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Showing 2231 to 2234 of 5186 entries
Published on November 24, 2020
Uncovering the pharmacological mechanism of the effects of the Banxia-Xiakucao Chinese Herb Pair on sleep disorder by a systems pharmacology approach.
Abstract: Sleep disorder (SD) has a high incidence and seriously affects quality of life, mental health and even the manifestation of physical diseases. The combination of Pinellia ternata (Chinese name: banxia) and Prunella vulgaris (Chinese name: xiakucao), known as the Banxia-Xiakucao Chinese herb pair (BXHP), is a proven Chinese herbal medicine that has been used to treat SD for thousands of years due to its significant clinical effects. However, its active pharmacological components and sedative-hypnotic mechanisms have not been fully elucidated. Thus, the present study used a systematic pharmacological approach to develop pharmacokinetic screens and target predictions via construction of a protein-protein interaction network and annotation database for SD-related and putative BXHP-related targets. Visualization, screening and integrated discovery enrichment analyses were conducted. The BXHP chemical database contains 166 compounds between the two herbal ingredients, and of these, 22 potential active molecules were screened by pharmacokinetic evaluation. The targets of 114 of the active molecules were predicted, and 34 were selected for further analysis. Finally, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses suggested that BXHP can reduce inflammatory responses. and mediate immune-related and central nervous system neurotransmitters via regulation of multiple targets and pathways. The use of a systematic pharmacology-based approach in the present study further elucidated the mechanisms of action underlying BXHP for the treatment of SD from a holistic perspective and sheds light on the systemic mechanisms of action of Chinese herbal medicines in general.
Published on November 24, 2020
Targeting the renin-angiotensin signaling pathway in COVID-19: Unanswered questions, opportunities, and challenges.
Abstract: The role of the renin-angiotensin signaling (RAS) pathway in COVID-19 has received much attention. A central mechanism for COVID-19 pathophysiology has been proposed: imbalance of angiotensin converting enzymes (ACE)1 and ACE2 (ACE2 being the severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] virus "receptor") that results in tissue injury from angiotensin II (Ang II)-mediated signaling. This mechanism provides a rationale for multiple therapeutic approaches. In parallel, clinical data from retrospective analysis of COVID-19 cohorts has revealed that ACE inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) may be beneficial in COVID-19. These findings have led to the initiation of clinical trials using approved drugs that target the generation (ACEIs) and actions (ARBs) of Ang II. However, treatment of COVID-19 with ACEIs/ARBs poses several challenges. These include choosing appropriate inclusion and exclusion criteria, dose optimization, risk of adverse effects and drug interactions, and verification of target engagement. Other approaches related to the RAS pathway might be considered, for example, inhalational administration of ACEIs/ARBs (to deliver drugs directly to the lungs) and use of compounds with other actions (e.g., activation of ACE2, agonism of MAS1 receptors, beta-arrestin-based Angiotensin receptor agonists, and administration of soluble ACE2 or ACE2 peptides). Studies with animal models could test such approaches and assess therapeutic benefit. This Perspective highlights questions whose answers could advance RAS-targeting agents as mechanism-driven ways to blunt tissue injury, morbidity, and mortality of COVID-19.
Published on November 23, 2020
The urgent need for pan-antiviral agents: from multitarget discovery to multiscale design.
Abstract:
Published on November 21, 2020
Exploring the mechanism of resistance to sorafenib in two hepatocellular carcinoma cell lines.
Abstract: Sorafenib has long been the only approved systemic therapy for advanced hepatocellular carcinoma (HCC), but most patients show primary or acquired drug resistance. In the present study, RNA was extracted from sorafenib-resistant and -sensitive clones of the HCC cell lines HepG2 and Huh7. Protein-protein interaction networks of the up- and down-regulated genes common to the two sorafenib-resistant cell lines were extracted and subjected to modular analysis in order to identify functional modules. Functional enrichment analysis showed the modules were involved in different biological processes and pathways. These results indicate that sorafenib resistance in HCC is complicated and heterogeneous. The potential regulators of each functional module, including transcription factors, microRNAs and long non-coding RNAs, were explored to construct a comprehensive transcriptional regulatory network related to sorafenib resistance in HCC. Our results provide new insights into sorafenib resistance of HCC at the level of transcriptional regulation.
Published on November 20, 2020
KIAA0101 as a new diagnostic and prognostic marker, and its correlation with gene regulatory networks and immune infiltrates in lung adenocarcinoma.
Abstract: Proliferating cell nuclear antigen binding factor (encoded by KIAA0101/ PCLAF) regulates DNA synthesis and cell cycle progression; however, whether the level of KIAA0101 mRNA in lung adenocarcinoma is related to prognosis and tumor immune infiltration is unknown. In patients with lung adenocarcinoma, the differential expression of KIAA0101 was analyzed using the Oncomine, GEPIA, and Ualcan databases. The prognosis of patients with different KIAA0101 expression levels was evaluated using databases such as Prognostan and GEPIA. Tumor immune infiltration associated with KIAA0101 was analyzed using TISIDB. Linkedmics was used to perform gene set enrichment analysis of KIAA0101. KIAA0101 expression in lung adenocarcinoma tissues was higher than that in normal lung tissues. Patients with lung adenocarcinoma with low KIAA0101 expression had a better prognosis than those with high KIAA0101 expression. We constructed the gene regulatory network of KIAA0101 in lung adenocarcinoma. KIAA0101 appeared to play an important role in the regulation of tumor immune infiltration and targeted therapy in lung adenocarcinoma. Thus, KIAA0101 mRNA levels correlated with the diagnosis, prognosis, immune infiltration, and targeted therapy in lung adenocarcinoma. These results provide new directions to develop diagnostic criteria, prognostic evaluation, immunotherapy, and targeted therapy for lung adenocarcinoma.
Published on November 20, 2020
Generating Multibillion Chemical Space of Readily Accessible Screening Compounds.
Abstract: An approach to the generation of ultra-large chemical libraries of readily accessible ("REAL") compounds is described. The strategy is based on the use of two- or three-step three-component reaction sequences and available starting materials with pre-validated chemical reactivity. After the preliminary parallel experiments, the methods with at least approximately 80% synthesis success rate (such as acylation - deprotection - acylation of monoprotected diamines or amide formation - click reaction with functionalized azides) can be selected and used to generate the target chemical space. It is shown that by using only on the two aforementioned reaction sequences, a nearly 29-billion compound library is easily obtained. According to the predicted physico-chemical descriptor values, the generated chemical space contains large fractions of both drug-like and "beyond rule-of-five" members, whereas the strictest lead-likeness criteria (the so-called Churcher's rules) are met by the lesser part, which still exceeds 22 million.
Published on November 19, 2020
Network-based approach highlighting interplay among anti-hypertensives: target coding-genes: diseases.
Abstract: Elucidating the relation between the medicines: targets, targets: diseases and diseases: diseases are of fundamental significance as-is for societal benefit. Hypertension is one of the dangerous health conditions prevalent in society, is a risk factor for several other diseases if left untreated and anti-hypertensives (AHs) are the approved drugs to treat it. The goal of the study is to decipher the connection between hypertension with other health conditions, however, is challenging due to the large interactome. To fulfill the aim, the strategy involves prior clustering of the AHs into groups as per our previous method, followed by the analyzing functional association of the target coding-genes (tc-genes) and health conditions for each group. Following our recently published work where the AHs are clustered into six groups such that molecules having similar patterns come together, here, the distribution of molecular functions and the cellular components adopted by the tc-genes of each group are analyzed. The analyses indicate that kidney, heart, brain or lung related ailments are commonly associated with the tc-genes. The association of selective tc-genes to health conditions suggests a preference for certain health conditions despite many possibilities. Analyses of experimentally validated drug-drug combinations indicate the trend in successful AHs combinations. Clinically validated combinations bind different targets. Our study provides a promising methodology in a network-based approach that considers the influence of structural diversity of AHs to the functional perspective of tc-genes concerning the health conditions. The method could be extended to explore disease-disease relationships.
Published on November 19, 2020
Actionable Cytopathogenic Host Responses of Human Alveolar Type 2 Cells to SARS-CoV-2.
Abstract: Human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative pathogen of the COVID-19 pandemic, exerts a massive health and socioeconomic crisis. The virus infects alveolar epithelial type 2 cells (AT2s), leading to lung injury and impaired gas exchange, but the mechanisms driving infection and pathology are unclear. We performed a quantitative phosphoproteomic survey of induced pluripotent stem cell-derived AT2s (iAT2s) infected with SARS-CoV-2 at air-liquid interface (ALI). Time course analysis revealed rapid remodeling of diverse host systems, including signaling, RNA processing, translation, metabolism, nuclear integrity, protein trafficking, and cytoskeletal-microtubule organization, leading to cell cycle arrest, genotoxic stress, and innate immunity. Comparison to analogous data from transformed cell lines revealed respiratory-specific processes hijacked by SARS-CoV-2, highlighting potential novel therapeutic avenues that were validated by a high hit rate in a targeted small molecule screen in our iAT2 ALI system.
Published on November 18, 2020
Target-Centered Drug Repurposing Predictions of Human Angiotensin-Converting Enzyme 2 (ACE2) and Transmembrane Protease Serine Subtype 2 (TMPRSS2) Interacting Approved Drugs for Coronavirus Disease 2019 (COVID-19) Treatment through a Drug-Target Interaction Deep Learning Model.
Abstract: Previously, our group predicted commercially available Food and Drug Administration (FDA) approved drugs that can inhibit each step of the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using a deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI). Unfortunately, additional clinically significant treatment options since the approval of remdesivir are scarce. To overcome the current coronavirus disease 2019 (COVID-19) more efficiently, a treatment strategy that controls not only SARS-CoV-2 replication but also the host entry step should be considered. In this study, we used MT-DTI to predict FDA approved drugs that may have strong affinities for the angiotensin-converting enzyme 2 (ACE2) receptor and the transmembrane protease serine 2 (TMPRSS2) which are essential for viral entry to the host cell. Of the 460 drugs with Kd of less than 100 nM for the ACE2 receptor, 17 drugs overlapped with drugs that inhibit the interaction of ACE2 and SARS-CoV-2 spike reported in the NCATS OpenData portal. Among them, enalaprilat, an ACE inhibitor, showed a Kd value of 1.5 nM against the ACE2. Furthermore, three of the top 30 drugs with strong affinity prediction for the TMPRSS2 are anti-hepatitis C virus (HCV) drugs, including ombitasvir, daclatasvir, and paritaprevir. Notably, of the top 30 drugs, AT1R blocker eprosartan and neuropsychiatric drug lisuride showed similar gene expression profiles to potential TMPRSS2 inhibitors. Collectively, we suggest that drugs predicted to have strong inhibitory potencies to ACE2 and TMPRSS2 through the DTI model should be considered as potential drug repurposing candidates for COVID-19.
Published on November 17, 2020
Pangenome Analysis of Mycobacterium tuberculosis Reveals Core-Drug Targets and Screening of Promising Lead Compounds for Drug Discovery.
Abstract: Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), is one of the leading causes of human deaths globally according to the WHO TB 2019 report. The continuous rise in multi- and extensive-drug resistance in M. tuberculosis broadens the challenges to control tuberculosis. The availability of a large number of completely sequenced genomes of M. tuberculosis has provided an opportunity to explore the pangenome of the species along with the pan-phylogeny and to identify potential novel drug targets leading to drug discovery. We attempt to calculate the pangenome of M. tuberculosis that comprises a total of 150 complete genomes and performed the phylo-genomic classification and analysis. Further, the conserved core genome (1251 proteins) is subjected to various sequential filters (non-human homology, essentiality, virulence, physicochemical parameters, and pathway analysis) resulted in identification of eight putative broad-spectrum drug targets. Upon molecular docking analyses of these targets with ligands available at the DrugBank database shortlisted a total of five promising ligands with projected inhibitory potential; namely, 2'deoxy-thymidine-5'-diphospho-alpha-d-glucose, uridine diphosphate glucose, 2'-deoxy-thymidine-beta-l-rhamnose, thymidine-5'-triphosphate, and citicoline. We are confident that with further lead optimization and experimental validation, these lead compounds may provide a sound basis to develop safe and effective drugs against tuberculosis disease in humans.
Showing 2231 to 2234 of 5186 entries