Molecular Diversity最新文献

Cancer, a leading global cause of death, presents considerable treatment challenges due to resistance to conventional therapies like chemotherapy and radiotherapy. Cyclin-dependent kinase 11 (CDK11), which plays a pivotal role in cell cycle regulation and transcription, is overexpressed in various cancers and is linked to poor prognosis. This study focused on identifying potential inhibitors of CDK11 using computational drug discovery methods. Techniques such as pharmacophore modeling, virtual screening, molecular docking, ADMET predictions, molecular dynamics simulations, and binding free energy analysis were applied to screen a large natural product database. Three pharmacophore models were validated, leading to the identification of several promising compounds with stronger binding affinities than the reference inhibitor. ADMET profiling indicated favorable drug-like properties, while molecular dynamics simulations confirmed the stability and favorable interactions of top candidates with CDK11. Binding free energy calculations further revealed that UNPD29888 exhibited the strongest binding affinity. In conclusion, the identified compound shows potential as a CDK11 inhibitor based on computational predictions, suggesting their future application in cancer treatment by targeting CDK11. These computational findings encourage further experimental validation as anti-cancer agents.

ROCK inhibitors can inhibit IL-1β and NLRP3, and their therapeutic potential for osteoarthritis and rheumatoid arthritis has been confirmed, but their impact on gouty arthritis has not been reported yet. By hybridization the structure of Edaravone, a series of ROCK inhibitors with pyrazolone scaffold were designed and synthesized. RM-04 has acceptable selective ROCK2 inhibitory activity with an IC₅₀ of 4.62 µM, and its IC₅₀ values for scavenging DPPH^• and ABTS^•+ are 16.72 µM and 23.15 µM, respectively, which is equivalent to that of Edaravone. Furthermore, RM-04 exhibits good pharmacokinetic properties and good safety in vivo. Meanwhile, in sodium urate-induced acute gout model, RM-04 at a dose of 5 mg/kg exhibited the alleviating effect approximately equivalent to that of Celecoxib, indicating that ROCKs inhibitors with antioxidation activity could reduce the damage caused by gouty arthritis.

A series of flavonoid derivatives containing piperazine sulfonate were designed and synthesized. The results of antiviral experiments in vivo showed that some target compounds had good inhibitory effect on tobacco mosaic virus (TMV). The EC₅₀ values of S15 and S19 curative activity were 174.5 and 110.4 μg/mL, respectively, which were better than 253.7 μg/mL of Ningnanmycin (NNM). The EC₅₀ values of S4 and S19 protection activity were 140.3 and 116.1 μg/mL, respectively, better than that of NNM (247.1 μg/mL). Microscale thermophoresis (MST) and molecular docking experiments showed that S19 had a good molecular binding force with TMV. Transmission electron microscopy (TEM) results show that S19 can fracture TMV particles and affect self-assembly. S19 treatment had almost no effect on the growth of seeds and seedlings, and can change the content of chlorophyll malondialdehyde (MDA) and superoxide dismutase (SOD) in tobacco to a certain extent, and improve the disease resistance of tobacco.

The drug combination is an attractive approach for cancer treatment. PARP and kinase inhibitors have recently been explored against cancer cells, but their combination has not been investigated comprehensively. In this study, we used various drug combination databases to build ML models for drug combinations against brain cancer cells. Some decision tree-based models were used for this purpose. The results were further evaluated using molecular docking and molecular dynamics (MD) simulation. The possibility of the hit drug combinations for crossing the Blood-brain barrier (BBB) was also examined. Based on the obtained results, the combination of niraparib, as the PARP inhibitor, and lapatinib, as the kinase inhibitor, exhibited more considerable outcomes with a remarkable model performance (accuracy of 0.915) and prediction confidence of 0.92. The protein tweety homolog 3 and BTB/POZ domain-containing protein 2 are the main targets of niraparib and lapatinib with - 10.2 and - 8.5 scores, respectively. Due to the outcomes, this drug combination can use the CAT1 transporter on the BBB surface and effectively cross the BBB. Based on the obtained results, niraparib-lapatinib can be a promising drug combination candidate for brain cancer treatment. This combination is worth to be examined by experimental investigation in vitro and in vivo.

Apigenin, a dietary flavonoid with notable anti-cancer properties, has emerged as a promising candidate for the treatment of neurodegenerative disorders, particularly Alzheimer's disease (AD). While extensively studied for its ability to modulate key molecular pathways in cancers, apigenin also exerts neuroprotective effects by reducing neuroinflammation, protecting neurons from oxidative stress, and enhancing neuronal survival and synaptic plasticity. This dual functionality makes apigenin an intriguing therapeutic option for diseases like AD, where kinase dysregulation plays a central role. In this study, we focus on Microtubule Affinity-Regulating Kinase 4 (MARK4), a key enzyme implicated in tauopathies associated with AD, as well as in cancer progression. Through in silico analysis, we explore the interaction between apigenin and MARK4, revealing significant structural changes within the kinase domain upon ligand binding. These computational findings were confirmed via experimental assays using purified recombinant MARK4, where apigenin demonstrated potent inhibition with an IC₅₀ value of 2.39 µM. Fluorescence binding assays further confirmed a strong binding affinity (Ka = 10⁸ M^-1), indicating that apigenin efficiently occupies the MARK4 active site, thereby suppressing its enzymatic activity. These results position apigenin as a potent inhibitor of MARK4, offering a dual therapeutic advantage-both as an anti-cancer agent and as a neuroprotective compound for the potential treatment of AD. This study opens new avenues for the development of apigenin-based therapeutics targeting kinase dysregulation in cancer and neurodegeneration.

Dengue is one of the most prevalent viruses transmitted by the Aedes aegypti mosquitoes. Currently, no specific medication is available to treat dengue diseases. The NS2B-NS3 protease is vital during post-translational processing, which is a key target in this study. Due to methoxy group substitution, methoxyflavones are more bioavailable and metabolically stable than hydroxylated flavones. To date, research on the anti-dengue activity of methoxyflavones is limited. Hence, this work aims to determine the inhibitory activity of methoxyflavones against the dengue NS2B-NS3. Methoxyflavones derivatives were screened using molecular docking. The result showed a strong binding interaction of compound 1 and compound 2 with NS2B-NS3 protease. Both compounds exhibited comparable binding energy as the reference compound, quercetin, with values lower than - 8.1 kcal/mol. Molecular dynamics simulation using GROMACS revealed the stability and stiffness of the complexes over a 100 ns time scale. In addition, an in vitro assay for NS2B-NS3 protease inhibition revealed inhibitory effects of compounds 1 and 2 with IC₅₀ values of 316.80 µM and 463.30 µM, respectively. The ADMET analyses showed favorable pharmacokinetics profiles that comply with Lipinski's Rule of Five. Collectively, our findings suggest that compounds 1 and 2 inhibit dengue NS2B-NS3 activity. These findings hold promise of methoxyflavones as starting compounds for potential dengue treatment, highlighting the need for further investigation.

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases. Given the multifactorial pathophysiology of AD, monotargeted agents can only alleviate symptoms but not cure AD. Acetylcholinesterase (AChE) and Monoamine oxidase B (MAO-B) are two key targets in the treatment of AD, molecules that inhibiting both targets are considered promising avenue to develop more effective AD therapies. In the present work, a dual inhibition dataset containing 449 molecules was established, based on which five machine learning algorithms (KNN, SVM, RF, GBDT, and LGBM) four fingerprints (MACCS, ECFP4, RDKitFP, PubChemFP) and DRAGON descriptors were combined to develop 25 classification models in which GBDT paired with ECFP4 and RF paired with PubchemFP achieved the same best performance across multiple metrics (Accuracy = 0.92, F1 Score = 0.94, MCC = 0.81). Moreover, based on the curated bioactivity datasets of AChE and MAO-B, regression models were developed to predict pIC₅₀ values. For the AChE inhibition task, GBDT demonstrated the best performance (RMSE = 0.683, MAE = 0.500, R² = 0.721). The SVM algorithm emerged as the most effective for MAO-B inhibition (RMSE = 0.668, MAE = 0.507, R² = 0.675). The SHAP algorithm was used to interpret the optimal models, identifying and analyzing the key substructures and properties for both dual-target and single-target inhibitors. Moreover, molecules docking process provided potential mechanism and Structure-Activity Relationships (SAR) of dual-target inhibition further.

The 2-substituted benzimidazole has emerged as a promising heterocyclic compound in the field of drug design. In pursuit of more sustainable photocatalysts for 2-substituted benzimidazole synthesis, the method for coating Fe₃O₄ with V-doped TiO₂ was presented. On the base of characterizing composition, morphology, and properties, the prepared nano-sized Fe₃O₄@V/TiO₂ composites were used as a heterogeneous photocatalyst to catalyze the synthesis of 2-substituted benzimidazoles under light. The photocatalyst Fe₃O₄@V/TiO₂ composites showed the enhanced photocatalytic activity compared to no V-doped Fe₃O₄@TiO₂, being able to yield various 2-substituted benzimidazoles in moderate to good yield with recyclability and stability. A possible photocatalysis mechanism was investigated. It was evident that holes, singlet oxygen, and ·O₂̄ radical played important roles in the synthesis of 2-substituted benzimidazole. Moreover, some of the obtained products were demonstrated excellent antibacterial activity.

The quinazoline scaffold serves as a fundamental framework, demonstrating potent anti-tumor activity. Employing the pharmacophore-based scaffold hopping principle, we successfully synthesized a series of FAK/PLK1 inhibitors incorporating the quinazoline scaffold. The synthesized compounds were characterized using ¹H NMR, ¹³C NMR, and HRMS techniques. Through computer-assisted screening and antitumor activity tests, the majority of the compounds demonstrated significant inhibitory effects against various cancer cell lines. Notably, compound 3m exhibited remarkable anticancer activity by inducing G2/M phase cell cycle arrest, apoptosis, as confirmed by western blot assay, cellular fluorescence staining, and transcriptomics testing. Docking simulation was performed to determine the probable binding conformation of compound 3m within the active sites of FAK and PLK1. This compound emerged as a highly promising lead compound during our screening process, displaying high efficiency.

CD47, a cell surface protein, serves as a "don't eat me" signal that prevents immune cells from engulfing healthy cells upon its interaction with SIRPα. Cancer cells exploit this mechanism by overexpressing CD47 to evade immune destruction. Blocking the interaction between CD47 and its receptor, SIRPα, is a promising therapeutic strategy. Targeting the interactions between these surface proteins with small molecules is quite challenging, and on the other hand, antibodies offer potential. However, the interactions between antigen (CD47) and antibody (B6H12.2) play a crucial role in this scenario, and increasing the affinity by mutating the interacting residues might impact the inclination and effectiveness of the antibody towards antigen. Thus, this study focuses on designing antibodies with increased affinity and stability towards the antigen compared to the wild-type. Residual scanning calculations were performed to mutate the interacting as well as the hydrophobic residues of the antibody and affinity was assessed. Computational approaches, including antigen-antibody docking studies and molecular dynamics simulations, were employed to evaluate the affinity, stability and therapeutic potential of these modified antibodies.