Current computer-aided drug design最新文献

Background: Diabetes mellitus (DM) is characterized by elevated blood glucose levels either due to insufficient insulin production, defective insulin action, or both. It affects nearly 537 million individuals worldwide. Pharmacological treatment involves the use of oral antidiabetic agents as mono or combination therapy that effectively aids in controlling hyperglycemia. Despite providing therapeutic benefits, these medications limit their use owing to adverse side effects. Certain natural products, including essential oils, have promising anti-diabetic properties.

Objective: The present study explores the effectiveness of two polyherbal oils and their compound towards the treatment of DM based on an In-silico approach to drug investigations Methods: Compounds present in the polyherbal oil formulation were identified using GCMS/ MS analysis. Selected compounds undergo molecular docking with the receptor, and proteins play an important role in DM. The potential compounds showing higher interactions than the known inhibitors or inducers were evaluated using molecular dynamic simulations RMSD value.

Results: The compounds identified through GC-MS analysis possess anti-diabetic and antiinflammatory properties. With the aid of in silico prediction methods, compounds such as geraniol, cinnamaldehyde, anethole, caryophyllene, terpinyl acetate, cymene, linalool, menthol, Phenol,2-methoxy-3-(2-propenyl), and 2,6- octadienal,3,7-dimethyl were identified as strong binders of GLUT4 and insulin receptor proteins. Geraniol and Phenol,2-methoxy-3-(2-propenyl) interaction with GLUT4 were of particular importance owing to their conformational stability.

Conclusion: Our data suggest an agonistic effect of compounds on target proteins aiding in enhanced insulin activity and could serve as a potential anti-diabetic agent.

Background: Nardostachys chinensis is an herbal medicine widely used in the treatment of atrial fibrillation (AF), but the mechanism is unclear.

Objective: To explore the molecular mechanism of N. chinensis against AF.

Methods: The TCMSP was used to screen the active N. chinensis compounds and their targets. Differentially expressed genes (DEGs) for AF were identified using open-access databases. Using Venn diagrams, the cross-targets of N. chinensis, pyroptosis, and AF were obtained. The genes underwent molecular docking as well as gene set enrichment analysis (GSEA). A nomogram based on candidate genes was constructed and evaluated with the clinical impact curve. After that, the immune infiltration of the dataset was analyzed by single sample GSEA (ssGSEA). Finally, microRNAs (miRNAs) and transcription factors (TFs) were predicted based on candidate genes.

Results: Tumor necrosis factor (TNF) and caspase-8 (CASP8) were obtained as candidate genes by taking the intersection of DEGs, targets of N. chinensis, and pyroptosis-related genes. Tolllike receptor (TLR) and peroxisome proliferator-activated receptor (PPAR) signaling pathways were linked to candidate genes. Additionally, immune cell infiltration analysis revealed that CASP8 was associated with natural killer T cells, natural killer cells, regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSC), macrophages, CD8 T cells, and CD4 T cells. Finally, miR-34a-5p and several TFs were found to regulate the expression of CASP8 and TNF.

Conclusion: CASP8 and TNF are potential targets of N. chinensis intervention in pyroptosisrelated AF, and the TLR/NLRP3 signaling pathway may be associated with this process.

Background: The Fule Cream (FLC) is an herbal formula widely used for the treatment of pediatric atopic dermatitis (AD), however, the main active components and functional mechanisms of FLC remain unclear. This study performed an initial exploration of the potential acting mechanisms of FLC in childhood AD treatment through analyses of an AD mouse model using network pharmacology, molecular docking technology, and RNA-seq analysis.

Materials and methods: The main bioactive ingredients and potential targets of FLC were collected from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and SwissTargetPrediction databases. An herb-compound-target network was built using Cytoscape 3.7.2. The disease targets of pediatric AD were searched in the DisGeNET, Therapeutic Target Database (TTD), OMIM, DrugBank and GeneCards databases. The overlapping targets between the active compounds and the disease were imported into the STRING database for the construction of the protein-protein interaction (PPI) network. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the intersection targets were performed, and molecular docking verification of the core compounds and targets was then performed using AutoDock Vina 1.1.2. The AD mouse model for experimental verification was induced by MC903.

Results: The herb-compound-target network included 415 nodes and 1990 edges. Quercetin, luteolin, beta-sitosterol, wogonin, ursolic acid, apigenin, stigmasterol, kaempferol, sitogluside and myricetin were key nodes. The targets with higher degree values were IL-4, IL-10, IL-1α, IL-1β, TNFα, CXCL8, CCL2, CXCL10, CSF2, and IL-6. GO enrichment and KEGG analyses illustrated that important biological functions involved response to extracellular stimulus, regulation of cell adhesion and migration, inflammatory response, cellular response to cytokine stimulus, and cytokine receptor binding. The signaling pathways in the FLC treatment of pediatric AD mainly involve the PI3K-Akt signaling pathway, cytokine‒cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and NF-κB signaling pathway. The binding energy scores of the compounds and targets indicate a good binding activity. Luteolin, quercetin, and kaempferol showed a strong binding activity with TNFα and IL-4.

Conclusion: This study illustrates the main bioactive components and potential mechanisms of FLC in the treatment of childhood AD, and provides a basis and reference for subsequent exploration.

Background: Alzheimer's disease (AD) is one of the most concerned neurodegenerative disorders across the world characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs), leading to cognitive decline and memory loss. Targeting key pathways involved in AD like Aβ and NFT pathways, are crucial for the development of effective therapeutic strategies. In this study, we aimed to identify and establish promising dual inhibitors targeting BACE1 and GSK-3β, two proteins implicated in Aβ and NFT formation respectively.

Methods: We have used molecular docking, ADME property analysis, and MMGBSA calculations for the identification of hit molecules and further evaluation of binding affinity, drug-like properties, and stability against BACE1 and GSK-3β.

Results: Our results demonstrated strong binding affinities of ZINC000034853956 towards the active sites of both proteins, with favorable interactions involving key residues crucial for inhibitory activity. Additionally, ZINC000034853956 exhibited favorable drug-like properties. MD simulations revealed the stable binding of ZINC000034853956 to both BACE1 and GSK-3β over a 50 ns period, with consistent ligand-protein interactions, such as hydrogen bonding and hydrophobic contacts. These findings highlight the potential of ZINC000034853956 as a promising candidate for AD treatment, acting as a dual inhibitor targeting both BACE1 and GSK-3β. Overall, our study provides valuable insights into the potential of ZINC000034853956 as a dual inhibitor for AD. The strong binding affinity, favorable drug-like properties, and stability observed in MD simulations support its suitability for further optimization and preclinical studies.

Conclusion: Further investigations are warranted to elucidate the precise molecular mechanisms and therapeutic benefits of ZINC000034853956. Our findings offer hope for the development of novel therapeutic interventions targeting crucial pathways involved in AD neurodegeneration.

Background: Two main factors, which have an influence on oral absorption from solid, immediate release dosage form, are solubility and permeability. These are considered the main fundamental properties that govern the rate and extent of oral absorption. The significance of these properties has been highlighted in the Biopharmaceutics Classification System (BCS).

Objective: The concept of this paper was to predict the solubility and permeability of fluoroquinolones using in silico methods based on the assumptions of the BCS. An attempt was also made to determine the place within this system for drugs from the fluoroquinolone group.

Method: The study was carried out with the use of modern computational techniques which developed based on Artificial Neural Network Ensembles for Binary Classification.

Results: Using the values of the physicochemical descriptors of medicinal compounds with labeled BCS class, two classification models were elaborated for solubility and permeability.

Conclusion: The obtained models helped to predict the provisional class for the following drugs in the BCS. Continuous improvement of computational models may support and can be treated equally with the in vivo data.

The coronavirus nucleocapsid (N) plays an important role in the virus structure, the replication, and the transcription of CoV. This protein, which has a helix and flexible structure, and capable of binding on to the viral genomic RNA, is a non-structural protein (nsp3). Many studies suggest that the N protein interaction with nsp3 plays a critical role in the virus replication early in infection. Therefore, it is necessary to know the definition of the interaction mechanism of N and nsp3 protein in terms of the CoV replication transcription mechanism. We report on the homology modeling, molecular dynamics simulation, and docking studies to explain the structure-function relationship and the interaction mechanism. In addition, the prototype MHV is preferred in the wet experiment, so we also based our study on the MHV N and nsp3 proteins that belong to the experimental study. The amino acid sequences of MHV N and nsp3 proteins have similarity between human and severe acute respiratory syndrome coronavirus. Therefore, the 3D structure models of these proteins were built with using the crystal structure of the CoV family members as a template. By following these models, molecular dynamics simulations were applied to attain the most stable conformation. Finally, protein-protein docking was performed to prove accuracy of model structures of the MHV N and to clarify the interaction with nsp3. As a result, Lys 113, Arg 125, Tyr 127, Glu 173, Tyr 190 residues that play an important role in virus replication were determined.

The increasing mortality due to antibacterial resistance necessitates the search for novel antimicrobial agents. Hence, series of 1-R-2-([1,2,4]triazolo[1,5-c]quinazoline-2-ylthio)etanon(ol)s were synthesized, evaluated by spectral data and studied against St. aureus, M. luteum, E. faecalis, E. aerogenes, P. aeruginosa, C. sakazakii, E.coli, K. pneumonia, hospital Streptococcus spp., C. albicans and A. niger in 100, 500 µg/mL and 100 µg/disk. Substances exhibited moderate toxicity in 0.025, 0.1 and 0.25 mg/mL in bioluminescence inhibition tests of Photobacterium leiognathi. SAR exposed that introduction of 2,4-(Cl)2C6H3-, 2,5-(OMe)2C6H3-, 4-Me-2-iPr-C6H3O- and 3-iPr-C6H4O- fragments and reduction of the pyrimidine ring of R-([1,2,4]triazolo[1,5-c]quinazolin-2-ylthio)alcohols were the best modifications to promote antimicrobial activity. Molecular docking showed their good affinity into the active sites of EcPanK-AMPPNP and hDHFR. Hence, reported results will be used for subsequent QSAR model creation and purposeful antimicrobial modification of the strongest compounds.