6, shown as missing of the 110-kDa APN1 (phenotype APN1¯) in larval midgut brush border membrane vesicles (BBMV). In this study, genetic linkage analysis identified that the APN1¯ phenotype and the ABCC2 mutation in Cry1Ac-resistant T. ni segregated independently, although they were always associated under Cry1Ac selection. The ABCC2 mutation and APN1¯ phenotype were separated into two T. ni strains respectively. Bioassays of the T. ni strains with Cry1Ac determined that the T. ni with the APN1¯ phenotype showed a low level resistance to Cry1Ac (3.5-fold), and the associated resistance is incompletely dominant in the background of the ABCC2 mutation. Whereas the ABCC2 mutation-associated resistance to Cry1Ac is at a moderate level, and the resistance is incompletely recessive in the genetic background of downregulated APN1. Analysis of Cry1Ac binding to larval midgut BBMV indicated that the midgut in larvae with the APN1¯ phenotype had reduced binding affinity for Cry1Ac, but the number of binding sites remained unchanged, and the midgut in larvae with the ABCC2 mutation had both reduced binding affinity and reduced number of binding sites for Cry1Ac. The reduced Cry1Ac binding to BBMV from larvae with the ABCC2 mutation or APN1¯ phenotype correlated with the lower levels of resistance.IMPORTANCEThe soil bacterium Bacillus thuringiensis (Bt) is an important insect pathogen used as a bioinsecticide for pest control. Bt genes coding for insecticidal proteins are the primary transgenes engineered into transgenic crops (Bt crops) to confer insect resistance. However, the evolution of resistance to Bt proteins in insect populations in response to exposure to Bt threatens the sustainable application of Bt biotechnology. Cry1Ac is a major insecticidal toxin utilized for insect control. Genetic mechanisms of insect resistance to Cry1Ac are complex and require to be better understood. The resistance to Cry1Ac in Trichoplusia ni is associated with a mutation in the ABCC2 gene and also associated with the APN expression phenotype APN1¯. This study identified the genetic independence of the APN1¯ phenotype from the ABCC2 mutation and isolated and analyzed the ABCC2 mutation-associated and APN1¯ phenotype-associated resistance traits in T. ni to provide new insights into the genetic mechanisms of Cry1Ac resistance in insects.

Piperine’s potential in treating polycystic ovarian syndrome explored through in-silico docking

Polycystic Ovarian Syndrome (PCOS) is a multifaceted metabolic and hormonal condition that impacts women in their procreative ages, identified by ovarian dysfunction, hyperandrogenaemia overweight and insulin insensitivity. The piperine, an important alkaloid compound of black pepper has shown promise in modulating various physiological processes. In this work, employed computational docking studies to explore the potential of piperine as a treatment for PCOS. Utilizing computational methods, we analyzed the binding interactions between piperine and key molecular targets implicated in PCOS pathogenesis, including hyperandrogenism, and “oligomenorrhea. The network pharmacology analysis report found 988 PCOS-related genes, 108 hyperandrogenism-related genes, and 377 oligomenorrhea-related genes, and we finally shortlisted 5 common genes in PCOS, hyperandrogenism, and “oligomenorrhea”: NR3C1, PPARG, FOS, CYP17A1, and H6PD. Our results reveal favorable binding affinities with PPARG (-8.34 Kcal/mol) and H6PD (-8.70 Kcal/mol) and interaction patterns, suggesting the potential of piperine to modulate these targets. Moreover, the reliability of the piperine-target interactions was revealed by molecular simulations studies. These findings support further experimental investigations to validate the therapeutic efficacy of piperine in PCOS management. The integration of computational approaches with experimental studies has the potential to lay the groundwork for the creation of new therapies specifically targeting PCOS and related endocrine disorders.

Mesothelin- and nucleolin-specific T cells from combined short peptides effectively kill triple-negative breast cancer cells

BackgroundTriple-negative breast cancer (TNBC), known for its aggressiveness and limited treatment options, presents a significant challenge. Adoptive cell transfer, involving the ex vivo generation of antigen-specific T cells from peripheral blood mononuclear cells (PBMCs), emerges as a promising approach. The overexpression of mesothelin (MSLN) and nucleolin (NCL) in TNBC samples underscores their potential as targets for T cell therapy. This study explored the efficacy of multi-peptide pulsing of PBMCs to generate MSLN/NCL-specific T cells targeting MSLN+/NCL+ TNBC cells.MethodsTNBC patient samples were confirmed for both MSLN and NCL expression via immunohistochemistry. Synthesized MSLN and NCL peptides were combined and administered to activate PBMCs from healthy donors. The cancer-killing ability of the resultant T cells was assessed using crystal violet staining, and their subtypes and cytotoxic cytokines were characterized through flow cytometry and cytokine bead array.ResultsFindings showed that 85.3% (127/149) of TNBC cases were positive for either MSLN or NCL, or both; with single positivity rates for MSLN and NCL of 14.1% and 28.9%, respectively. MSLN and NCL peptides, with high binding affinity for HLA-A*02, were combined and introduced to activated PBMCs from healthy donors. The co-pulsed PBMCs significantly induced TEM and TEMRA CD3+/CD8+ T cells and IFN-γ production, compared to single-peptide pulsed or unpulsed conditions. Notably, MSLN/NCL-specific T cells successfully induced cell death in MSLN+/NCL+ MDA-MB-231 cells, releasing key cytotoxic factors such as perforin, granzymes A and B, Fas ligand, IFN-γ, and granulysin.ConclusionsThese findings serve as a proof-of-concept for using multiple immunogenic peptides as a novel therapeutic approach in TNBC patients.