Journal of Biomolecular Structure & Dynamics最新文献

Drug repurposing is preferred over de-novo drug discovery to unveil the therapeutic applications of existing drug candidates before investing considerable resources in unexplored novel chemical entities. This study demonstrated multifaceted stratagems to reconnoiter promising repurposable candidates against Hepatocellular Carcinoma (HCC) by amalgamating Real-World-Data (RWD) with bioinformatics algorithms corroborated with in-silico and in-vitro studies. At the outset, the RWD from the Food and Drug Administration Adverse Event Reporting System (FAERS) was explored to navigate signals to retrieve repurposable drugs that are inversely associated with HCC via Disproportionality Analysis. Further, transcriptomic analysis was used to capture the potential targets of HCC. Following this, the interactions between repurposable drugs and HCC targets were virtually demonstrated via molecular docking and Molecular Dynamics Simulations (MDS). Furthermore, additional cytotoxicity and gene expression experiments were conducted to corroborate the results. Overall, 64 drugs with Drug Event >5 were shortlisted as prospective repurposable drugs as per the RWD obtained from FAERS. The transcriptomic analysis highlighted significant upregulation of Cyclin A2 (CCNA2) in HCC, which activates Cyclin Dependent Kinase 2 (CDK2). Further, in-silico studies identified Losartan and Allopurinol, with docking scores of -7.11 and -6.219, respectively, as potential repurposable drugs. The selected drugs underwent further scrutiny through in-vitro studies. The treatment of HepG2 cells with Allopurinol resulted in significant downregulation of CCNA2/CDK2 expression with an elevation in reactive oxygen species levels, uncovering Allopurinol's anticancer mechanism through cellular apoptosis. This study suggests the importance of RWD in drug repurposing and the potential of Allopurinol as a repurposable drug against HCC.

Triple-negative breast cancer (TNBC), characterized by the absence of Estrogen Receptor (ER), Progesterone Receptor (PR), and amplified HER2, represents an aggressive subtype devoid of targeted therapies, contributing to heightened mortality rates. Matairesinol (MAT) has demonstrated anti-cancer, anti-inflammatory, immunomodulatory, anti-migratory, and antiangiogenic activities. This study investigates MAT's therapeutic potential for TNBC, employing network pharmacology, molecular docking, and molecular dynamics simulations. Through the integration of MAT and TNBC targets from public databases, we identified 47 potential therapeutic targets. Top 10 hub targets, including HIF1A, ESR1, AKT1, EGFR, HSP90AA1, Src, ERBB2, IGF1, ANXA5, and MAPK1, were revealed through protein-protein interaction analysis. Biological enrichments, encompassing GO and KEGG pathway analyses, unveiled insights into functional roles and associated pathways. The Compound-Targets-Pathways-Disease (C-T-P-D) network illustrated relationships between MAT, its targets, and pertinent pathways. Exploring protein-protein interactions with STRING, followed by validation and supplementation using the GeneMANIA-based functional association (GMFA) method and David web wizard, emphasized the MAPK signaling pathway as a more potential target of MAT against TNBC. The biological significance of these findings underscores MAT's potential as a multi-target inhibitor within multiple signaling pathways related to TNBC, showcasing its efficacy against TNBC. Molecular docking and dynamics simulations substantiated the interaction between MAT and the identified hub targets. In conclusion, our in-silico analysis proposes that MAT could mediate a multi-target and multi-pathway anti-TNBC effect with the MAPK pathway as its novel target pathway. These insights into the potential therapeutic mechanisms of MAT offer valuable directions for further research and the development of interventions against TNBC.

Oral squamous cell carcinoma (OSCC), a prevalent form of head and neck cancer, poses a significant health challenge with limited improvements in patient outcomes over the years. Its development is influenced by a complex interplay of genetic alterations and environmental factors. While progress has been made in understanding the molecular mechanisms driving OSCC, pinpointing critical molecular markers and potential drug candidates has proven elusive. This study uniquely endeavors to conduct a meta-analysis to unveil therapeutic genes responsible for OSCC tumorigenesis. A multi-omics approach identified $951$ differentially expressed genes (DEGs) associated with OSCC by analyzing microarray data from the NCBI GEO database. Weighted gene co-expression network analysis (WGCNA) detected a significant hub gene module comprising $805$ genes, followed by the construction of protein-protein interaction network resulting in two small clusters of $7$ gene-encoded proteins each. These clusters were filtered out based on top 10 significant pathways and gene ontology terms to identify six key target proteins with elevated expression levels, acting as potential therapeutic biomarkers for OSCC. Notably, RSAD2 emerged as a novel biomarker linked to OSCC progression. Furthermore, we identified potential inhibitors targeting AURKA, AURKB, and RSAD2 proteins and validated their interactions through molecular dynamics simulation studies. The simulations confirmed the stability of receptor-ligand complexes, suggesting ZINC03839281, ZINC04026167, and ZINC00718292 compounds hold promise as potential inhibitors for therapeutically targeting AURKA, AURKB, and RSAD2 as significant OSCC biomarkers. We recommend further comprehensive studies, including experimental and preclinical investigations, to validate the effectiveness of these lead compounds for OSCC treatment.

1,4-Dialkylamino -5,8-dihydroxy anthraquinones are investigated using density functional theory (DFT) and time-dependent DFT (TD-DFT) for their growth inhibitory potential. The frontier molecular orbital shows that the electron density is located at the anthraquinone core and at the substituents NH and OH in both HOMO as well as in LUMO. The chemical potential and electrophilicity index showed a direct relation, while hardness and hyperhardness had an inverse association with an energy gap. The results of the molecular docking analysis revealed that the anthraquinone molecules have a high affinity for the primary targets of the DNA topoisomerase IIα enzyme. The docking results showed good binding ability with extremely energetically stable scores ranging from -8.9 to -7.6 kcal/mol. Electron correlation descriptors showed a direct link with NLO properties and toxicity.

Pathogenesis and therapeutic drugs for ulcerative colitis (UC) have plagued researchers worldwide. In this study, therapeutic targets, and drugs from Chinese medicines for UC were screened using bioinformatics. We downloaded five datasets from the GEO database and three machine learning algorithms were used for screening diagnostic biomarkers of UC. Combined with the differential genes for UC, gene sets related to bile acid metabolism, short-chain fatty acids, apoptosis, pyroptosis, G-protein-coupled receptors, mitochondria, and autophagy were collected to screen the core targets, and analyze the association of therapeutic genes (diagnostic biomarkers and core targets) with immune cells. In addition, screening ingredients of Chinese medicines based on UC therapeutic targets was performed. Molecular docking, molecular dynamics simulation, and literature validation were also performed. The screening yielded 37 key therapeutic targets, including 5 diagnostic biomarkers (CCL11, CXCL1, PDZK1IP1, TIMP1, and UGT2A3) and 32 core targets based on hot gene sets. Immune cell infiltration was strongly associated with therapeutic targets in UC, especially neutrophils, macrophages, mast cells, and dendritic cells. Furthermore, a total of 33 compounds with high safety had been recognized as having potential to mitigate UC by reverse prediction from Chinese medicines, and molecular docking, molecular dynamics simulation, and literature reports preliminarily validated the screening results. Although further experimental validation is needed, this work provides some potential therapeutic targets and drugs from Chinese medicines against UC.

The development of effective non-nucleoside inhibitors targeting HIV-1 reverse transcriptase (RT) remains a persistent challenge in AIDS research, particularly in overcoming drug-induced mutations. This study focuses on harnessing the potential of Rilpivirine (RPV), a widely recognized non-nucleoside inhibitor, as a foundational structure for designing and synthesizing inhibitors with superior anti-HIV-1 activities compared to RPV. Through strategic conjugation of RPV to molecular umbrellas using diverse linkers such as BSOCOES, DSP, and EGS, a novel series of potent non-nucleoside inhibitors is crafted. Guided by a structure-based drug design approach, this study unveils a new series of non-nucleoside reverse transcriptase inhibitors (NNRTIs). Comprehensive molecular analyses reveal extensive interactions between these NNRTIs and the RT inhibitor-binding pocket, confirming their superior antiviral efficacy against the wild-type virus when compared to RPVs. The innovative strategy employed in this research, focusing on drug-linker-nanocarrier interactions, introduces a promising avenue for designing and developing robust HIV-1 RT inhibitors with potential clinical applications. The findings emphasize the approach's potential for addressing challenges posed by drug-resistant mutations, opening new possibilities for advancing antiretroviral therapy.

Cardiac fibrosis, characterized by excessive extracellular matrix deposition, is a critical contributor to cardiovascular diseases, including heart failure. Transforming growth factor-beta 1 signaling, especially through activin receptor-like kinase 5 (ALK5), plays a key role in cardiac fibroblast activation and fibrosis. Traditional drug discovery approaches face challenges in identifying ALK5 inhibitors. This study leverages computational methods to expedite the discovery of potential ALK5 inhibitors. An active learning model was trained to screen a vast compound library, resulting in the selection of promising candidates. Molecular fingerprint clustering analysis and the absorption, distribution, metabolism, excretion, toxicity evaluation further characterized these compounds. Machine learning-based quantitative structure - activity relationship models predicted their activity. Molecular dynamics simulations assessed binding stability in different environments. DE50349483 and DE21377883 emerged as promising candidates with potential inhibitory effects. This study showcases the power of computational methods in drug discovery, offering hope for innovative therapies in cardiac fibrosis.

The increasing resistance of cancer drugs, especially in the treatment of breast cancer, underlines the urgent need for new and effective cancer drugs. Chemotherapeutic agents based on metal complexes are recognized as highly effective treatment options. The aim of this study is to synthesize a non-platinum chemotherapeutic agent with high efficacy and to investigate its therapeutic effect in mice with tumors. Novel transition metal complexes derived from Schiff base ligands (cobalt(III) H₂salophen complexes) were synthesized, characterized and optimized by quantum calculations based on DFT-D. MDA-MB231 and 4T1 cells were cultured and the scavenging and hemolysis activity, cytotoxic effect, migration and apoptosis were investigated. In addition, the therapeutic effects of the complex were investigated in mice with tumors. The interactions of the target macromolecules were investigated by molecular docking. The results showed that the complexes exhibited considerable cytotoxicity, apoptosis and migration inhibition against tumor cell lines and inhibition of tumor growth in mice, and greatly increased IFN-γ and TNF-α and reduced IL-4 and IL-1β. Data suggest that complex C treatment can enhance immune responses with a Th1 dominance by inducing the secretion of proinflammatory cytokines. Molecular docking experiments confirmed that complex C binds to the most stable state and induces apoptosis by interacting with the DNA minor groove. Our results suggest that complex C triggers apoptosis, leading to a lethal effect on malignant tumor cells, and has the potential to inhibit tumor growth through direct cytotoxic effects. It also stimulates the immune system and alters the cytokine profile.

Breast cancer, the most prevalent cancer in females, is a heterogeneous disease with various molecular subtypes, which presents challenges in diagnosis and treatment. Ubiquitination is one of the most critical post-translational protein modifications, that plays regulatory roles in numerous cellular processes including cell cycle progression, DNA replication & repair, apoptosis, transcription regulation, protein localization, trafficking and signal transduction. This modification can be reversed by deubiquitinases, or DUBs, a superfamily of cysteine proteases and metalloproteases that cleave ubiquitin-protein bonds. Dysregulation of DUBs has been associated to various diseases including cancer, making them promising targets for cancer therapy. We leveraged publicly available breast cancer datasets and employed various bioinformatics tools to identify differentially expressed DUBs in breast cancer. Our analysis identified six genes (COPS5, EIF3H, MINDY1, MINDY2, PSMD14 and USP26) with significant differential expression and survival implications. We further validated our findings experimentally and found upregulation of COPS5, EIF3H and MINDY 1 in MCF-7 and T47D breast cancer cell lines using qPCR analysis. To identify the role of these genes, EIF3H and COPS5, in disease progression, we constructed a protein-protein interaction (PPI) network with genes associated with metastasis and explored their correlation at the gene expression level in breast cancer patients. Together, this comprehensive study sheds light on DUB gene expression patterns in breast cancer with the potential to identify novel targets for therapeutic interventions.

Cervical cancer burden due to recurrent human papillomavirus (HPV) infections necessitates the urgent need to impede viral proliferation targeting the oncogene E6 of the high-risk serotype HPV16. This study aims to identify a small molecule from a natural product library that could prevent a tumorigenic complex of E6 with p53 in HPV16-positive cervical cancer cells. In silico methods such as high-throughput virtual screening (HTVS) of natural product like library ZINC database followed by atomistic molecular dynamics (MD) simulations were performed to identify lead natural compound. This was validated with in vitro analysis using HPV16 positive SiHa cells and CaSki cells by MTT and flow cytometry assays. Virtual screening identified top 10 compounds with high affinity for HPV16 E6. The docking scores, Protein-Ligand Interaction Profiler analysis, MD simulation and molecular mechanics Poisson Boltzmann surface area-based binding energy estimation narrowed down the search to ZINC1797251, a molecule with stable binding, low energy scores and consistent H-bonds, establishing that it could prevent interaction of p53 and E6. ZINC1797251 inhibited the proliferation of SiHa and CaSki cells with a G_I50 values of 615.40 and 417.30 nM, respectively. The compound reduced HPV16 E6, while increased p53 positive populations in SiHa and CaSki cells. Treatment with ZINC1797251 induced the G₁ cell phase arrest and promoted early and late phase apoptosis in these cells. The restoration of tumor inhibitory activity of p53 in HPV-infected cervical cancer cells to promote apoptosis could be achieved using the ZINC molecule-ZINC1797251. However, further studies are deemed essential for further developments.