Development Of Cancer Therapeutics Research Articles

Evaluating the therapeutic potential of 4-hydroxyflavanes diastereomers derivatives against (MetAP2) for anti-cancer therapy: a molecular docking study

Abstract The 4-hydroxyflavanes are derived from flavanones through a condensation reaction with a primary amine; therefore, the 4-hydroxyflavanes derivatives have been shown to have key biological actions such as aldose reductase inhibition, cancer chemoprevention, antibacterial and anti-inflammatory effects. In this study, we investigated the molecular docking interactions between 2-phenyl-4 (phenylamino)chroman-4-ol, 4-((3-chlorophenyl) amino)-2-phenylchroman-4-ol and 4-((3-methoxyphenyl) amino)-2-phenylchroman-4-ol diastereomers with methionine aminopeptidase II (MetAP2) which is an enzyme that is essential for tissue healing and cancer progression in humans, in order to find novel antiangiogenic agents. The molecular docking program used in this work was Moe software. The binding affinity composed of (MetAP2) with 4-((3-methoxyphenyl) amino)-2-phenylchroman-4-ol diastereomers derivatives (RR, RS, SR, SS) were found to be the most stable, with the free energy of −7.06, −7.85, −7.44, and −7.82 kcal/mol docking score and the RMSD 1.77, 1.24, 1.93 and 1.41 respectively; specifically, the RS configuration. The findings provide insights into the potential efficacy of 4-hydroxyflavanes derivatives as a (MetAP2) inhibitor, which could have implications for the development of novel cancer therapeutics.

A Novel Multicompartment Barrier-Free Microfluidic Device Reveals the Impact of Extracellular Matrix Stiffening and Temozolomide on Immune-Tumor Interactions in Glioblastoma.

The immune system plays a crucial role in shaping the glioblastoma tumor microenvironment, characterized by its complexity and dynamic interactions. Understanding the tumor-immune crosstalk is essential for advancing cancer research and therapeutic development. Here, a novel multicompartment, barrier-free microfluidic device is presented that overcomes the limitations of existing models by enabling direct tumor-immune interactions without physical barriers, preserving natural immune cell infiltration. This platform supports the independent and simultaneous culture of tumor and immune cells, replicating the healthy-tumoral stroma interface, and allows investigating the effect of matrix stiffness and chemotherapy on both populations. The findings reveal that increased collagen concentration promotes tumor invasiveness while impairing immune cell infiltration. Additionally, temozolomide treatment reduces immune cell motility but enhances anti-tumor immune responses. These insights highlight the critical roles of extracellular matrix mechanics and chemotherapy in tumor progression and immune modulation, establishing this device as a powerful tool for studying glioblastoma-immune dynamics and evaluating therapeutic strategies.

Triphenylamine-Naphthalimide-Based "On-Off-On" AIEgen for Imaging Golgi Apparatus and Endoplasmic Reticulum.

Golgi apparatus (GA) and endoplasmic reticulum (ER) are two of the interesting subcellular organelles that are critical for protein synthesis, folding, processing, post-translational modifications, and secretion. Consequently, dysregulation in GA and ER and cross-talk between them are implicated in numerous diseases including cancer. As a result, simultaneous visualization of the GA and ER in cancer cells is extremely crucial for developing cancer therapeutics. To address this, herein, we have designed and synthesized a 1,8-napthalimide-based small molecule (AIE-GA-ER) consisting of phenylsulfonamide as Golgi-ER homing and triphenylamine-napthalimide as aggregation-induced emission (AIE) triggering moieties. AIE-GA-ER exhibited remarkable "on-off-on" AIE properties in THF/water binary solvent system due to aggregated "on-state" in pure THF and 80% water in THF. Molecular dynamic simulations and density functional theory (DFT) calculations exhibited the underlying mechanism of the emissive property of AIE-GA-ER to be the interplay between intramolecular charge transfer (ICT) stabilization and aggregation in THF, DMSO, and water. AIE-GA-ER efficiently homed into the GA and ER of HCT-116 colon cancer cells within 15-30 min as well as noncancerous human retinal epithelial pigment cells (RPE-1) within 3 h with minimum toxicity. This AIEgen has the potential to illuminate the Golgi apparatus and ER simultaneously in cancer cells to understand the chemical biology of their cross-talk for next-generation cancer therapeutics.

Dynamics of spindle assembly and position checkpoints: Integrating molecular mechanisms with computational models.

Mitotic checkpoints orchestrate cell division through intricate molecular networks that ensure genomic stability. While experimental research has uncovered key aspects of checkpoint function, the complexity of protein interactions and spatial dynamics necessitates computational modeling for a deeper, system-level understanding. This review explores mathematical frameworks-from ordinary differential equations to stochastic simulations, which reveal checkpoint dynamics across multiple scales, encompassing models ranging from simple protein interactions to whole-system simulations with thousands of parameters. These approaches have elucidated fundamental properties, including bistable switches driving spindle assembly checkpoint (SAC) activation, spatial organization principles underlying spindle position checkpoint (SPOC) signaling, and critical system-level features ensuring checkpoint robustness. This study evaluates diverse modeling approaches, from rule-based models to chemical organization theory, highlighting their successful application in predicting protein localization patterns and checkpoint response dynamics validated through live-cell imaging. Contemporary challenges persist in integrating spatial and temporal scales, refining parameter estimation, and enhancing spatial modeling fidelity. However, recent advances in single-molecule imaging, data-driven algorithms, and machine learning techniques, particularly deep learning for parameter optimization, present transformative opportunities for improving model accuracy and predictive power. By bridging molecular mechanisms with system-level behaviors through validated computational frameworks, this review offers a comprehensive perspective on the mathematical modeling of cell cycle control, with practical implications for cancer research and therapeutic development.

Evaluation of Stability and In vitro Anti-Cancer Activity of Dihydroquercetin Nanoemulsion

Background: Dihydroquercetin (DHQ), also known as taxifolin, is a flavonoid commonly found in many plants. Dihydroquercetin has been documented to have powerful antioxidant activity and many beneficial properties for human health, especially its ability to inhibit certain types of cancer cells. However, its low solubility and bioavailability are major obstacles to biomedical applications. Moreover, DHQ is chemically unstable and quickly degrades when exposed to alkaline conditions. Objective: In the present study, a DHQ nanoemulsion formulation was prepared by Self Nano- Emulsifying Drug Delivery System (SNEDDS) technique to overcome the above disadvantages. Methods: The obtained nanoemulsion system was evaluated for its micro-properties, stability, and in vitro cytotoxic activity against some cancer cells using tetrazolium dyes (MTS assay). Results: Measurement results showed that the DHQ nanoemulsion was successfully synthesized with typical mean droplet sizes from 9 to 11 nm, and revealed excellent stability over time. Dihydroquercetin in nanoemulsion form is more stable than the non-encapsulated form, as evidenced by the maintenance of droplet size in the nanometer range when dispersed in aqueous solution for up to 48 hours. This stability is particularly pronounced in both acidic and neutral environments. In vitro experiments on cytotoxic activities against A549, Hela, and HepG2 cancer cell lines indicated that the prepared DHQ nanoemulsion effectively inhibited the growth of all these cell lines with IC50 values (μg/mL) of 8.0, 20.4, and 29.5 respectively. Conclusion: From the detailed results above, it is evident that the solubility and bioavailability of DHQ can be improved by creating its nanostructure in the form of nanoemulsions. Furthermore, the nano form of DHQ carried within stable nanoemulsions exhibited better performance in inhibiting cancer cells compared to free DHQ. Therefore, further research is required to explore the development of cancer therapeutics utilizing nano DHQ emulsions.

Exploring Marine Compounds for Inhibition of the BRAF V600E Mutation in Lung Cancer: A High Throughput Virtual Screening Approach

The BRAF V600E mutation is present in a variety of cancer cell types, including lung cancer, which is a leading cause of cancer-related death globally. Drugs like Dabrafenib and Vermaifenib were specifically used in targeted therapy for patients with BRAF V600E mutation. Drug resistance is typical, though, and more study is required to improve therapeutic strategies for this subset of lung cancer. Recently, marine natural compounds have emerged as a resource for the development of novel cancer therapeutics. In this study, we used virtual screening of marine compounds to find potential therapeutic candidates for NSCLC patients with the BRAF V600E mutation. We developed a receptor-based pharmacophore model and screened a library of 31,561 compounds from the Comprehensive Marine Natural Products Database (CMNPD) using a virtual screening protocol that was constructed and validated. Molecular docking was performed using CDOCKER to investigate potential inhibitors and ADMET for their toxicity and other properties. Seven compounds exhibited higher efficacy than the experimentally verified compound of BRAF mutation. A molecular dynamics simulation was performed to confirm the stability of the docked compounds and compare them with the experimentally verified compound. Our study identified, out of seven, the CMNPD7700 compound as a potential drug candidate for further development due to its high, effectiveness and molecular stability.

In Silico Optimization of a Streptomyces sp. Antimicrobial Peptide Against Oncobacteria in Oral Squamous Cell Carcinoma

ABSTRACTOral squamous cell carcinoma (OSCC) is a major public health concern, accounting for more than 90% of all oral malignancies. Pathogenic bacteria, such as Streptococcus mutans, Fusobacterium nucleatum, and Porphyromonas gingivalis, are closely linked to OSCC and promote chronic inflammation, a key factor in the tumor microenvironment. The increasing incidence of oral malignancies necessitates the development of antimicrobial peptides (AMPs) with enhanced anticancer activity as targeted therapeutics against bacteria to mitigate their impact on OSCC. A total of 182 Streptomyces genus‐derived AMPs were collected and analyzed in silico to determine their potent antibacterial and anticancer characteristics. Fourteen AMPs were tested for 3D structural alignment prediction and validation, and the most efficient peptide was determined to be sAMP2. A genome‐based analysis of the peptide sourced from Streptomyces globisporus C‐1027 was conducted to explore its evolutionary significance. The cell‐penetrating peptide activity of sAMP2 was optimized to make it more stable and better able to target OSCC host cellular receptors. The peptide Mut_sAMP2 was found to interact with the bacterial virulence proteins DEX of S. mutans, LPS of F. nucleatum, and KGP of P. gingivalis and with OSCC‐associated proteins (TNFα, IL‐6, IL‐8, p38, p53, E‐cadherin, Jak‐1, and PAR2) with greater binding affinity. The peptide Mut_sAMP2 treated OECM‐1 cells showed reduced cell survival by the cytotoxicity activity of IC50 5.4 μg/mL. To the best of our knowledge, our computational study is the first to significantly impact the development of new and effective cancer therapeutics from Streptomyces sp. derived AMPs with a broad spectrum of activity and potential evaluating to combat OSCC progression linked with oral oncobacteria.

Synthetic lethal strategies for the development of cancer therapeutics.

Synthetic lethality is a genetic phenomenon whereby the simultaneous presence of two different genetic alterations impairs cellular viability. Importantly, targeting synthetic lethal interactions offers potential therapeutic strategies for cancers with alterations in pathways that might otherwise be considered undruggable. High-throughput screening methods based on modern CRISPR-Cas9 technologies have emerged and become crucial for identifying novel synthetic lethal interactions with the potential for translation into biologically rational cancer therapeutic strategies as well as associated predictive biomarkers of response capable of guiding patient selection. Spurred by the clinical success of PARP inhibitors in patients with BRCA-mutant cancers, novel agents targeting multiple synthetic lethal interactions within DNA damage response pathways are in clinical development, and rational strategies targeting synthetic lethal interactions spanning alterations in epigenetic, metabolic and proliferative pathways have also emerged and are in late preclinical and/or early clinical testing. In this Review, we provide a comprehensive overview of established and emerging technologies for synthetic lethal drug discovery and development and discuss promising therapeutic strategies targeting such interactions.

Unveiling novel type 1 inhibitors for targeting LIM kinase 2 (LIMK2) for cancer therapeutics: An integrative pharmacoinformatics approach

LIMK2 is crucial in regulating actin cytoskeleton dynamics, significantly contributing to cancer cell proliferation, invasion, and metastasis. Inhibitors like LIMKi3 effectively suppress LIMK2 kinase activity by directly affecting actin polymerization and preventing the formation of structures like filopodia and lamellipodia, which are typical of motile cancer cells. By modulating these actin dynamics, LIMKi3 inhibits cancer cell migration and invasion, reducing the potential for metastasis. Thus, this study aims to explore potential anti-cancer therapeutic LIMK2 inhibitors with properties resembling LIMKi3. Henceforth, molecular docking was utilized in this study to comprehend the ATP mimetic binding mode of LIMKi3, followed by Pharmacophore-based virtual screening to identify small molecules resembling LIMKi3. In addition, molecular dynamics simulations were performed to explore the dynamic behavior of LIMK2 and potential inhibitors. Further, network analysis and binding free energy calculations were implemented to comprehensively assess the interactions between the compounds and LIMK2. In molecular docking, LIMKi3 demonstrated an ATP mimetic hinge binding mode with hydrogen bonds at Ile408. Among the screened compounds (NCI300395, ChemDiv-8020–2508, and ChemDiv-7997–0024), three displayed "ADRH" pharmacophoric features like LIMKi3, with favorable ADMET properties, higher binding affinity, and significant hydrogen bond interactions at Ile408. LIMK2-inhibitor complexes showed lower RMSD than LIMK2-LIMKi3, indicating higher equilibrium by identified compounds. Protein-drug Complexes exhibited significant inter-domain correlation in N-lobe residues of LIMK2, including conserved β3, αC, and Hinge residues. Binding free energy analysis ranked LIMK2-NCI300395 highest, followed by LIMK2-ChemDiv-7997–0024 and LIMK2-ChemDiv-8020–2508, highlighting their potential as effective LIMK2-targeting compounds. Hence, this study emphasizes LIMKi3's significance and identifies potential candidates (NCI300395, ChemDiv-7997–0024, and ChemDiv-8020–2508) for developing cancer therapeutics targeting LIMK2. These findings open avenues for further investigations into the complex interplay between cytoskeletal dynamics and cancer progression.

Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning.

Cancer is a group of complex diseases, with tumor heterogeneity, durable drug efficacy, emerging resistance, and host toxicity presenting major challenges to the development of effective cancer therapeutics. While traditionally used methods have remained limited in their capacity to overcome these challenges in cancer drug development, efforts have been made in recent years toward applying "big data" to cancer research and precision oncology. By curating, standardizing, and integrating data from various databases, we developed deep learning architectures that use perturbation and baseline transcriptional signatures to predict efficacious small molecule compounds and genetic dependencies in cancer. A series of internal validations followed by prospective validation in prostate cancer cell lines were performed to ensure consistent performance and model applicability. We report SensitivitySeq, a novel bioinformatics tool for prioritizing small molecule compounds and gene dependencies in silico to drive the development of targeted therapies for cancer. To the best of our knowledge, this is the first supervised deep learning approach, validated in vitro, to predict drug sensitivity using baseline cancer cell line gene expression alongside cell line-independent perturbation-response consensus signatures.

Abstract A030: Beyond the LNP: Self-amplifying RNA with LION nanoformulation technology for development of safe and effective cancer therapeutics

Abstract HDT Bio, a Seattle biotech company, has developed a platform technology based on self-amplifying RNA and a proprietary nanoparticle delivery system. mRNA have been increasingly used in the development of vaccines in both infectious diseases and oncology. Especially LNP- delivered mRNA has been deployed, following the success during the COVID pandemic, However, self-ampliying RNA (repRNA) possesses several features of particular relevance to cancer medicine. HDT has developed a nanoparticle technology named LION[TM] to safely and effectively deliver RNA to patients. In vivo studies showed that repRNA not only is capable of delivering robust cell-mediated immune responses but also doing so with a significanlty improved safety profile compared to administration using LNP-based formulations. These data will be presented in the context of clinical safety data with repRNA/LION. Furthermore, repRNA/LION was siuccessfully used to induce robust T-cell responses against tumor antigens, and will be discussed. Citation Format: Peter Berglund. Beyond the LNP: Self-amplifying RNA with LION nanoformulation technology for development of safe and effective cancer therapeutics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr A030.

Immune Cell-Derived Exosomes: A Cell-Free Cutting-Edge Tumor Immunotherapy.

Extracellular vesicles (EVs) are cellular communication molecules and are classified into three major subpopulations, such as microvesicles, apoptotic bodies, and exosomes. Among these, exosomes-based cancer research is a cutting-edge investigation approach to cancer understanding. During cancer progression , tumor-derived exosomes can reprogram the cellular system and promote cancer. Circulating exosomes in the body fluids such as blood, plasma, serum, saliva, CSF, sweat, and tears play a key role in identifying diagnostic and prognostic cancer biomarkers. Diverse therapeutic sources of exosomes including stem cells, plants, and immune cells, etc. exhibit significant cancer-healing properties. Although cancer-targeting immunotherapy is an effective strategy, it has limitations such as toxicity, and high costs. In comparison, immune cell-derived exosomes-based immunotherapy is a cell-free approach for cancer treatment and has advantages like less toxicity, biocompatibility, reduced immunogenicity, and efficient, target-specific cancer therapeutic development. This review highlights the therapeutic signature of immune cell-derived exosomes for cancer treatment.

A Call for Innovative Translational and Clinical Research to Address China's Unique Cancer Landscape.

The Chinese government has, in recent decades, implemented various administrative laws and regulatory policies to expedite cancer therapeutic development, boosting research and development pipelines for domestic pharmaceutical companies and clinical trials; however, China faces unique challenges given the high prevalence of certain cancer types and distinct disease burdens, some of which are frequently overlooked by international pharmaceutical companies. Given the substantial unmet need for China-specific cancer care, it is crucial to promote the development of innovative pharmaceutical and clinical research in China, with a particular emphasis on addressing tumors most prevalent in its population.

Translational Relevance and Future Integration of the Oncopig Cancer Model in Preclinical Applications.

Porcine cancer models offer a valuable platform for evaluating interventions such as devices, surgeries, and locoregional therapies, which are often challenging to test in mouse models. In addition to size and anatomical similarities with humans, pigs share greater similarities in genetics, immunity, drug metabolism, and metabolic rate with humans as compared to mouse models, increasing their translational relevance. This review focuses on the Oncopig Cancer Model, a genetically engineered porcine model designed to recapitulate human cancer. Harboring a transgenic cassette that expresses oncogenic mutant KRAS and TP53 under control of a Cre-Lox system, the Oncopig allows temporal and spatial control of tumor induction. Its versatility has enabled the development of diverse cancer models including liver, pancreatic, lung, and bladder cancer. Serving as a clinically relevant model for human cancer, the Oncopig addresses unmet clinical needs and holds immense promise for advancing preclinical cancer research and therapeutic development.

Differential effect of plakoglobin in restoring the tumor suppressor activities of p53-R273H vs. p53-R175H mutants.

The six most common missense mutations in the DNA binding domain of p53 are known as "hot spots" and include two of the most frequently occurring p53 mutations (p53-R175H and p53-R273H). p53 stability and function are regulated by various post-translational modifications such as phosphorylation, acetylation, sumoylation, methylation, and interactions with other proteins including plakoglobin. Previously, using various carcinoma cell lines we showed that plakoglobin interacted with wild-type and several endogenous p53 mutants (e.g., R280K, R273H, S241F, S215R, R175H) and restored their tumor suppressor activities in vitro. Since mutant p53 function is both mutant-specific and cell context-dependent, we sought herein, to determine if plakoglobin tumor suppressive effects on exogenously expressed p53-R273H and p53-R175H mutants are similarly maintained under the same genetic background using the p53-null and plakoglobin-deficient H1299 cell line. Functional assays were performed to assess colony formation, migration, and invasion while immunoblotting and qPCR were used to examine the subcellular distribution and expression of specific proteins and genes that are typically regulated by or regulate p53 function and are altered in mutant p53-expressing cell lines and tumors. We show that though, plakoglobin interacted with both p53-R273H and p53-R175H mutants, it had a differential effect on the transcription and subcellular distribution of their gene targets and their overall oncogenic properties in vitro. Notably, we found that plakoglobin's tumor suppressive effects were significantly stronger in p53-R175H expressing cells compared to p53-R273H cells. Together, our results indicate that exploring plakoglobin interactions with p53-R175H may be useful for the development of cancer therapeutics focused on the restoration of p53 function.

11 Oral: Transforming cancer care and therapeutic development by predicting individual patient responses to treatment

11 Oral: Transforming cancer care and therapeutic development by predicting individual patient responses to treatment

Machine learning optimized DriverDetect software for high precision prediction of deleterious mutations in human cancers.

The detection of cancer-driving mutations is important for understanding cancer pathology and therapeutics development. Prediction tools have been created to streamline the computation process. However, most tools available have heterogeneous sensitivity or specificity. We built a machine learning-derived algorithm, DriverDetect that combines the outputs of seven pre-existing tools to improve the prediction of candidate driver cancer mutations. The algorithm was trained with cancer gene-specific mutation datasets of cancer patients to identify cancer drivers. DriverDetect performed better than the individual tools or their combinations in the validation test. It has the potential to incorporate future novel prediction algorithms and can be retrained with new datasets, offering an expanded application to pan-cancer analysis for cross-cancer study. (115 words).

Landscape of exosomes to modified exosomes: a state of the art in cancer therapy.

Exosomes are a subpopulation of extracellular vesicles (EVs) that naturally originate from endosomes. They play a significant role in cellular communication. Tumor-secreted exosomes play a crucial role in cancer development and significantly contribute to tumorigenesis, angiogenesis, and metastasis by intracellular communication. Tumor-derived exosomes (TEXs) are a promising biomarker source of cancer detection in the early stages. On the other hand, they offer revolutionary cutting-edge approaches to cancer therapeutics. Exosomes offer a cell-free approach to cancer therapeutics, which overcomes immune cell and stem cell therapeutics-based limitations (complication, toxicity, and cost of treatment). There are multiple sources of therapeutic exosomes present (stem cells, immune cells, plant cells, and synthetic and modified exosomes). This article explores the dynamic source of exosomes (plants, mesenchymal stem cells, and immune cells) and their modification (chimeric, hybrid exosomes, exosome-based CRISPR, and drug delivery) based on cancer therapeutic development. This review also highlights exosomes based clinical trials and the challenges and future orientation of exosome research. We hope that this article will inspire researchers to further explore exosome-based cancer therapeutic platforms for precision oncology.

Synthesis and biological evaluation of ortho-phenyl phenylhydroxamic acids containing phenothiazine with improved selectivity for class IIa histone deacetylases

Class IIa histone deacetylases (HDACs) have been linked to tumorigenesis in various cancers. Previously, we designed phenylhydroxamic acid LH4f as a potent class IIa HDAC inhibitor. However, it also unselectively inhibited class I and class IIb HDACs. To enhance the compound’s selectivity towards class IIa HDACs, the ortho-phenyl group from the selective HDAC7 inhibitor 1 is incorporated into ortho position of the phenylhydroxamic acid in LH4f. Compared to LH4f, most resulting compounds displayed substantially improved selectivity towards the class IIa HDACs. Notably, compound 7 g exhibited the strongest HDAC9 inhibition with an IC50 value of 40 nM. Molecular modelling further identified the key interactions of compound 7 g bound to HDAC9. Compound 7 g significantly inhibited several human cancer cells, induced apoptosis, modulated caspase-related proteins as well as p38, and caused DNA damage. These findings suggest the potential of class IIa HDAC inhibitors as lead compounds for the development of cancer therapeutics.

Discovery and biological evaluation of 6-aryl-4-(3,4,5-trimethoxyphenyl)quinoline derivatives with promising antitumor activities as novel colchicine-binding site inhibitors

Tubulin, as the fundamental unit of microtubules, is a crucial target in the investigation of anticarcinogens. The synthesis and assessment of small-molecule tubulin polymerization inhibitors remains a promising avenue for the development of novel cancer therapeutics. Through an analysis of reported colchicine-binding site inhibitors (CBSIs) and tubulin binding models, a set of 6-aryl-4-(3,4,5-trimethoxyphenyl)quinoline derivatives were meticulously crafted as potential CBSIs. Notably, compound 14u exhibited potent anti-proliferative efficacy, displaying IC50 values ranging from 0.03 to 0.18 μM against three human cancer cell lines (Huh7, MCF-7, and SGC-7901). Mechanistic investigations revealed that compound 14u could disrupt tubulin polymerization, dismantle the microtubule architecture, arrest the cell cycle at G2/M phase, and induce apoptosis in cancer cells. Furthermore, compound 14u demonstrated significant inhibition of tumor proliferation in vivo with no discernible toxicity in the Huh7 orthotopic tumor model mice. Additionally, physicochemical property predictions indicated that compound 14u adhered well to Lipinski's rule of five. These findings collectively suggest that compound 14u holds promise as an antitumor agent targeting the colchicine-binding site on tubulin and warrants further investigation.