Current computer-aided drug design最新文献

Background: Hypertension, a major risk factor for cardiovascular disease morbidity and mortality, remains poorly controlled in many patients despite available treatments. There are many patients with poorly managed blood pressure despite the availability of treatments. We employed Mendelian Randomization (MR) and colocalization analyses of plasma proteins and hypertension to identify genetically supported drug targets.

Methods: We investigated genetic associations between plasma protein quantitative trait loci (pQTLs) and hypertension GWAS data from FinnGen using two-sample MR, enrichment analysis, and Protein-Protein Interaction (PPI) analysis. Colocalization verified shared causal variants between identified proteins and hypertension. Drug prediction and molecular docking were used to assess therapeutic potential.

Results: In the MR analysis, 12 plasma proteins were found to be associated with hypertension, three of which (ACE, AGT, and NPPA) were supported by colocalization. Among these, ACE and AGT are established drug targets, whereas NPPA remains relatively underexplored. Drug prediction and molecular docking results indicated that several candidate drugs exhibited highly stable interactions and strong binding affinities with the screened proteins.

Discussion: Our findings confirm the centrality of the renin-angiotensin system (ACE, AGT) and highlight NPPA as a novel, genetically supported protective target. While the study benefits from robust MR and colocalization methods, the focus on European ancestry warrants validation in diverse populations. Experimental and clinical studies are needed to translate these targets into therapies.

Conclusion: This proteome-wide MR analysis demonstrates a causal relationship between genetically determined levels of ACE, AGT, and NPPA and hypertension. These proteins represent promising targets for the development of novel hypertension therapeutics.

Introduction: Breast cancer is a leading cause of cancer-related mortality in women. Although the traditional Chinese medicine Codonopsis Pilosula (CP) is empirically used in its treatment, the underlying mechanisms of action remain elusive. This study aimed to apply a novel integrative network pharmacology and machine learning approach to identify bioactive compounds in CP and elucidate their anti-breast cancer mechanisms.

Methods: The analysis utilized a comprehensive and innovative workflow that combined network pharmacology, machine learning-based target prediction, bioinformatics analyses, and molecular docking and molecular dynamics simulations. Publicly available datasets were mined for CP constituents and putative targets, and integrated with breast cancer-associated gene profiles. Key compound-target interactions were prioritized via machine learning algorithms.

Results: Machine learning highlighted EGFR and PTGS2 as primary targets. Molecular docking and dynamics demonstrated stable binding of Taraxerol and Stigmasterol to these proteins, with EGFR-Taraxerol, EGFR-Spinasterol, PTGS2-Stigmasterol, and PTGS2-Taraxerol complexes exhibiting robust affinity and stability.

Discussion: The findings are significant as they reveal previously unreported interactions between CP's bioactive compounds and critical breast cancer targets. This provides a molecularlevel explanation for the traditional use of CP, bridging the gap between TCM and modern pharmacology. These results offer a solid foundation for further experimental validation.

Conclusion: This multidisciplinary, predictive strategy successfully identified key bioactive compounds in CP and their molecular targets in breast cancer. The study provides crucial mechanistic evidence for CP's therapeutic potential and highlights the power of this integrated approach for drug discovery from TCM (Traditional Chinese Medicine).

Introduction: Inflammatory bowel disease (IBD) poses a major threat to human health. Current pharmacological therapies primarily manage symptoms and are often associated with adverse effects.

Objective: To develop targeted natural drugs with fewer side effects for IBD therapy by identifying potential agents from medicinal and edible Chinese herbs (MECHs) and clarifying their underlying molecular mechanisms.

Methods: An integrated approach was employed, combining single-cell analysis, transcriptomics, reverse network pharmacology, immunological infiltration assessment, molecular docking, ADMET evaluation, and molecular dynamics (MD) simulations.

Results: Multi-omic integration identified nine differentially infiltrating immune cell types and a CXCL8-CXCR2-driven neutrophil communication axis. Frequent intercellular communication was observed among neutrophils, epithelial cells, monocytes, B cells, and T cells. Topological screening yielded 15 hub targets and identified MMP2 and PTGS2 as key targets. Molecular docking, ADMET analyses, and 100-ns MD simulations converged on the natural product (NP) MOL009551 (isoprincepin) as a high-affinity, stable MMP2 binder (ΔG = -11.0 kcal/mol), supporting MMP2-directed isoprincepin as a novel therapeutic candidate for IBD.

Discussion: Bioinformatic analyses suggest that MMP2 may play an important role in IBD, and isoprincepin, identified from MECHs, may serve as a potential therapeutic agent by modulating MMP2 activity. However, experimental validation of their direct interaction and therapeutic efficacy remains necessary, along with further mechanistic and preclinical studies to clarify their potential for IBD treatment.

Conclusion: This study provides a comprehensive understanding of the molecular mechanisms underlying IBD, identifies MMP2 as a key target, and highlights isoprincepin as a promising natural product for IBD therapy.

Aims: To Discover novel PTP1B inhibitors by high-throughput virtual screening.

Background: Type 2 Diabetes is a significant global health concern. According to projections, the estimated number of individuals affected by the condition will reach 578 million by the year 2030 and is expected to further increase to 700 million deaths by 2045. Protein Tyrosine Phosphatase 1B is an enzymatic protein that has a negative regulatory effect on the pathways involved in insulin signaling. This regulatory action ultimately results in the development of insulin resistance and the subsequent elevation of glucose levels in the bloodstream. The proper functioning of insulin signaling is essential for maintaining glucose homeostasis, whereas the disruption of insulin signaling can result in the development of type 2 diabetes. Consequently, we sought to utilize PTP1B as a drug target in this investigation.

Objective: The purpose of our study was to identify novel PTP1B inhibitors as a potential treatment for managing type 2 diabetes.

Methods: To discover potent PTP1B inhibitors, we have screened the Maybridge HitDiscover database by SBVS. Top hits have been passed based on various drug-likeness rules, toxicity predictions, ADME assessment, Consensus Molecular docking, DFT, and 300 ns MD Simulations.

Results: Compound RJC02059 has been identified with strong binding affinity at the active site of PTP1B along with drug-like properties, efficient ADME, low toxicity, and high stability.

Discussion: Two compounds, demonstrated strong binding affinity, favorable drug-like properties, and stable interactions with PTP1B's active site throughout 200 ns MD simulations, with RJC02059 showing superior binding stability and persistent hydrogen bonding with catalytic residues. However, experimental validation through enzymatic assays and assessment of selectivity against related phosphatases, remain essential next steps to confirm therapeutic potential.

Conclusion: The identified molecule could potentially manage T2DM effectively by inhibiting PTP1B, providing a promising avenue for therapeutic strategies.

Background: As a traditional Chinese medicine, Danshen shows potential efficacy for treating ulcerative colitis (UC). However, the bioactive components and mode of action were unclear.

Aim: This paper uses a combination of network pharmacology, serum medicinal chemistry, and gene expression profiling to clarify its possible molecular mechanism of action and material basis.

Methods: Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was utilized to analyze the herbal components and metabolites from the serum of Danshen-treated mice. Gene expression profiles were applied to construct a database of Danshen action targets. Then, active ingredient-target-biological functional module networks were constructed to analyze the mechanism of action. Molecular docking has further confirmed the possibility of its components to the targets.

Results: As a result, 193 common targets between 1684 Danshen-related DEGs and 1492 UC targets were determined as the potential targets for Danshen in treatment with UC. Serum pharmacochemistry and target prediction showed that 22 components in serum acted on 777 targets. Intersection with common targets yielded 46 core targets, and an active ingredienttarget- biological functional module network was constructed for analysis. Network prediction and molecular docking results showed that the main action modules were inflammatory response and cell apoptosis, which mainly acted on targets SRC, RELA, HSP90AA1, CTNNB1, STAT3, and CASP3. The main components of Danshen intervention in UC were predicted to include Catechol, 3,9-Dimethoxypterocarpan, 8-Prenylnaringenin, Isoferulic acid, Salvianolic acid C, and Danshensu.

Discussion: This work resolved the ambiguity of Danshen's anti-UC material basis and mechanism: 22 serum-absorbed components acted on 46 core targets to modulate inflammation and apoptosis, validating the integrated approach and laying groundwork for UC treatment and TCM research.

Conclusion: The present study provides a scientific foundation for further explicating the mechanisms of Danshen against UC.

Background: Centipeda minima (CM) is a traditional Chinese herbal medicine used for the treatment of sinusitis and rhinitis, and it possesses anti-cancer properties. However, the mechanism of CM in the treatment of nasopharyngeal carcinoma (NPC) remains unclear.

Objective: This study aimed to explore the mechanism of CM in the treatment of NPC using a network pharmacology approach.

Methods: The active components and targets of CM and NPC were screened using TCMSP, SwissTarget, and GeneCards database. The association between CM components and NPC targets or pathways was analyzed using String, Cytoscape 3.9.1, David 6.7, and AutoDock Vina. The Sangerbox platform was used to conduct differential expression and Kaplan-Meier survival analysis of core genes.

Results and discussion: We identified 17 active compounds of CM and 146 corresponding targeted proteins in NPC. These targets may modulate pathways in cancer, PI3K-Akt, apoptosis, prolactin, relaxin, and TNF signaling. The top 5 core genes of the PPI network were found to be AKT1, STAT3, CASP3, EGFR, and SRC, which may be the main targets of CM in treating NPC. Molecular docking confirmed the binding energies of quercetin with CASP3, 8-Hydroxy-9,10-diisobutyryloxythymol with AKT1, and plenolin with AKT1, which were particularly low, suggesting robust and stable interactions. The expression levels of AKT1, CASP3, EGFR, SRC, MMP9, PTGS2 are significantly higher in head and neck squamous cell carcinoma (HNSC) samples compared to normal samples. In addition, the hub genes could predict the prognosis of HNSC as the Kaplan-Meier survival curve showed that patients with lower expressions of AKT1, EGFR, SRC, CCND1, PPARG had better overall survival.

Conclusion: By conducting a network pharmacology approach, we revealed the main ingredients, key targets, and regulatory pathways of Centipeda minima in the treatment of NPC.

Objective: Kushen (Sophora flavescens Ait.) has a long history of medicinal use in China due to its medicinal values, such as antibacterial, antiviral, and anti-inflammatory. Rapid discovery of the components and the medicinal effects exerted by Kushen will help elucidate the science of Kushen in curing diseases. GSK3β (glycogen synthase kinase-3 beta) is a protein kinase with a wide range of physiological functions, such as antibacterial, antiviral, and anti-inflammatory. The discovery of inhibitors targeting GSK3β from Kushen was not only helpful for the rapid discovery of the components responsible for the efficacy of Kushen but also important for the development of novel drugs.

Methods: In this study, the chemical composition of Kushen was extracted from the TMSCP database. Molecular docking, GSK3β enzyme assay, and molecular dynamics simulations were used to discover the GSK3β inhibitors from the chemical composition of Kushen.

Results and discussion: A total of 113 chemical compositions of Kushen were extracted from the TMSCP database. Molecular docking indicated that 15 chemical compositions of Kushen scored better than -8 kcal/mol against GSK3β. GSK3β enzyme assay demonstrated several inhibitory activities of kushenol I and kushenol F with IC₅₀ values of 7.53 ± 2.55 μM and 4.96 ± 1.29 μM, respectively. Molecular dynamics simulations were used to reveal the interactions of kushenol I and kushenol F with GSK3β from structural and energetic perspectives.

Conclusion: Kushenol I and kushenol F could be the material basis for the antibacterial, antiviral, and anti-inflammatory properties of Kushen.

Introduction: DENV NS2B-NS3 protease inhibitors were designed based upon the reference molecule, 4-(1,3-dioxoisoindolin-2-yl)-N-(4-ethylphenyl) benzenesulfonamide, reported by our team with the aim to optimize lead compound via rational approach. Top five best scoring molecules with zinc ids ZINC23504872, ZINC48412318, ZINC00413269, ZINC13998032 and ZINC75249613 bearing 'pyrimidin-4(3H)-one' basic scaffold have been identified as a promising candidate against DENV protease enzyme.

Methods: The shape and electrostatic complementary between identified HITs and reference molecules were found to be Tanimoto_shape 0.453, 0.690, 0.680, 0.685 & 0.672 respectively and Tanimoto_{electrostatic} 0.211, 0.211, 0.441, 0.442, 0.442 and 0.442 respectively. The molecular docking studies suggested that the identified HITs displayed the good interactions with active site residues and lower binding energies. The stability of docked complexes was assessed by MD simulations studies. The RMSD values of protein backbone (1.6779, 3.1563, 3.3634, 3.3893 & 3.0960 Å) and protein backbone RMSF values (1.0126, 1.0834, 1.0890, 0.9974 & 1.0080 Å respectively) for all top five HITs were stable and molecules did not fluctuate from the active pocket during entire 100ns MD run.

Results: The druggability Dscore below 1 indicate the tightly binding of ligand at the active site. Dscore for ZINC23504872 was found to be 1.084 while for the second class of compounds ZINC48412318, ZINC00413269, ZINC13998032 and ZINC75249613, 0.503, 0.484, 0.487 and 0.501 Dscores were observed. In-silico ADMET calculations suggested that all five HITs were possessed the drug likeliness properties and did not violate the Lipinski's rule of five.

Conclusion: Summing up, these in-silico generated data suggested that the identified molecules bearing pyrimidin-4(3H)-one would be promising scaffold for DENV protease inhibitors. However, experimental results are needed to prove the obtained results.