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- Volume 27, Issue 17, 2024
Combinatorial Chemistry & High Throughput Screening - Volume 27, Issue 17, 2024
Volume 27, Issue 17, 2024
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Computational Advancement towards the Identification of Natural Inhibitors for Dengue Virus: A Brief Review
Viral infectious illnesses represent a severe hazard to human health due to their widespread incidence worldwide. Among these ailments, the dengue virus (DENV) infection stands out. World Health Organization (WHO) estimates that DENV infection affects ~400 million people each year, with potentially fatal symptoms showing up in 1% of the cases. In several instances, academic and pharmaceutical researchers have conducted several pilot and clinical studies on a variety of topics, including viral epidemiology, structure and function analyses, infection source and route, therapeutic targets, vaccinations, and therapeutic drugs. Amongst Takeda, TAK-003, Sanofi, Dengvaxia®, and Butantan/NIH/Merck, Dengvaxia® (CYD-TDV) is the only licensed vaccination yet; however, the potential inhibitors are under development. The biology and evolution of DENVs are briefly discussed in this review, which also compiles the most recent studies on prospective antiviral targets and antiviral candidates. In conclusion, the triumphs and failures have influenced the development of anti-DENV medications, and the findings in this review article will stimulate more investigation.
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Exploring the Targets of Dengue Virus and Designs of Potential Inhibitors
Authors: Sayan Nath, Piyali Malakar, Baisakhi Biswas, Suryatapa Das, Nahid Sabnam, Sisir Nandi and Asmita SamadderBackground: Dengue, a mosquito-borne viral disease spread by the dengue virus (DENV), has become one of the most alarming health issues in the global scenario in recent days. The risk of infection by DENV is mostly high in tropical and subtropical areas of the world. The mortality rate of patients affected with DENV is ever-increasing, mainly due to a lack of anti-dengue viral-specific synthetic drug components. Introduction: Repurposing synthetic drugs has been an effective tool in combating several pathogens, including DENV. However, only the Dengvaxia vaccine has been developed so far to fight against the deadly disease despite the grave situation, mainly because of the limitations of understanding the actual pathogenicity of the disease. Methods: To address this particular issue and explore the actual disease pathobiology, several potential targets, like three structural proteins and seven non-structural (NS) proteins, along with their inhibitors of synthetic and natural origin, have been screened using docking simulation. Results: Exploration of these targets, along with their inhibitors, has been extensively studied in culmination with molecular docking-based screening to potentiate the treatment. Conclusion: These screened inhibitors could possibly be helpful for the designing of new congeneric potential compounds to combat dengue fever and its complications.
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Proposition of In silico Pharmacophore Models for Malaria: A Review
In the field of medicinal chemistry, the concept of pharmacophore refers to the specific region of a molecule that possesses essential structural and chemical characteristics for binding to a receptor and eliciting biological activity. Understanding the pharmacophore is crucial for drug research and development, as it allows the design of new drugs. Malaria, a widespread disease, is commonly treated with chloroquine and artemisinin, but the emergence of parasite resistance limits their effectiveness. This study aims to explore computer simulations to discover a specific pharmacophore for Malaria, providing new alternatives for its treatment. A literature review was conducted, encompassing articles proposing a pharmacophore for Malaria, gathered from the "Web of Science" database, with a focus on recent publications to ensure up-to-date analysis. The selected articles employed diverse methods, including ligand-based and structurebased approaches, integrating molecular structure and biological activity data to yield comprehensive analyses. Affinity evaluation between the proposed pharmacophore and the target receptor involved calculating free energy to quantify their interaction. Multiple linear regression was commonly utilized, though it is sensitive to multicollinearity issues. Another recurrent methodology was the use of the Schrödinger package, employing tools such as the Phase module and the OPLS force field for interaction analysis. Pharmacophore model proposition allows threedimensional representations guiding the synthesis and design of new biologically active compounds, offering a promising avenue for discovering therapeutic agents to combat Malaria.
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Chemical Probes Review: Choosing the Right Path Towards Pharmacological Targets in Drug Discovery, Challenges and Future Perspectives
Authors: Ashima Ahuja, Sonia Singh and Yogesh MurtiChemical probes are essential for academic research and target validation for disease identification. They facilitate drug discovery, target function investigation, and translation studies. A chemical probe provides starting material that can accelerate therapeutic values and safety measures for identifying any biological target in drug discovery. Essential read outs depend on their versatility in biochemical testing, proving the hypothesis, selectivity, specificity, affinity towards the target site, and valuable in new therapeutic approaches. Disease management will depend upon chemical probes as a primitive tool to ascertain the physicochemical stability for in vivo and in vitro studies useful for clinical trials and industrial application in the future. For cancer research, bacterial infection, and neurodegenerative disorders, chemical probes are integrated circuits which are on pipeline for the drug discovery process Furthermore, pharmacological modulators incorporate activators, crosslinkers, degraders, and inhibitors. Reports accessed depend on their structural, mechanical, biochemical, and pharmacological characterization in drug discovery research. The perspective for designing any chemical probes concludes with the utilization of drug discovery and identification of the potential target. It focuses mainly on evidence-based studies and produces promising results in successfully delivering novel therapeutics to treat cancers and other disorders at the target site. Moreover, natural product pharmacophores like rapamycin, cephalosporin, and α-lactamase are utilized for drug discovery. Chemical probes revolutionize computational-based study design depending on identifying novel targets within the database framework. Chemical probes are the clinical answers for drug development and goforward tools in solving other riddles for scientists and researchers working in this industries.
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Based on Bioinformatics to Explore the Mechanism of “Tangzhiqing” Decoction Alleviating Type 2 Diabetes-associated Cognitive Dysfunction in Mice by Regulating Hippocampal Neuron Apoptosis and Autophagy
More LessBackground: Diabetic cognitive dysfunction (DCD) is emerging as a chronic complication of diabetes that is gaining increasing international recognition. The traditional Chinese medicine (TCM) formulation, Tangzhiqing decoction (TZQ), has shown the capacity to modulate the memory function of mice with DCD by ameliorating insulin resistance. Nevertheless, the precise mechanism underlying the effects of TZQ remains elusive. Methods: The chemical constituents of TZQ were screened using TCMSP databases, and DCDassociated disease targets were retrieved from various databases. Subsequently, core targets were identified through network topology analysis. The core targets underwent analysis using Gene Ontology (GO) functional annotations and enrichment in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Models were established through high-fat and high-glucose diet feeding along with intraperitoneal injection of streptozotocin (STZ). TZQ and metformin were administered at varying doses over 8 weeks. The Morris water maze was employed to evaluate the cognitive capabilities of each rat group, while indicators of oxidative stress and insulin were assessed in mice. Neuronal apoptosis in distinct groups of mice's hippocampi was detected using TdT-mediated dUTP Nick-End Labeling (TUNEL), and western blot (WB) analysis was conducted to assess the expression of apoptosis- and autophagy-related proteins, including Bax, Bcl2, Caspase3, Caspase8, Beclin1, ATG7, LC3, p62, and Lamp2, within the hippocampus. Results: TZQ exhibited the capacity to modulate neuronal autophagy, ameliorate endoplasmic reticulum stress, apoptosis, inflammation, and oxidative stress, as well as to regulate synaptic plasticity and conduction. TZQ mitigated cognitive dysfunction in mice, while also regulating hippocampal inflammation and apoptosis. Additionally, it influenced the protein expression of autophagy-related factors such as Bax, Bcl2, Caspase3, Caspase8, Beclin1, ATG7, and LC3. Notably, this modulation significantly reduced neuronal apoptosis in the hippocampus and curbed excessive autophagy. Conclusion: TZQ demonstrated a substantial reduction in neuronal apoptosis within the hippocampus and effectively suppressed excessive autophagy.
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Evaluation of the Mechanism of Yishan Formula in Treating Breast Cancer Based on Network Pharmacology and Experimental Verification
Authors: Xiaoyue Lin, Wencheng Chi, Xue Geng, Qinghui Jiang, Baozhu Ma, Bowen Dai, Yutong Sui and Jiakang JiangBackground: Yishan formula (YSF) has a significant effect on the treatment of breast cancer, which can improve the quality of life and prolong the survival of patients with breast cancer; however, its mechanism of action is unknown. Objective: In this study, network pharmacology and molecular docking methods have been used to explore the potential pharmacological effects of the YSF, and the predicted targets have been validated by in vitro experiments. Methods: Active components and targets of the YSF were obtained from the TCMSP and Swiss target prediction website. Four databases, namely GeneCards, OMIM, TTD, and DisGeNET, were used to search for disease targets. The Cytoscape v3.9.0 software was utilized to draw the network of drug-component-target and selected core targets. DAVID database was used to analyze the biological functions and pathways of key targets. Finally, molecular docking and in vitro experiments have been used to verify the hub genes. Results: Through data collection from the database, 157 active components and 618 genes implicated in breast cancer were obtained and treated using the YSF. After screening, the main active components (kaempferol, quercetin, isorhamnetin, dinatin, luteolin, and tamarixetin) and key genes (AKT1, TP53, TNF, IL6, EGFR, SRC, VEGFA, STAT3, MAPK3, and JUN) were obtained. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the YSF could affect the progression of breast cancer by regulating biological processes, such as signal transduction, cell proliferation and apoptosis, protein phosphorylation, as well as PI3K-Akt, Rap1, MAPK, FOXO, HIF-1, and other related signaling pathways. Molecular docking suggested that IL6 with isorhamnetin, MAPK3 with kaempferol, and EGFR with luteolin have strong binding energy. The experiment further verified that YSF can control the development of breast cancer by inhibiting the expression of the hub genes. Conclusion: This study showed that resistance to breast cancer may be achieved by the synergy of multiple active components, target genes, and signal pathways, which can provide new avenues for breast cancer-targeted therapy.
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Investigating High-risk Factors, Precise Diagnosis, and Treatment of Castration- Resistant Prostate Cancer (CRPC)
More LessBackground: The treatment of metastatic castration-resistant prostate cancer (mCRPC) in the actual world currently presents difficulties. In light of this, it is crucial to investigate high-risk factors for the progression of advanced prostate cancer and to identify methods for delaying the onset of CRPC. Aims: This study aimed to explore the high-risk factors that impact the progression of prostate cancer and emphasize the significance of precise diagnosis and treatment based on etiological classification in the clinical management of castration-resistant prostate cancer. Methods: A retrospective analysis was conducted on 277 newly diagnosed cases of PCa treated with endocrine therapy. A follow-up was done on prostate-specific antigen (PSA) levels and testosterone. Additionally, a prospective analysis was performed on the clinical data of 60 patients with CRPC. Following the principle of "4W1H", 30 patients were included in the precision treatment group for a second biopsy and related tests, while another 30 patients were included in the conventional treatment group. The therapeutic effect and prognosis of the two groups were observed. Results: Distant metastasis (HR = 1.879, 95% CI: 1.311 ~ 2.694, P = 0.001), PSA nadir > 0.2 ng/mL (HR = 1.843, 95% CI: 1.338 ~ 2.540, P = 0.001), testosterone nadir > 20 ng/dL (HR = 1.403, 95% CI: 1.035 ~ 1.904, P = 0.029), and time to testosterone nadir > 6 months (HR = 1.919, 95% CI: 1.364 ~ 2.701, P = 0.001) were risk factors for the progression to CRPC. Patients in the CRPC group were treated with precision therapy and conventional therapy based on their molecular subtyping. The precision treatment group showed a significantly prolonged median PSA progression-free survival compared to the conventional treatment group (16.0 months vs. 13.0 months, P=0.025). The median radiographic progression-free survival was also significantly extended in the precision treatment group compared to the conventional treatment group (21.0 months vs. 16.0 months, P=0.042). Conclusion: Patients with prostate cancer diagnosed with distant metastasis at initial presentation require early intervention. Close monitoring of PSA and serum testosterone changes is necessary during the process of endocrine therapy. After entering the CRPC stage, the etiological classification precision treatment can improve the therapeutic effect and improve the prognosis of patients.
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Gegen Qinlian Decoction Modulates Atherosclerosis and Lipid Metabolism Through Cellular Interplay and Signaling Pathways
More LessObjective: The objective of this study is to investigate Gegen Qinlian decoction (GQD) effects on lipid metabolism and explore its mechanism for preventing and treating atherosclerosis. Methods: An atherosclerotic rat model was established, and after an 8-week high-fat diet, atherosclerosis and non-alcoholic fatty liver disease were assessed. Subsequently, GQD was administered at low and high doses. Histopathological aortic wall changes, hepatic lipid deposition, and blood lipid changes were evaluated. ELISA indicated the influence of TNF-α and IL-13, and Western blotting revealed MerTK, ABCA1, and LXR-α expression. A foam macrophage model was established, and Cell activity was detected by the MTT method. ELISA indicated the influence of PPAR-γ. The expression of ABCA1, ABCA7, ABCG1, GAS6, MerTK, SCARB1, LXR- α and LXR-β mRNA were detected by qPCR and Western blotting revealed MerTK and LXR-α expression. The impact of drug-containing serum of GQD on efferocytosis-related factors was studied. Results: GQD improved atherosclerosis and non-alcoholic fatty liver disease and reduced serum low-density lipoprotein levels in the high-dose group. The high- and low-dose groups showed upregulated ABCA1, MerTK, and LXR-α expression in blood vessels and the liver, respectively. GQD decreased serum TNF-α and increased IL-13 levels. PPAR-γ expression was elevated in the high-, and low-dose groups. In the high-and low-dose groups, ABCA7, GAS6, SCARB1, and LXR-α, ABCA1 and MerTK, and ABCG1 gene expression were upregulated, respectively. Both low- and high-dose serum-containing drugs promoted LXR-β gene expression, and LXR-α protein expression was improved in the high-dose group. Conclusion: GQD improves rat atherosclerosis and hepatic lipid metabolism by regulating PPAR-γ, LXR-α, LXR-β, ABCA1, ABCA7, and ABCG1 expression and augmenting cellular intercalation through the GAS6/TAM pathway.
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Volumes & issues
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Volume 28 (2025)
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Volume 27 (2024)
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Volume 26 (2023)
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Volume 25 (2022)
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Volume 24 (2021)
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Volume 23 (2020)
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Volume 22 (2019)
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Volume 21 (2018)
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Volume 20 (2017)
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Volume 19 (2016)
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Volume 18 (2015)
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Volume 17 (2014)
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Volume 16 (2013)
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Volume 15 (2012)
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Volume 14 (2011)
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Volume 13 (2010)
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Volume 12 (2009)
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Volume 11 (2008)
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Volume 10 (2007)
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Volume 9 (2006)
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Volume 8 (2005)
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Volume 7 (2004)
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Volume 6 (2003)
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Volume 5 (2002)
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Volume 4 (2001)
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Volume 3 (2000)
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Label-Free Detection of Biomolecular Interactions Using BioLayer Interferometry for Kinetic Characterization
Authors: Joy Concepcion, Krista Witte, Charles Wartchow, Sae Choo, Danfeng Yao, Henrik Persson, Jing Wei, Pu Li, Bettina Heidecker, Weilei Ma, Ram Varma, Lian-She Zhao, Donald Perillat, Greg Carricato, Michael Recknor, Kevin Du, Huddee Ho, Tim Ellis, Juan Gamez, Michael Howes, Janette Phi-Wilson, Scott Lockard, Robert Zuk and Hong Tan
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