Targeting of multiple tumor-associated antigens by individual T cell receptors during successful cancer immunotherapy.

The T cells of the immune system can target tumors and clear solid cancers following tumor-infiltrating lymphocyte (TIL) therapy. We used combinatorial peptide libraries and a proteomic database to reveal the antigen specificities of persistent cancer-specific T cell receptors (TCRs) following successful TIL therapy for stage IV malignant melanoma. Remarkably, individual TCRs could target multiple different tumor types via the HLA A∗02:01-restricted epitopes EAAGIGILTV, LLLGIGILVL, and NLSALGIFST from Melan A, BST2, and IMP2, respectively. Atomic structures of a TCR bound to all three antigens revealed the importance of the shared x-x-x-A/G-I/L-G-I-x-x-x recognition motif. Multi-epitope targeting allows individual T cells to attack cancer in several ways simultaneously. Such "multipronged" T cells exhibited superior recognition of cancer cells compared with conventional T cell recognition of individual epitopes, making them attractive candidates for the development of future immunotherapies.

Emergence of immune escape at dominant SARS-CoV-2 killer T cell epitope.

We studied the prevalent cytotoxic CD8 T cell response mounted against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike glycoprotein269-277 epitope (sequence YLQPRTFLL) via the most frequent human leukocyte antigen (HLA) class I worldwide, HLA A∗02. The Spike P272L mutation that has arisen in at least 112 different SARS-CoV-2 lineages to date, including in lineages classified as "variants of concern," was not recognized by the large CD8 T cell response seen across cohorts of HLA A∗02+ convalescent patients and individuals vaccinated against SARS-CoV-2, despite these responses comprising of over 175 different individual T cell receptors. Viral escape at prevalent T cell epitopes restricted by high frequency HLAs may be particularly problematic when vaccine immunity is focused on a single protein such as SARS-CoV-2 Spike, providing a strong argument for inclusion of multiple viral proteins in next generation vaccines and highlighting the need for monitoring T cell escape in new SARS-CoV-2 variants.

Twisted van der Waals Quantum Materials: Fundamentals, Tunability, and Applications.

Twisted van der Waals (vdW) quantum materials have emerged as a rapidly developing field of two-dimensional (2D) semiconductors. These materials establish a new central research area and provide a promising platform for studying quantum phenomena and investigating the engineering of novel optoelectronic properties such as single photon emission, nonlinear optical response, magnon physics, and topological superconductivity. These captivating electronic and optical properties result from, and can be tailored by, the interlayer coupling using moiré patterns formed by vertically stacking atomic layers with controlled angle misorientation or lattice mismatch. Their outstanding properties and the high degree of tunability position them as compelling building blocks for both compact quantum-enabled devices and classical optoelectronics. This paper offers a comprehensive review of recent advancements in the understanding and manipulation of twisted van der Waals structures and presents a survey of the state-of-the-art research on moiré superlattices, encompassing interdisciplinary interests. It delves into fundamental theories, synthesis and fabrication, and visualization techniques, and the wide range of novel physical phenomena exhibited by these structures, with a focus on their potential for practical device integration in applications ranging from quantum information to biosensors, and including classical optoelectronics such as modulators, light emitting diodes, lasers, and photodetectors. It highlights the unique ability of moiré superlattices to connect multiple disciplines, covering chemistry, electronics, optics, photonics, magnetism, topological and quantum physics. This comprehensive review provides a valuable resource for researchers interested in moiré superlattices, shedding light on their fundamental characteristics and their potential for transformative applications in various fields.

MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.

RNA modification serves as a pivotal component in numerous biological processes. Among the prevalent modifications, 5-methylcytosine (m5C) significantly influences mRNA export, translation efficiency and cell differentiation and are also associated with human diseases, including Alzheimer's disease, autoimmune disease, cancer, and cardiovascular diseases. Identification of m5C is critically responsible for understanding the RNA modification mechanisms and the epigenetic regulation of associated diseases. However, the large-scale experimental identification of m5C present significant challenges due to labor intensity and time requirements. Several computational tools, using machine learning, have been developed to supplement experimental methods, but identifying these sites lack accuracy and efficiency. In this study, we introduce a new predictor, MLm5C, for precise prediction of m5C sites using sequence data. Briefly, we evaluated eleven RNA sequence-derived features with four basic machine learning algorithms to generate baseline models. From these 44 models, we ranked them based on their performance and subsequently stacked the Top 20 baseline models as the best model, named MLm5C. The MLm5C outperformed the-state-of-the-art predictors. Notably, the optimization of the sequence length surrounding the modification sites significantly improved the prediction performance. MLm5C is an invaluable tool in accelerating the detection of m5C sites within the human genome, thereby facilitating in the characterization of their roles in post-transcriptional regulation.

Idiotopes of antibodies against HIV-1 CD4-induced epitope shared with those against microorganisms.

Induction of antibodies (Abs) against the conformational CD4-induced (CD4i) epitope is frequent in HIV-1 infection. However, the mechanism of development of anti-CD4i Abs is unclear. We used anti-idiotypic (aID) monoclonal Abs (mAbs) of anti-CD4i mAbs to isolate anti-CD4i mAbs from infected subjects and track the causative antigens. One anti-aID mAb sorted from infected subjects by aID mAbs had the characteristics of anti-CD4i Abs, including IGHV1-69 usage and ability to bind to HIV-1 Env enhanced by sCD4. Critical amino acid sequences for the binding of six anti-aID mAbs, with shared idiotope to anti-CD4i mAbs, were analysed by phage display. The identified amino acid sequences showed similarity to proteins from human microbiota and infectious agents. Peptides synthesized from Caudoviricetes sp and Vibrio vulnificus based on the identified sequences were reactive to most anti-aID and some anti-CD4i mAbs. These results suggest that anti-CD4i Abs may evolve from B cells primed by microorganisms.

YRNA and tRNA fragments can differentiate benign from malignant canine mammary gland tumors.

Mammary gland tumors (MGT) are the most common tumors in sexually intact female dogs. The functional regulation of miRNAs, a type of noncoding RNAs (ncRNAs), in canine MGT has been extensively investigated. However, the expression of other ncRNAs, such as YRNAs and transfer RNA-derived fragments (tRFs) in canine MGT is unknown. We investigated ncRNAs other than miRNAs from our small RNA project (PRJNA716131) in different canine MGT histologic subtypes. This study included benign tumors (benign mixed tumor, complex adenoma) and malignant tumors (carcinoma in benign tumor and carcinoma with metastasis) samples. Aberrantly expressed ncRNAs were examined by comparisons among MGT subtypes. The relative expression trends were validated in canine MGT tissues, plasma, extracellular vesicles, and MGT cell lines using quantitative reverse transcription PCR. Three aberrantly expressed ncRNAs were identified by comparisons among MGT subtypes. YRNA and tRNA-Gly-GCC distinguished benign mixed tumor from other MGT histologic subtypes, while tRNA-Val differentiated complex adenoma, carcinoma in benign tumors, and carcinoma with metastasis. The ROC curve of the three ncRNAs showed they might be potential biomarkers to discriminate malignant from benign MGT. YRNA and tRFs expression levels were decreased in metastatic compared with primary canine MGT cell lines. To the best of our knowledge, this is the first investigation of YRNA and tRFs in canine MGT. The three identified ncRNAs may be biomarkers for differentiating MGT histologic subtypes. Suggested Reviewers: Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporatio.

Allelopathic effect of the methanol extract of the weed species-red sorrel (Rumex acetosella L.) on the growth, phytohormone content and antioxidant activity of the cover crop - white clover (Trifolium repens L.).

Allelopathy is a biological process in which one organism releases biochemicals that affect the growth and development of other organisms. The current investigation sought to determine the allelopathic effect of Rumex acetosella on white clover (Trifolium repens) growth and development by using its shoot extract (lower IC50 value) as a foliar treatment. Here, different concentrations (25, 50, 100, and 200 g/L) of shoot extract from Rumex acetosella were used as treatments. With increasing concentrations of shoot extract, the plant growth parameters, chlorophyll and total protein content of Trifolium repens decreased. On the other hand, ROS, such as O2.- and H2O2, and antioxidant enzymes, including SOD, CAT, and POD, increased with increasing shoot extract concentration. A phytohormonal study indicated that increased treatment concentrations increased ABA and SA levels while JA levels were reduced. For the identification of allelochemicals, liquid‒liquid extraction, thin-layer chromatography, and open-column chromatography were conducted using R. acetosella shoot extracts, followed by a seed bioassay on the separated layer. A lower IC50 value was obtained through GC/MS analysis. gammaSitosterol was identified as the most abundant component. The shoot extract of Rumex acetosella has strong allelochemical properties that may significantly impede the growth and development of Trifolium repens. This approach could help to understand the competitive abilities of this weed species and in further research provide an alternate weed management strategy.

A systematic first-principles investigation of the structural, electronic, mechanical, optical, and thermodynamic properties of Half-Heusler ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) for spintronics and optoelectronics applications.

This paper is the first to look at the structural, electronic, mechanical, optical, and thermodynamic properties of the ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) half-Heusler (HH) using DFT based first principles method. The lattice parameters that we have calculated are very similar to those obtained in prior investigations with theoretical and experimental data. The positive phonon dispersion curve confirm the dynamical stability of ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn). The electronic band structure and DOS confirmed that the studied materials ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) are direct band gap semiconductors. The investigation also determined significant constants, including dielectric function, absorption, conductivity, reflectivity, refractive index, and loss function. These optical observations unveiled our compounds potential utilization in various electronic and optoelectronic device applications. The elastic constants were used to fulfill the Born criteria, confirming the mechanical stability and ductility of the solids ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn). The calculated elastic modulus revealed that our studied compounds are elastically anisotropic. Moreover, ANiX (ASc, Ti, Y, Zr, Hf; XBi, Sn) has a very low minimum thermal conductivity (Kmin), and a low Debye temperature (θD), which indicating their appropriateness for utilization in thermal barrier coating (TBC) applications. The Helmholtz free energy (F), internal energy (E), entropy (S), and specific heat capacity (Cv) are determined by calculations derived from the phonon density of states.

Power Scavenging Microsystem for Smart Contact Lenses.

On-the-eye microsystems such as smart contacts for vision correction, health monitoring, drug delivery, and displaying information represent a new emerging class of low-profile (≤ 1 mm) wireless microsystems that conform to the curvature of the eyeball surface. The implementation of suitable low-profile power sources for eye-based microsystems on curved substrates is a major technical challenge addressed in this paper. The fabrication and characterization of a hybrid energy generation unit composed of a flexible silicon solar cell and eye-blinking activated Mg-O2 metal-air harvester capable of sustainably supplying electrical power to smart ocular devices are reported. The encapsulated photovoltaic device provides a DC output with a power density of 42.4 µW cm-2 and 2.5 mW cm-2 under indoor and outdoor lighting conditions, respectively. The eye-blinking activated Mg-air harvester delivers pulsed power output with a maximum power density of 1.3 mW cm-2 . A power management circuit with an integrated 11 mF supercapacitor is used to convert the harvesters' pulsed voltages to DC, boost up the voltages, and continuously deliver ≈150 µW at a stable 3.3 V DC output. Uniquely, in contrast to wireless power transfer, the power pack continuously generates electric power and does not require any type of external accessories for operation.

A Mutagen Acts as a Potent Reducing Agent of Glycated Hemoglobin: a Combined Ultrafast Electron Transfer and Computational Studies.

Glycated hemoglobin (GHb) found in mammals undergoes irreversible damage when exposed to external redox agents, which is much more vulnerable than its normal counterpart hemoglobin (Hb). Besides the oxygen regulation throughout the body, Hb plays a vital role in balancing immunological health and the redox cycle. Photoinduced ultra-fast electron transfer phenomena actively participate in regulation of various kind of homeostasis involved in such biomacromolecules. In the present study we have shown that a well-known mutagen Ethidium Bromide (EtBr) reduces GHb in femtosecond time scale (efficiently) upon photoexcitation after efficient recognition in the biomolecule. We have performed similar experiment by colocalizing EtBr and Iron (Fe(III)) on the micellar surface as Hb mimic in order to study the excited state EtBr dynamics to rationalize the time scale obtained from EtBr in GHb and Hb. While other experimental techniques including Dynamic Light Scattering (DLS), Zeta potential, absorbance and emission spectroscopy have been employed for the confirmation of structural perturbation of GHb compared to Hb, a detailed computational studies involving molecular docking and density functional theory (DFT) have been employed for the explanation of the experimental observations.

PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection.

A newly invented post-translational modification (PTM), phosphoglycerylation, has shown its essential role in the construction and functional properties of proteins and dangerous human diseases. Hence, it is very urgent to know about the molecular mechanism behind the phosphoglycerylation process to develop the drugs for related diseases. But accurately identifying of phosphoglycerylation site from a protein sequence in a laboratory is a very difficult and challenging task. Hence, the construction of an efficient computation model is greatly sought for this purpose. A little number of computational models are currently available for identifying the phosphoglycerylation sites, which are not able to reach their prediction capability at a satisfactory level. Therefore, an effective predictor named PLP_FS has been designed and constructed to identify phosphoglycerylation sites in this study. For the training purpose, an optimal number of feature sets was obtained by fusion of multiple F_Score feature selection techniques from the features generated by three types of sequence-based feature extraction methods and fitted with the support vector machine classification technique to the prediction model. On the other hand, the k-neighbor near cleaning and SMOTE methods were also implemented to balance the benchmark dataset. The suggested model in 10-fold cross-validation obtained an accuracy of 99.22%, a sensitivity of 98.17% and a specificity of 99.75% according to the experimental findings, which are better than other currently available predictors for accurately identifying the phosphoglycerylation sites.

TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization.

Long noncoding RNAs (lncRNAs) are primarily regulated by their cellular localization, which is responsible for their molecular functions, including cell cycle regulation and genome rearrangements. Accurately identifying the subcellular location of lncRNAs from sequence information is crucial for a better understanding of their biological functions and mechanisms. In contrast to traditional experimental methods, bioinformatics or computational methods can be applied for the annotation of lncRNA subcellular locations in humans more effectively. In the past, several machine learning-based methods have been developed to identify lncRNA subcellular localization, but relevant work for identifying cell-specific localization of human lncRNA remains limited. In this study, we present the first application of the tree-based stacking approach, TACOS, which allows users to identify the subcellular localization of human lncRNA in 10 different cell types. Specifically, we conducted comprehensive evaluations of six tree-based classifiers with 10 different feature descriptors, using a newly constructed balanced training dataset for each cell type. Subsequently, the strengths of the AdaBoost baseline models were integrated via a stacking approach, with an appropriate tree-based classifier for the final prediction. TACOS displayed consistent performance in both the cross-validation and independent assessments compared with the other two approaches employed in this study. The user-friendly online TACOS web server can be accessed at https://balalab-skku.org/TACOS.

BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches.

N6-methyladenine (6mA) is associated with important roles in DNA replication, DNA repair, transcription, regulation of gene expression. Several experimental methods were used to identify DNA modifications. However, these experimental methods are costly and time-consuming. To detect the 6mA and complement these shortcomings of experimental methods, we proposed a novel, deep leaning approach called BERT6mA. To compare the BERT6mA with other deep learning approaches, we used the benchmark datasets including 11 species. The BERT6mA presented the highest AUCs in eight species in independent tests. Furthermore, BERT6mA showed higher and comparable performance with the state-of-the-art models while the BERT6mA showed poor performances in a few species with a small sample size. To overcome this issue, pretraining and fine-tuning between two species were applied to the BERT6mA. The pretrained and fine-tuned models on specific species presented higher performances than other models even for the species with a small sample size. In addition to the prediction, we analyzed the attention weights generated by BERT6mA to reveal how the BERT6mA model extracts critical features responsible for the 6mA prediction. To facilitate biological sciences, the BERT6mA online web server and its source codes are freely accessible at https://github.com/kuratahiroyuki/BERT6mA.git, respectively.

Ethylene-mediated stomatal responses to dehydration and rehydration in seed plants.

Ethylene, a plant hormone that significantly influences both plant growth and response to stress, plays a well-established role in stress signaling. However, its impact on stomatal opening and closure during dehydration and rehydration remains relatively unexplored and is still debated. Exogenous ethylene has been proven to induce stomatal closure through a series of signaling pathways, including the accumulation of reactive oxygen species (ROS), subsequent synthesis of nitric oxide (NO) and hydrogen sulfide (H2S), and SLOW ANION CHANNEL-ASSOCIATED 1 (SLAC1) activation. Thus, it has been suggested that ethylene might function to induce stomatal closure synergistically with abscisic acid (ABA). Furthermore, it has also been shown that increased ethylene can inhibit ABA- and jasmonic acid (JA)-induced stomatal closure, thus hindering drought-induced closure during dehydration. Simultaneously, other stresses, such as chilling, ozone pollution and K+ deficiency, inhibit drought and ABA-induced stomatal closure through an ethylene synthesis dependent way. However, ethylene has been shown to take on an opposing role during rehydration, preventing stomatal opening in the absence of ABA through its own signaling pathway. These findings offer novel insights into the function of ethylene in stomatal regulation during dehydration and rehydration, gaining a better understanding of the mechanisms underlying ethylene-induced stomatal movement in seed plants.

Intermittent cytomegalovirus infection alters neurobiological metabolism and induces cognitive deficits in mice.

Risk factors contributing to dementia are multifactorial. Accumulating evidence suggests a role for pathogens as risk factors, but data is largely correlative with few causal relationships. Here, we demonstrate that intermittent murine cytomegalovirus (MCMV) infection of mice, alters blood brain barrier (BBB) permeability and metabolic pathways. Increased basal mitochondrial function is observed in brain microvessels cells (BMV) exposed to intermittent MCMV infection and is accompanied by elevated levels of superoxide. Further, mice score lower in cognitive assays compared to age-matched controls who were never administered MCMV. Our data show that repeated systemic infection with MCMV, increases markers of neuroinflammation, alters mitochondrial function, increases markers of oxidative stress and impacts cognition. Together, this suggests that viral burden may be a risk factor for dementia. These observations provide possible mechanistic insights through which pathogens may contribute to the progression or exacerbation of dementia.

Carbon Nanosheets-Based Supercapacitor Materials: Recent Advances and Prospects.

The need for inexpensive and ecologically sustainable energy storage technologies is rising rapidly along with the severity of the world's environmental challenges as well as with the rising demand for portable electronics and hybrid vehicles. Supercapacitors have drawn a lot of attentions lately in this regard because of their ultrahigh power density, outstanding electrochemical stability, and environmental friendliness. Due to various advantages, carbon materials are the choice of designer for developing commercial electrodes for various applications including devising supercapacitors. Two-dimensional (2D) carbon nanosheets (CNSs) with a large surface area and excellent electronic transport properties have fired up the interest of researchers due to their unique properties and potential applications in energy storage. Such engineered 2D porous CNS may significantly improve the energy storage performance of supercapacitor by enabling fast ion transport and charge transfer kinetics. This article summarizes the most recent and significant advances in the area of activated, porous, graphene-based various CNSs and their composites with a special focus on their use as supercapacitor electrodes. A succinct overview about their syntheses and key characterizations regarding their different structural aspects have been discussed. The present challenges and prospects in using CNS in supercapacitor applications are highlighted.

Ophiobolin A derivatives with enhanced activities under tumor-relevant acidic conditions.

Glioblastoma (GBM) is the most common form of malignant primary brain tumor and is one of the most lethal cancers. The difficulty in treating GBM stems from its highly developed mechanisms of drug resistance. Our research team has recently identified the fungal secondary metabolite ophiobolin A (OpA) as an agent with significant activity against drug-resistant GBM cells. However, the OpA's mode of action is likely based on covalent modification of its intracellular target(s) and thus possible off-target reactivity needs to be addressed. This work involves the investigation of an acid-sensitive OpA analogue approach that exploits the elevated acidity of the GBM microenvironment to enhance the selectivity for tumor targeting. This project identified analogues that showed selectivity at killing GBM cells grown in cultures at reduced pH compared to those maintained under normal neutral conditions. These studies are expected to facilitate the development of OpA as an anti-GBM agent by investigating its potential use in an acid-sensitive analogue form with enhanced selectivity for tumor targeting.

Tobacco industry interference to undermine the development and implementation of graphic health warnings in Bangladesh.

BACKGROUND: In Bangladesh, the 2013 Amendment of the Tobacco Control Act made graphic health warnings (GHWs) on the upper 50% of all tobacco packs obligatory. However, at the time of writing (May 2022), GHWs are still being printed on the lower 50% of packs. This paper seeks to explore how the tobacco industry undermined the development and implementation of GHWs in Bangladesh, a country known for a high level of tobacco industry interference (TII) that has rarely been examined in the peer-reviewed literature. METHODS: Analysis of print and electronic media articles and documents. RESULTS: Cigarette companies actively opposed GHWs, while bidi companies did not. The primary strategy used to influence the formulation and delay the implementation of GHWs was direct lobbying by the Bangladesh Cigarette Manufacturers' Association and British American Tobacco Bangladesh. Their arguments stressed the economic benefits of tobacco to Bangladesh and sought to create confusion about the impact of GHWs, for example, claiming that GHWs would obscure tax banderols, thus threatening revenue collection. They also claimed technical barriers to implementation-that new machinery would be needed-leading to delays. Tensions between government bodies were identified, one of which (National Board of Revenue)-seemingly close to cigarette companies and representing their arguments-sought to influence others to adopt industry-preferred positions. Finally, although tobacco control advocates were partially successful in counteracting TII, one self-proclaimed tobacco control group, whose nature remains unclear, threatened the otherwise united approach. CONCLUSIONS: The strategies cigarette companies used closely resemble key techniques from the well-evidenced tobacco industry playbook. The study underlines the importance of continuing monitoring and investigations into industry conduct and suspicious actors. Prioritising the implementation of WHO Framework Convention on Tobacco Control Article 5.3 is crucial for advancing tobacco control, particularly in places like Bangladesh, where close government-industry links exist.

Prevalence and factors associated with digital addiction among students taking university entrance tests: a GIS-based study.

BACKGROUND: The surge in digital media consumption, coupled with the ensuing consequences of digital addiction, has witnessed a rapid increase, particularly after the initiation of the COVID-19 pandemic. Despite some studies exploring specific technological addictions, such as internet or social media addiction, in Bangladesh, there is a noticeable gap in research focusing on digital addiction in a broader context. Thus, this study aims to investigate digital addiction among students taking the university entrance test, examining its prevalence, contributing factors, and geographical distribution using GIS techniques. METHODS: Data from a cross-sectional survey were collected from a total of 2,157 students who were taking the university entrance test at Jahangirnagar University, Bangladesh. A convenience sampling method was applied for data collection using a structured questionnaire. Statistical analyses were performed with SPSS 25 Version and AMOS 23 Version, whereas ArcGIS 10.8 Version was used for the geographical distribution of digital addiction. RESULTS: The prevalence of digital addiction was 33.1% (mean score: 16.05 ± 5.58). Those students who are attempting the test for a second time were more likely to be addicted (42.7% vs. 39.1%), but the difference was not statistically significant. Besides, the potential factors predicted for digital addiction were student status, satisfaction with previous mock tests, average monthly expenditure during the admission test preparation, and depression. No significant difference was found between digital addiction and districts. However, digital addiction was higher in the districts of Manikganj, Rajbari, Shariatpur, and Chittagong Hill Tract areas, including Rangamati, and Bandarban. CONCLUSIONS: The study emphasizes the pressing need for collaborative efforts involving educational policymakers, institutions, and parents to address the growing digital addiction among university-bound students. The recommendations focus on promoting alternative activities, enhancing digital literacy, and imposing restrictions on digital device use, which are crucial steps toward fostering a healthier digital environment and balanced relationship with technology for students.

Investigating the potent TOPO IIα inhibitors in breast cancer through the study of computational drug discovery research approaches.

Breast cancer (BC) is the second-leading cause of cancer after lung cancer. The disease has affected millions of people and resulted in many deaths. In the metastasis of breast cancer cells, Topoisomerase IIα plays a vital role. Therefore, this investigation aims to identify potential flavonoid compounds against BC by inhibiting this enzyme at an early stage. Based on previous studies, we selected and screened several plant-derived flavonoid compounds with potential anti-breast cancer activity using PyRx 0.8 and Schrodinger applications for preliminary molecular docking: the highest docking scores of Myricetin (-11.6 kcal/mol) and Quercetin (-10.0 kcal/mol). Next, we evaluated the top four compounds on the Way2Drug server to complete the cytotoxicity evaluation, which demonstrated anti-cancer and anti-breast cancer activity in various cell lines. According to pharmacokinetics studies, four compounds exhibited outstanding values and functioned similar to drug-like molecules. Moreover, Myricetin, Quercetin, and Morin displayed the highest number of hydrogen bonds, with the corresponding receptor forming residues asn120, thr147, and lys168. The protein-ligand complexes were validated using the Desmond simulator, and their data were compared to the anti-breast cancer drug Doxorubicin. In the simulation analysis, various parameters were evaluated, including RMSD, RMSF, Rg, SASA, MolSA, PSA, and hydrogen bond interaction. Finally, validated our dynamic simulation result with MM-GBSA operation, and Myricetin and Quercetin had the greatest score of -72.74344651, -66.66771823 kcal/mol, which is outstanding than the control drug. Hence, the computational research approach determined that Myricetin, Quercetin, and Morin could be industrially developed for the alternative treatment of breast cancer following additional confirmation from animal and cell line studies.