Current computer-aided drug design最新文献

Introduction: Arthritis is the cause of morbidity associated with Chikungunya virus (CHIKV) infection. It persists even after the virus has been cleared from the body. MBZM-NIBT was earlier shown to inhibit (CHIKV) infection in vitro and in vivo.

Objectives: The objective of this study is to determine the ability of MBZM-N-IBT to manage arthritis independent of CHIKV infection.

Methods: The acute toxicity of MBZM-N-IBT was determined to find a permissible oral dose. Effects against inflammation and arthritis were determined in relevant preclinical models. Network pharmacology was used to propose possible modes of action.

Results: It showed no acute toxicity orally, with an estimated LD₅₀ of more than 5000 mg/kg in rats. It significantly reduced inflammation. Its effect against Complete Freund's Adjuvant (CFA) induced arthritis was comparable to that of Diclofenac sodium. Network pharmacology analysis revealed that MBZM-N-IBT can potentially interfere with multiple targets and pathways. MMP12 and CTSD were found to be the most probable hub targets of MBZM-N-IBT for its effect against arthritis.

Conclusion: In conclusion, MBZM-N-IBT is safe at 50 mg/kg and can manage arthritis independent of CHIKV infection through modulation of multiple pathways and arthritis-associated targets.

Background: Berberine (BBR), also known as berberine hydrochloride, was isolated from the rhizomes of the Coptis chinensis. Studies have reported that BBR plays an important role in glycolipid metabolism, including insulin resistance (IR). The targets, and molecular mechanisms of BBR against hyperlipid-induced IR is worthy to be further studied.

Materials and methods: The related targets of BBR were identified via Pharmmapper database and relevant targets of diabetes were obtained through GeneCards and Online Mendelian Inheritance in Man (OMIM) database. The common targets were employed with the STRING database and visualized with the protein-protein interactions (PPI) network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to explore the biological progress and pathways. In vitro, human hepatocellular carcinomas (HepG2) cell was used as experimental cell line, and an insulin resistant HepG2 cell model (IR-HepG2) was constructed using free fatty acid induction. After intervention with BBR, glucose consumption and uptake in HepG2 cells were observed. Molecular docking was used to test the interaction between BBR and key targets, and real-time fluorescence quantitative PCR was used to detect the regulatory effect of BBR on related targets.

Results: 262 overlapped targets were extracted from BBR and diabetes. In the KEGG enrichment analysis, the peroxisome proliferator activated receptor (PPAR) signaling pathway was included. In vitro experiments, BBR can significantly increase sugar consumption and uptake in IR HepG2 cells, while PPAR inhibitors can weaken the effect of BBR on IR-HepG2.

Conclusion: The PPAR signaling pathway is one of the important pathways for BBR to improve high-fat-induced insulin resistance in HepG2 cells.

Background: Virtual screening (VS) is essential for analyzing potential drug candidates in drug discovery. Often, this involves the conversion of large volumes of compound data into specific formats suitable for computational analysis. Managing and processing this wealth of information, especially when dealing with vast numbers of compounds in various forms, such as names, identifiers, or SMILES strings, can present significant logistical and technical challenges.

Methods: To streamline this process, we developed PyComp, a software tool using Python's PyQt5 library, and compiled it into an executable with Pyinstaller. PyComp provides a systematic way for users to retrieve and convert a list of compound names, IDs (even in a range), or SMILES strings into the desired 3D format.

Results: PyComp greatly enhances the efficiency of data extraction, conversion, and storage processes involved in VS. It searches for similar compounds coupled with its ability to handle misidentified compounds and offers users an easy-to-use, customizable tool for managing largescale compound data. By streamlining these operations, PyComp allows researchers to save significant time and effort, thus accelerating the pace of drug discovery research.

Conclusion: PyComp effectively addresses some of the most pressing challenges in highthroughput VS: efficient management and conversion of large volumes of compound data. As a user-friendly, customizable software tool, PyComp is pivotal in improving the efficiency and success of large-scale drug screening efforts, paving the way for faster discovery of potential therapeutic compounds.

Background: Alzheimer's disease is a type of dementia that affects neuronal function, leading to a decline in cognitive functions. Serotonin-6 (5HT₆) receptors are implicated in the etiology of neurological diseases. 5HT₆ receptor antagonists act as anti-dementia agents.

Pdb id: 7YS6 represents a membrane protein, and amplification and overexpression of this protein are associated with Alzheimer's disease. Coumarin-fused phenothiazines are significant anti-Alzheimer's agents due to their inhibitory activity on the Serotonin- 6 receptor.

Objectives: Numerous previously unreported Coumarin-substituted Phenothiazines [A2 to A50] were designed using In-silico methods to evaluate their 5HT₆ receptor antagonistic activity. Molecular modeling techniques were employed to study the ligands [A2 to A50] in interaction with the Serotonin-6 receptor (PDB ID: 7YS6) using Schrödinger Suite 2019-4.

Methods: Molecular modeling studies of the designed ligands [A2 to A50] were conducted using the Glide module. In-silico ADMET screening was performed using the QikProp module, and binding free energy calculations were carried out using the Prime MM-GBSA module within the Schrödinger Suite. The binding affinity of the designed ligands [A2 to A50] towards 5HT₆ receptors was determined based on Glide scores. Subsequently, ligand A31 underwent a 100 ns molecular dynamics simulation using the Desmond module of Schrödinger Suite 2020-1, which is based in New York, NY.

Results: The majority of the designed ligands exhibited strong hydrogen bonding interactions and hydrophobic associations with the serotonin-6 receptor, which hinder its activity. These ligands achieved remarkable Glide scores within the range of -4.2859 to -7.7128, in comparison to reference standards such as Idalopirdine (-7.78149), Intepirdine (-5.20103), Latrepirdine (-5.54853), and the co-crystallized ligand (-7.02889). In-silico ADMET properties for these ligands fell within the recommended values for drug-likeness. It is worth noting that the MMGBSA binding free energy of the most potent inhibitor was positive, indicating a strong binding interaction. Additionally, the dynamic behavior of the protein (7YS6)-ligand (A31) complex was studied by subjecting ligand A31 to a 100 ns molecular dynamics simulation.

Conclusion: The results of this study reveal strong evidence supporting the potential of coumarin- substituted phenothiazine derivatives as effective Serotonin-6 receptor antagonists. Ligands [A2 to A50], which exhibited noteworthy Glide scores, hold promise for significant anti- Alzheimer activity. Further in-vitro and in-vivo investigations are warranted to explore and confirm their therapeutic potential.

Background: Translationally controlled tumour protein (TCTP) is associated with tumor diseases, such as breast cancer, and its inhibitor can reduce the growth of tumor cells. Unfortunately, there is currently no effective medication available for treating TCTP-related breast cancer.

Objectives: The objective of this study was to explore the inhibitor candidates among natural compounds for the treatment of breast cancer related to TCTP protein.

Methods: To explore the potential inhibitors of TCTP, we first screened out four potential inhibitors in the Traditional Chinese Medicine (TCM) for cancer based on AI virtual screening using the docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCM with molecular docking and molecular dynamics (MD) methods.

Results: Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with the AI method using MolAICal software. Our MD simulations have revealed that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, and the VDW and hydrophobic interactions are crucial in the interactions between TCTP and ligands.

Conclusion: We have proposed the candidate inhibitor of TCTP. Our study has provided a potential new method for exploring inhibitors from Traditional Chinese Medicine (TCM).

Background: To a certain extent, traditional Chinese medicine (TCM)-based anesthesia has replaced opiate administration in recent years. Preliminary drug screening has revealed that scopolamine may affect breast cancer (BC) metastasis by an unknown mechanism.

Methods: Network pharmacology, bioinformatics, and protein-protein interaction (PPI) topological analysis were implemented to identify the core genes linking scopolamine and BC. The core genes were then subjected to gene expression profiling interactive analysis (GEPIA). The top ten pathways were detected by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The impact of immune infiltration on the core gene difference and survival analyses was then determined. Molecular docking was then performed on the core genes and the main active components.

Results: Protein kinase 1 (AKT1), epidermal growth factor receptor (EGFR), heat shock protein 90 alpha class A (HSP90AA1), caspase 3 (CASP3), and estrogen receptor 1 (ESR1) were the key genes in the interaction between scopolamine and BC cells. The KEGG enrichment analysis disclosed that the top ten pathways significantly associated with the scopolamine response in BC included "protein glycosylation," "phosphoinositide 3-kinase (PI3K)-Akt signaling," "mitogen- activated protein kinase (MAPK) signaling" and others. The AKT1, EGFR, and especially the HSP90AA1 expression levels were correlated with survival in patients with BC. Immune infiltration also influenced the survival outcome. Molecular docking demonstrated that scopolamine bound and formed stable complexes with the protein products of all five aforementioned genes.

Conclusion: Scopolamine has multiple targets regulating BC cell function and may increase the risk of metastasis during treatment. Therefore, it should be preoperatively administered with caution to patients with BC.

Background: Histone deacetylase 9 (HDAC9) is an important member of the class IIa family of histone deacetylases. It is well established that over-expression of HDAC9 causes various types of cancers including gastric cancer, breast cancer, ovarian cancer, liver cancer, lung cancer, lymphoblastic leukaemia, etc. The important role of HDAC9 is also recognized in the development of bone, cardiac muscles, and innate immunity. Thus, it will be beneficial to find out the important structural attributes of HDAC9 inhibitors for developing selective HDAC9 inhibitors with higher potency.

Methods: The classification QSAR-based methods namely Bayesian classification and recursive partitioning method were applied to a dataset consisting of HADC9 inhibitors. The structural features strongly suggested that sulphur-containing compounds can be a good choice for HDAC9 inhibition. For this reason, these models were applied further to screen some natural compounds from Allium sativum. The screened compounds were further accessed for the ADME properties and docked in the homology-modelled structure of HDAC9 in order to find important amino acids for the interaction. The best-docked compound was considered for molecular dynamics (MD) simulation study.

Results: The classification models have identified good and bad fingerprints for HDAC9 inhibition. The screened compounds like ajoene, 1,2 vinyl dithiine, diallyl disulphide and diallyl trisulphide had been identified as compounds having potent HDAC9 inhibitory activity. The results from ADME and molecular docking study of these compounds show the binding interaction inside the active site of the HDAC9. The best-docked compound ajoene shows satisfactory results in terms of different validation parameters of MD simulation study.

Conclusion: This in-silico modelling study has identified the natural potential lead (s) from Allium sativum. Specifically, the ajoene with the best in-silico features can be considered for further in-vitro and in-vivo investigation to establish as potential HDAC9 inhibitors.

Background: One of the most important targets in cancer immunotherapy is programmed cell death ligand 1 (PD-L1). Monoclonal antibodies developed for this target have disadvantages due to their low bioavailability and some immune-related adverse effects. Additionally, small molecules targeting PD-L1 are still in the experimental stage. At this point, discovering non-toxic natural compounds that directly or indirectly target PD-L1 is essential. In this in silico study, a comprehensive literature search was conducted to identify publications reporting the master regulator of PD-L1, which was suggested as a Signal Transducer and Activator of Transcription 3 (STAT3). The relationship between STAT3 and PD-L1 was further investigated through bioinformatic analysis.

Methods: Subsequently, natural compounds targeting PD-L1 and STAT3 were screened, and compounds with suitable toxicity profiles were docked against both PD-L1 and STAT3. Following molecular docking, the selected molecules underwent DNA docking, ADMET profile analysis, and in silico assessment of biological activities. The relationship between PD-L1 and STAT3 was determined in 52 out of the 453 articles, and it was further demonstrated in genegene interactions. Following the virtual screening, 76 natural compounds were identified, and after pre-filtering based on physicochemical properties, drug-likeness, and ADMET profiles, 29 compounds remained.

Results: Subsequent docking revealed that two compounds, 6-Prenylapigenin, and Gelomulide J, persisted. ADMET and biological activity prediction results suggested that 6-Prenylapigenin is non-toxic and has the potential to inhibit PD-L1 and STAT3 in silico. The present study highlights that STAT3 serves as the master regulator of PD-L1, and it further suggests that 6- Prenylapigenin exhibits the potential to modulate PD-L1 and/or STAT3.

Conclusion: This finding could pave the way for the development of small molecules designed to block the PD-1/PD-L1 interaction by silencing the PD-L1 and/or STAT3 genes or reducing protein levels.

A malignant tumor is a frequent and common disease that severely threatens human health. Many mechanisms, such as cell signaling pathway, anti-apoptosis mechanism, cell stemness, metabolism, and cell phenotype, have been studied to explain the reasons for chemotherapy, radioresistance, and tumor recurrences in antitumor treatment. Cancer stem cells (CSCs) are important tumor cell subclasses that can potentially organize and regulate stem cell properties. Growing evidence suggests that CSCs can initiate tumors and constitute a significant factor in metastasis, recurrence, and treatment resistance. The inability to completely target and remove CSCs is a considerable obstacle in tumor treatment. Therefore, drugs and therapeutic strategies that can effectively intervene with CSCs are essential for the treatment of different tumor types. However, the current strategies and efficacy of targeted elimination of CSCs are very limited. Oxidative stress has been recognized to play a crucial role in cancer pathophysiology. Moreover, reactive oxygen species (ROS) production and imbalance of the built-in cellular antioxidant defense system are hallmarks of tumor and cancer etiology. The current paper will focus on the regulation and mechanism behind oxidative stress in tumors and cancer stem cells and its tumor therapy applications. Additionally, the article discusses the role of CSCs in causing tumor treatment resistance and recurrence based on a redox perspective. The study also emphasizes that targeted modulation of oxidative stress in CSCs has great potential in tumor therapy, providing novel prospects for tumor therapy.