Subsequent Experimental Validation Research Articles

Phase-field based shape optimization of uni- and multiaxially loaded nature-inspired porous structures while maintaining characteristic properties

AbstractTriply periodic minimal surfaces (TPMS) are highly versatile porous formations that can be defined by formulas. Computationally based, load-specific shape optimization enables tailoring these structures for their respective application areas and thereby enhance their potential. In this investigation, individual sheet-based gyroid structures with varying porosities are specifically optimized with respect to their stiffness. A modified phase-field method is employed to establish a simulation framework for the shape optimization process. Despite constant volume and the preservation of the periodicity of the unit cells, volume redistribution occurs through displacement of the interfaces. The phase-field-based optimization process is detailed using unidirectional loading on three gyroidal unit cells with porosities of 75 %, 80 %, and 85 %. Subsequently, the gyroidal unit cell with a porosity of 85 % is shape-optimized under multidirectional loading. A subsequent experimental validation of the unidirectionally loaded cells confirms that the shape-optimized structures exhibit, on average, higher stiffness than the non-optimized structures. The highest increase of 40 % in effective modulus is achieved with the gyroid structure having a porosity of 75 %, while maintaining minimal alteration to the surface-to-volume ratio and preserving periodicity. Additionally, the experimental data show that the optimization process resulted in a shift in the linear elasticity and plasticity range. In summary, the phase-field method proves to be a valid optimization technique for complex porous structures, allowing the preservation of characteristic properties.

In Silico Identification of Promising PDE5 Inhibitors Against Hepatocellular Carcinoma Among Natural Derivatives: A Study Involving Docking and ADMET Analysis.

Hepatocellular carcinoma (HCC) represents a significant worldwide health challenge due to its high mortality rate, underscoring the need for advanced therapeutic strategies. This study employs a computer-based method to identify potential phosphodiesterase 5 (PDE5) inhibitors from a library of approved IBS_Scaff 532 natural compounds. PDE5 inhibitors have gained attention for their potential anti-tumor effects. Using molecular docking simulations, the researchers assessed how well these compounds bind to the PDE5 enzyme, which regulates cellular cGMP pathways. Additionally, ADMET profiling predicted the pharmacological and safety properties of candidate inhibitors. Notably, compounds like IBS_NC-0322 and IBS_NC-0320 exhibited favorable ADMET properties and strong binding affinities. These findings suggest their potential as therapeutic agents for treating HCC. While in silico methods serve as valuable screening tools, subsequent experimental validation and clinical trials are essential for confirmation.

Synthesis and Characterization of CaO nanoparticles from Periwinkle shell for the Treatment of Tetracycline-contaminated Water by Adsorption and Photocatalyzed Degradation

Due to the ever-increasing discharge of antibiotic residues into different water bodies, there is a significant need to improve existing water treatment methods. In this study, we synthesized calcium oxide nanoparticles from periwinkle shells using the sol-gel method for applications in the adsorption and photodegradation of tetracycline from wastewater. The nanoparticles were characterized using FTIR, UV-Visble spectroscopy, XRD, SEM-EDX, TEM, BET and TGA/DTA. The nanostructure produced showed strong crystalline, optical, structural and surface properties. With an average crystallite size of 25 nm, particle size of 2.09 nm, BET surface area of 582.68 m2/g, specific surface area of 90.08 m2/g, bandgap of 4.8 eV and other properties that supported their functionality as adsorbent and photocatalyst for the removal of tetracycline residue from water. The adsorption experiment gave a maximum efficiency of about 80% while the photodegradation catalysed by the nanoparticles indicated efficiency up to 97%. Both adsorption and photodegradation showed strong dependency on pH, tetracycline concentration, catalyst load and concentration of KI. Response surface analysis and subsequent experimental validation indicated that degradation approaching 100% for tetracycline is feasible under optimum conditions involving concentration = 500 ppm, time = 50 min, catalyst load = 1.25 g and KI concentration = 0.25 M. Computational calculations gave results that are in good match with experimental data and further proved that the degradation is limited by adsorption and is majorly controlled by oxidation facilitated by O2*.

Engineering inhibitory repeat domains of Pin-II type proteinase inhibitors indicate their high structural-functional tolerance to mutagenesis

Plant proteinase inhibitors (PIs) are critical in defending against biotic stress. Most PIs contain an inhibitory repeat domain (IRD), which serves as the functional component, displaying a high degree of sequence and structural conservation. In this study, we examined the structural and functional resilience of IRDs using a combination of computational modeling and experimental validation. We have taken an evolution-based approach to enhance the PIs effectiveness of two previously identified Capsicum annuum IRDs, IRD4 and IRD10. Through in silico site-saturation mutagenesis of IRD4 and IRD10, we identified key sites associated with enhanced PI activity for targeted mutagenesis. Binding energy predictions for a mutant IRD library, tested against target proteases, suggested that positions R11 and N32 in IRD4 and N32 and H33 in IRD10 were promising candidates for further modification to improve inhibitory potential. Subsequent experimental validation revealed that the mutant proteins IRD4_R11K and IRD4_N32S exhibited stronger chymotrypsin inhibition than the wild-type (WT) IRD4. Similarly, the mutants IRD10_N32S and IRD10_H33 N demonstrated improved trypsin inhibition relative to the WT IRD10. These findings indicate that engineered IRD variants can tolerate structural changes while maintaining or enhancing their inhibitory activity against target proteases. Overall, this study demonstrates the potential of engineering PIs to increase their structural and functional resilience, offering new opportunities for biotechnological applications.

Unveiling the Anticancer Potential: Computational Exploration of Nitrogenated Derivatives of (+)-Pancratistatin as Topoisomerase I Inhibitors.

Cancer poses a substantial global health challenge, driving the need for innovative therapeutic solutions that offer improved effectiveness and fewer side effects. Topoisomerase I (Topo I) has emerged as a validated molecular target in the pursuit of developing anticancer drugs due to its critical role in DNA replication and transcription. (+)-Pancratistatin (PST), a naturally occurring compound found in various Amaryllidaceae plants, exhibits promising anticancer properties by inhibiting Topo I activity. However, its clinical utility is hindered by issues related to limited chemical availability and aqueous solubility. To address these challenges, molecular modelling techniques, including virtual screening, molecular docking, molecular mechanics with generalised born and surface area solvation (MM-GBSA) calculations, and molecular dynamics simulations were utilised to evaluate the binding interactions and energetics of PST analogues with Topo I, comparing them with the well-known Topo I inhibitor, Camptothecin. Among the compounds screened for this study, nitrogenated analogues emerged as the most encouraging drug candidates, exhibiting improved binding affinities, favourable interactions with the active site of Topo I, and stability of the protein-ligand complex. Structural analysis pinpointed key molecular determinants responsible for the heightened potency of nitrogenated analogues, shedding light on essential structural modifications for increased activity. Moreover, in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions highlighted favourable drug-like properties and reduced toxicity profiles for the most prominent nitrogenated analogues, further supporting their potential as effective anticancer agents. In summary, this screening study underscores the significance of nitrogenation in augmenting the anticancer efficacy of PST analogues targeting Topo I. The identified lead compounds exhibit significant potential for subsequent experimental validation and optimisation, thus facilitating the development of novel and efficacious anticancer therapeutics with enhanced pharmacological profiles.

SNRPB2 in the pan-cancer landscape: A bioinformatics exploration and validation in hepatocellular carcinoma

Aberrant splicing is a significant contributor to gene expression abnormalities in cancer. SNRPB2, a component of U2 small nuclear ribonucleoprotein particles (snRNPs), contributes to the assembly of the spliceosome, the molecular machinery responsible for splicing. To date, few studies have investigated the role of SNRPB2 in tumorigenesis. We examined data sourced from various public databases, such as The Cancer Genome Atlas(TCGA), the Clinical Proteomic Tumor Analysis Consortium(CPTAC), and Gene Expression Omnibus(GEO). Our investigation included gene expression, genomic and epigenomic scrutiny, gene set enrichment assessment(GSEA), and immune cell infiltration evaluation. Furthermore, we performed empirical validation to ascertain the impact of SNRPB2 suppression on the proliferation and migration of liver cancer cells. Analysis of gene expression revealed widespread upregulation of SNRPB2 across a spectrum of cancer types, with heightened levels of SNRPB2 expression in numerous tumors linked to unfavorable prognosis. Genomic and epigenomic assessments revealed connections between SNRPB2 expression and variations in SNRPB2 copy number, DNA methylation patterns, and RNA modifications. Through gene set enrichment analysis, the involvement of SNRPB2 in vital biological processes and pathways related to cancer was identified. Furthermore, scrutiny of immune cell infiltration suggested a potential relationship between SNRPB2 and the tumor microenvironment, which was reinforced by multiple single-cell sequencing profiles. Subsequent experimental validation revealed that silencing SNRPB2 effectively impeded the proliferation and migration of liver cancer cells. Taken together, these findings underscore the prospective utility of SNRPB2 as a prognostic biomarker and a promising candidate for immunotherapy in cancer. It is necessary to engage in additional exploration into its underlying mechanisms and clinical treatment potential.

Cratoxylum formosum ssp. pruniflorum induces gastric cancer cell apoptosis and pyroptosis through the elevation of ROS and cell cycle arrest.

Cratoxylum formosum ssp. pruniflorum (CF), a traditional medicinal plant in Southern China, is widely recognized as a popular medicinal and tea plant traditionally utilized by diverse linguistic groups in the region for the treatment of gastrointestinal ailments. The objective of this study was to explore the active components and mechanisms of CF against gastric cancer (GC). The chemical ingredients of CF were obtained by using UPLC-MS/MS-based metabolomics. MGC-803 and HGC-27 cells were employed to investigate the direct anti-GC effect. The potential targets and signaling pathway of CF were identified through network pharmacology and proteomics, followed by subsequent experimental validation. Through UPLC-MS/MS metabolomics analysis, a total of 197 chemical ingredients were identified in CF leaves. Network pharmacology and proteomics techniques revealed 25 potential targets for GC, with a protein-protein interaction (PPI) network highlighting 12 cores targets, including CTNNB1, CDK2, et al. Furthermore, seven key CF ingredients - vismione B, feruloylcholine, α-amyrin, vanillic acid, galangin, cinnamic acid, and caffeic acid - were found to mediate anti-GC effects through pathways such as reactive oxygen species (ROS) and cell cycle signaling pathway. In vitro experiments demonstrated that CF significantly inhibited the proliferation and migration of GC cells, increased intracellular reactive oxygen species (ROS), malondialdehyde (MDA) and lactate dehydrogenase (LDH) levels, arrested the cell cycle at the S-phase, induced apoptosis and pyroptosis, and upregulated expression of apoptosis proteins (Bax, Bax/Bcl-2, cleaved-Caspase-3/Caspase-3), and pyroptosis proteins (GSDMD-N/GSDMD and GSDME-N/GSDME), while downregulating expression of cell cycle proteins (CDK2 and cyclin A1) as well as necroptosis proteins (RIP1 and MLKL). Collectively, these findings reveal CF's therapeutic potential against GC by the augmentation of ROS production, cell cycle arrest, promotion of apoptosis, and pyroptosis, offering valuable evidence for the development and utilization of CF in clinical settings.

Therapeutic potential of Nelumbo nucifera Linn. in systemic lupus erythematosus: Network pharmacology and molecular modeling insights.

Systemic lupus erythematosus is a chronic autoimmune inflammatory disease characterized by multiple symptoms. The phenolic acids and other flavonoids in Nelumbo nucifera have anti-oxidants, anti-inflammatory, and immunomodulatory activities that are essential for managing SLE through natural sources. This study employs network pharmacology to unveil the multi-target and multi-pathway mechanisms of Nelumbo nucifera as a complementary therapy. The findings are validated through molecular modeling, which includes molecular docking followed by a molecular dynamics study. Active compounds and targets of SLE were obtained from IMPPAT, KNApAcKFamily and SwissTargetPrediction databases. SLE-related targets were retrieved from GeneCards and OMIM databases. A protein-protein interaction (PPI) network was built to screen out the core targets using Cytoscape software. ShinyGO was used for GO and KEGG pathway enrichment analyses. Interactions between potential targets and active compounds were assessed by molecular docking and molecular dynamics simulation study. In total, 12 active compounds and 1190 targets of N. nucifera's were identified. A network analysis of the PPI network revealed 10 core targets. GO and KEGG pathway enrichment analyses indicated that the effects of N. nucifera are mediated mainly by AGE-RAGE and other associated signalling pathways. Molecular docking indicated favourable binding affinities, particularly leucocianidol exhibiting less than -4.5kcal/mol for all 10 targets. Subsequent molecular dynamics simulations of the leucocianidol-ESR1 complex aimed to elucidate the optimal binding complex's stability and flexibility. Our study unveiled the potential therapeutic mechanism of N. nucifera in managing SLE. These findings provide insights for subsequent experimental validation and open up new avenues for further research in this field.

Rational Design of a Triple-Layered Coaxial Extruder System: in silico and in vitro Evaluations Directed Toward Optimizing Cell Viability.

Biofabrication is a rapidly evolving field whose main goal is the manufacturing of three-dimensional (3D) cell-laden constructs that closely mimic tissues and organs. Despite recent advances on materials and techniques directed toward the achievement of this goal, several aspects such as tissue vascularization and prolonged cell functionality are limiting bench-to-bedside translation. Extrusion-based 3D bioprinting has been devised as a promising biofabrication technology to overcome these limitations, due to its versatility and wide availability. Here, we report the development of a triple-layered coaxial nozzle for use in the biomanufacturing of vascular networks and vessels. The design of the coaxial nozzle was first optimized toward guaranteeing high cell viability upon extrusion. This was done with the aid of in silico evaluations and their subsequent experimental validation by investigating the bioprinting of an alginate-based bioink. Results confirmed that the values for pressure distribution predicted by in silico experiments resulted in cell viabilities above 70% and further demonstrated the effect of layer thickness and extrusion pressure on cell viability. Our work paves the way for the rational design of multi-layered coaxial extrusion systems to be used in biofabrication approaches to replicate the very complex structures found in native organs and tissues.

Inference of essential genes in Brugia malayi and Onchocerca volvulus by machine learning and the implications for discovering new interventions

Detailed explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have substantially improved our knowledge and understanding of biological processes and pathways in metazoan organisms. Extensive functional genomic and multi-omic data sets have enabled the discovery and characterisation of ‘essential’ genes that are critical for the survival of these organisms. Recently, we showed that a machine learning (ML)-based pipeline could be utilised to predict essential genes in both C. elegans and D. melanogaster using features from DNA, RNA, protein and/or cellular data or associated information. As these distantly-related species are within the Ecdysozoa, we hypothesised that this approach could be suited for non-model organisms within the same group (phylum) of protostome animals. In the present investigation, we cross-predicted essential genes within the phylum Nematoda – between C. elegans and the parasitic filarial nematodes Brugia malayi and Onchocerca volvulus, and then ranked and prioritised these genes. Highly ranked genes were linked to key biological pathways or processes, such as ribosome biogenesis, translation and RNA processing, and were expressed at relatively high levels in the germline, gonad, hypodermis and/or nerves. The present in silico workflow is hoped to expedite the identification of drug targets in parasitic organisms for subsequent experimental validation in the laboratory.

Huanglian Jiedu decoction alleviates ischemia-induced cerebral injury in rats by mitigating NET formation and activiting GABAergic synapses.

Huanglian Jiedu decoction (HLJD) has been used to treat ischemic stroke in clinic. However, the detailed protective mechanisms of HLJD on ischemic stroke have yet to be elucidated. The aim of this study is to elucidate the underlying pharmacological mechanisms of HLJD based on the inhibition of neuroinflammation and the amelioration of nerve cell damage. A middle cerebral artery occlusion reperfusion (MCAO/R) model was established in rats and received HLJD treatment. Effects of HLJD on neurological function was assessed based on Bederson's score, postural reflex test and asymmetry score. 2, 3, 5-Triphenyltetrazolium chloride (TTC) staining, Hematein and eosin (HE) and Nissl staining were used to observe the pathological changes in brain. Then, transcriptomics was used to screen the differential genes in brain tissue in MCAO/R model rats following HLJD intervention. Subsequently, the effects of HLJD on neutrophil extracellular trap (NET) formation-related neuroinflammation, gamma-aminobutyric acid (GABA)ergic synapse activation, nerve cell damage and proliferation were validated using immunofluorescence, western blot and enzyme-linked immunosorbent assay (ELISA). Our results showed that HLJD intervention reduced the Bederson's score, postural reflex test score and asymmetry score in MCAO/R model rats. Pathological staining indicated that HLJD treatment decreased the cerebral infarction area, mitigated neuronal damage and increased the numbers of Nissl bodies. Transcriptomics suggested that HLJD affected 435 genes in MCAO/R rats. Among them, several genes involving in NET formation and GABAergic synapses pathways were dysregulated. Subsequent experimental validation showed that HLJD reduced the MPO+CitH3+ positive expression area, reduced the protein expression of PAD4, p-P38/P38, p-ERK/ERK and decreased the levels of IL-1β, IL-6 and TNF-α, reversed the increase of Iba1+TLR4+, Iba1+p65+ and Iba1+NLRP3+ positive expression area in brain. Moreover, HLJD increased GABA levels, elevated the protein expression of GABRG1 and GAT3, decreased the TUNEL positive expression area and increased the Ki67 positive expression area in brain. HLJD intervention exerts a multifaceted positive impact on ischemia-induced cerebral injury in MCAO/R rats. This intervention effectively inhibits neuroinflammation by mitigating NET formation, and concurrently improves nerve cell damage and fosters nerve cell proliferation through activating GABAergic synapses.

Identification of Selective JAK3/STAT1 and CYP34A from Pyrazolopyrimidine Derivatives: A Search for Potential Drug Targets for Rheumatoid Arthritis using In-silico Drug Discovery Techniques

Objective: This study aimed to discover a novel active compound capable of effectively inhibiting JAK3/STAT1 and CYP3A4 using molecular modelling techniques, with the goal of treating autoimmune diseases such as cancer and specifically rheumatoid arthritis. The study involved modelling compounds derived from pyrazolopyrimidine, followed by screening methods to identify the most promising compounds. Moreover, this study seeks to identify potential compounds that can inhibit JAK3/STAT through molecular modelling techniques and validate the stability and affinity of the predicted molecule. Methods: Various molecular modelling techniques were employed to identify potential compounds and assess the stability and affinity of the predicted molecule. A pharmacophore hypothesis was developed to obtain crucial information about the experimental series of pyrazolopyrimidine studied, which served as the basis for designing new molecules. Additionally, ADMET was utilized to predict and evaluate the pharmacokinetic properties and potential toxicity of the compound prior to synthesis or utilization. To determine the essential residues involved in the interaction between the molecule and the target JAK3 protein, the covalent docking method was applied. We further validated the binding stability of the JAK3 protein with the ligands ZINC62162141 and Tofacitinib, both of which have been approved by the FDA for JAK3/STAT inhibition., using DFT/B3LYP/6-31G molecular dynamics simulations lasting 1000 ns and MM/GBSA. Results: During the study, we identified compounds that displayed notable activity against JAK3/STAT, specifically those containing thiadiazol, oxadiazol, and chlorophenyl groups. Additionally, the pharmacophore model, ADRRR_1, exhibited promising potential for predicting new molecules. The predicted compound, ZINC62162141, demonstrated favourable ADMET properties, including inhibition of CYP3A4. Furthermore, we assessed its binding stability to the target protein and determined its affinity for the protein-ligand complex using MMGBSA. Conclusion: The results of this study suggest that the compounds identified have the potential to be promising candidates for inhibiting JAK3/STAT and CYP3A4, offering potential therapeutic benefits for the treatment of rheumatoid arthritis. These findings provide a foundation for subsequent experimental validation and the development of novel drugs in this field.

Comprehensive Analysis of Conserved B-Cell Epitopes in DENV NS1 Protein for Enhanced Rapid Diagnostic Tests Development in Indonesia

Dengue virus (DENV) constitutes a formidable public health threat within tropical and subtropical regions. The escalation of cases in Southeast Asia, notably Indonesia, is a matter of considerable concern. Timely identification of DENV infection remains imperative for efficient disease management. The non-structural protein-1 (NS1), distinguished by its heightened immunogenicity and early detectability during infection, stands as a pivotal target for diagnostic modalities. The current investigation delves into the exploration of B-cell epitopes within Indonesian DENV NS1 protein isolates, with the overarching objective of enhancing the sensitivity and specificity of early detection systems, such as the Rapid Diagnostic Test (RDT). This study has successfully delineated five B-cell epitopes that exhibit conservation across DENV serotypes within Indonesian isolates (accessions number: QBB90021.1, QBE90252.1, QBB90023.1, and UDW38833.1). These epitopes were discerned through comprehensive screening leveraging the IEDB platforms. Noteworthy variations in antigenicity, allergenicity, and toxicity profiles were observed among these identified epitopes. Molecular docking analysis substantiated a robust binding affinity between the predicted epitope and the B-cell receptor. The ensuing in silico protein-peptide docking analyses offer valuable insights into potential B-cell epitopes on the Indonesian DENV NS1 protein. The identified epitopes, particularly the SQHNYRPGY epitope characterized by its antigenic potency and non-allergenic attributes, hold promise for advancing the development of sensitive and specific RDTs tailored for DENV detection in the Indonesian context. However, it is imperative to underscore the requisite for subsequent experimental validation to affirm the efficacy of these epitopes in diagnostic applications.

Optimization of Quartz Sand-Enhanced Coagulation for Sewage Treatment by Response Surface Methodology.

The quartz sand-enhanced coagulation (QSEC) is an improved coagulation method for treating water, which uses quartz sand as a heavy medium to accelerate the sedimentation rate of flocs and reduce the sedimentation time. The factors that influence the QSEC effect and can be controlled manually include the quartz sand dosage, coagulant dosage, sewage pH, stirring time, settling time, etc., and their reasonable setting is critical to the result of water treatment. This paper aimed to study the optimal conditions of QSEC; first, single-factor tests were conducted to explore the optimal range of influencing factors, followed by response surface methodology (RSM) tests to accurately determine the optimum values of significant factors. The results show that the addition of quartz sand did not improve the water quality of the coagulation treatment, it took only 140 s for the floc to sink to the bottom, and the sediment volume only accounted for 12.2% of the total sewage. The quartz sand dosage, the coagulant dosage, and sewage pH all had a significant impact on the coagulation effect, and resulted in inflection points. A QSEC-guiding model was derived through RSM tests, and subsequent model optimization and experimental validation revealed the optimal conditions for treating domestic sewage as follows: the polyaluminum chloride (PAC) dosage, cationic polyacrylamide (CPAM) dosage, the sewage pH, quartz sand dosage, stirring time, and settling time were 0.97 g/L, 2.25 mg/L, 7.22, 2 g/L, 5 min, and 30 min, respectively, and the turbidity of the treated sewage was reduced to 1.15 NTU.

Abstract A021: Hunting for synthetic lethal partners in DNA damage response-altered endometrial cancer

Abstract DNA damage response (DDR) genes are frequently altered in cancer, which may lead to protein loss-of-function (LoF) and result in particular DDR defects that can be therapeutically targeted via the concept of synthetic lethality (SL). There is a high prevalence of DDR alterations in endometrial cancer, a gynecologic malignancy with increased incidence and mortality in recent decades, and an unmet clinical need for a wider range of treatment options to reduce adverse effects and combat therapy resistance. In this study, a large-scale, agnostic bioinformatic screening approach was employed to discover novel potential SL targets specific to DDR LoF biomarkers in endometrial cancer for subsequent experimental validation in vitro. SL analysis was performed with the in-house Target / Biomarker / Lineage (TBL) bioinformatic pipeline (Division of Cancer Therapeutics, The Institute of Cancer Research) using datasets obtained from the Cancer Dependency Map (DepMap). The TBL pipeline statistically analyzed cancer cell line target gene dependency probabilities, inferred from Project Achilles and Project Score genome-wide CRISPR-Cas9 dropout screens, and integrated this with mutation and copy number variation genomic datasets. Potential interactions were filtered for target-biomarker mutual exclusivity using patient data from The Cancer Genome Atlas (TCGA). The ability of the TBL pipeline to identify known SL interactions was demonstrated through in silico identification of ARID1B/ARID1A in ovarian cancer and SMARCA2/SMARCA4 in lung cancer as significant hits. In addition, the identification of WRN/ARID1A as a significant hit in uterine cancer, given that ARID1A loss has been significantly associated with microsatellite instability (MSI) in endometrial cancer, is consistent with previous findings of WRN helicase as a SL partner with MSI in endometrial cancer. Analysis and downstream refinement of endometrial cancer significant hits led to the identification of seven final candidate target-biomarker gene pairs. These putative SL partners comprise novel potential endometrial cancer targets, with various functions ranging from nucleotide biosynthesis to epigenetic remodeling, and include novel potential and established LoF biomarkers relevant to endometrial cancer biology, namely DNA mismatch repair. In vitro validation of the final candidates by genetic or pharmacologic approaches to assess target gene dependency in endometrial cancer cell lines with altered or wildtype biomarker status will be discussed. These experiments will provide key experimental data to validate our bioinformatic approach to SL target-biomarker discovery, and may identify novel SL partners involving DDR LoF alterations in endometrial cancer that could lead to the development of new molecular targeted therapies and improved treatment options for this patient subpopulation. Citation Format: Julie Zhou, Konstantinos Mitsopoulos, Olivia Rossanese. Hunting for synthetic lethal partners in DNA damage response-altered endometrial cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A021.

Advancing thermal stability analysis of haloperidol: Integrative approaches and optimization strategies for enhanced pharmaceutical formulations

This study investigates the thermal stability of haloperidol, a crucial pharmaceutical compound, employing a multidimensional approach encompassing UV spectrometry, thermal degradation studies, kinetics analysis, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and differential scanning calorimetry (DSC). The UV spectrometry method demonstrates exceptional linearity across a concentration range of 2–34 µg/ml, meeting stringent industry standards. Thermal degradation studies affirm the compound's stability when exposed to 80°C for 6 h. Kinetic analysis indicates a first-order reaction for the degradation process, with activation energy values suggesting a sluggish degradation profile under diverse heat stress conditions. FTIR analysis underscores the consistency of haloperidol's molecular structure across varying temperatures, while XRD confirms the retention of its crystalline form even under heat stress. DSC analysis unveils a melting temperature of 150°C, indicative of initial melting preceding degradation. Response surface methodology (RSM) optimization identifies the conservation conditions effects (temperature and time)to minimize degradation, a finding substantiated by predictions from the Improved Grey Wolf Optimization (IGWO) algorithm and subsequent experimental validation. Furthermore, a bespoke MATLAB application is developed to streamline and enhance the accuracy of the complex optimization processes. This tool offers advanced features for predicting and optimizing haloperidol degradation rates, catering to the needs of both researchers and industry professionals. In essence, this study not only sheds light on the thermal stability of haloperidol but also provides practical tools and insights crucial for optimizing its stability under diverse environmental conditions, thereby bolstering its pharmaceutical applicability and efficacy.

In Vitro Analysis of Camellia sinensis Leaf Extract Against Diabetes Mellitus.

Diabetes mellitus (DM) poses a significant global health challenge, with its prevalence steadily increasing. Natural compounds derived from plants have garnered attention for their potential therapeutic effects in managing this metabolic disorder. Camellia sinensis, commonly known as tea, is rich in bioactive compounds exhibiting various pharmacological properties. This study investigates the potential anti-diabetic activity of C. sinensis leaf extract through in vitro analysis. Camella sinensisleaf extract was prepared by grinding the plant's leaf into a powder, mixing it with distilled water, and heating. The antidiabetic activity was assessed through α-Amylase and α-Glucosidase inhibitory assays, employing varying concentrations of the plant extract. Molecular docking analysis utilized Autodock 1.5.6 software (The Scripps Research Institute, California, US)to predict ligand-receptor interactions, guiding subsequent experimental validation. Camella sinensisleaf extract exhibited high phenolic content, suggesting potential in managing hyperglycemia. Tannins may aid glucose absorption and inhibit adipogenesis, making them promising for non-insulin-dependent DM (NIDDM). Terpenoids, with antioxidant activity, inhibit advanced glycation. Saponins and steroids were absent. Molecular docking revealed residues like IR, IRS1, and AS160 with significant impact on α-Amylase and α-Glucosidase, comparable to metformin. The findings of this study highlight the promising potential of C. sinensis leaf extract in managing hyperglycemia associated with DM. The high phenolic content aids in glucose regulation. Specifically, the presence of tannins suggests a potential role in modulating glucose absorption and inhibiting adipogenesis, which could be particularly beneficial for individuals with NIDDM.These findings provide valuable insights into the molecular mechanisms underlying the potential therapeutic efficacy of C. sinensis leaf extract against DM, paving the way for further research and development of novel therapeutic interventions in diabetes management.

Discovery and in vitro Evaluation of Novel Serotonin 5-HT2A Receptor Ligands Identified Through Virtual Screening.

The 5-HT2A receptor is a molecular target of high pharmacological importance. Ligands of this protein, particularly atypical antipsychotics, are useful in the treatment of numerous mental disorders, including schizophrenia and major depressive disorder. Structure-based virtual screening using a 5-HT2A receptor complex was performed to identify novel ligands for the 5-HT2A receptor, serving as potential antidepressants. From the Enamine screening library, containing over 4 million compounds, 48 molecules were selected for subsequent experimental validation. These compounds were tested against the 5-HT2A receptor in radioligand binding assays. From the tested batch, six molecules were identified as ligands of the main molecular target and were forwarded to a more detailed in vitro profiling. This included radioligand binding assays at 5-HT1A, 5-HT7, and D2 receptors and functional studies at 5-HT2A receptors. These compounds were confirmed to show a binding affinity for at least one of the targets tested in vitro. The success rate for the inactive template-based screening reached 17 %, while it was 9 % for the active template-based screening. Similarity and fragment analysis indicated the structural novelty of the identified compounds. Pharmacokinetics for these molecules was determined using in silico approaches.

The Bioactive Compounds of Epimedium and Their Potential Mechanism of Action in Treating Osteoporosis: A Network Pharmacology and Experimental Validation Study.

Osteoporosis is a global health challenge characterized by bone loss and microstructure deterioration, which urgently requires the development of safer and more effective treatments due to the significant adverse effects and limitations of existing drugs for long-term treatment. Traditional Chinese medicine, like Epimedium, offers fewer side effects and has been used to treat osteoporosis, yet its active compounds and pharmacological mechanisms remain unclear. In this study, 65 potential active compounds, 258 potential target proteins, and 488 pathways of Epimedium were identified through network pharmacology analysis. Further network analysis and review of the literature identified six potential active compounds and HIF-1α for subsequent experimental validation. In vitro experiments confirmed that 2″-O-RhamnosylIcariside II is the most effective compound among the six potential active compounds. It can promote osteoblast differentiation, bind with HIF-1α, and inhibit both HIF-1α gene and protein expression, as well as enhance COL1A1 protein expression under hypoxic conditions. In vivo experiments demonstrated its ability to improve bone microstructures and reduce bone loss by decreasing bone marrow adipose tissue, enhancing bone formation, and suppressing HIF-1α protein expression. This study is the first to describe the therapeutic effects of 2-O-RhamnosylIcariside II on osteoporosis, which was done, specifically, through a mechanism that targets and inhibits HIF-1α. This study provides a scientific basis for the clinical application of Epimedium and offers a new candidate drug for the treatment of osteoporosis. Additionally, it provides new evidence supporting HIF-1α as a therapeutic target for osteoporosis.

Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization’s 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand–protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.