Expression-based discovery of candidate ovule development regulators through transcriptional profiling of ovule mutants

Background  

Arabidopsis ovules comprise four morphologically distinct parts: the nucellus, which contains the embryo sac, two integuments that become the seed coat, and the funiculus that anchors the ovule within the carpel. Analysis of developmental mutants has shown that ovule morphogenesis relies on tightly regulated genetic interactions that can serve as a model for developmental regulation. Redundancy, pleiotropic effects and subtle phenotypes may preclude identification of mutants affecting some processes in screens for phenotypic changes. Expression-based gene discovery can be used access such obscured genes.     

In silico screening of anti-inflammatory compounds from Lichen by targeting cyclooxygenase-2

Abstract

Non-steroidal anti-inflammatory drugs (NSAID) targeting cyclooxygenase-2 are clinically effective. However, they lack anti-thrombotic activity resulting in incidences of adverse effects like myocardial infarction, gastrointestinal and abdominal discomfort which necessitate for discovering new drug candidates with improved therapeutic effects and tolerability. Various recent researches have suggested that many lichens offer a vast reservoir for anti-inflammatory drug candidates which are natural as well as safe for human consumption. Drug discovery is a very complex and time-consuming process; however, in silico techniques can make this process simple and economic. Hence to find out natural anti-inflammatory compounds, we have carried out the virtual screening of 412 lichen compounds by molecular docking with human Cox-2 enzyme and validated the docking score by X-Score followed by ADMET and Drug-likeness analysis. The resulting 6 top-scored compounds were subjected to Molecular dynamics simulation (MDS) to analyze the stability of docked protein-ligand complex, to assess the fluctuation and conformational changes during protein-ligand interaction. The values of RMSD, Rg, and interaction energy after 30?ns of MDS revealed the good stability of these Lichen compounds in the active site pocket of Cox-2 in compare to reference, JMS. Additionally, we have done the pharmacophore analysis which found many common pharmacophore features between Lichen compounds and well known anti-inflammatory compounds. Our result shows that these lichen compounds are potential anti-inflammatory candidates and could be further modified and evaluated to develop more effective anti-inflammatory drugs with fewer side effects for the treatment of inflammatory diseases.

Communicated by Ramaswamy H. Sarma     

Virtual high-throughput in silico screening

In silico methods may benefit drug discovery and development significantly by saving an average of $130 million and 0.8 years per drug. Virtual high-throughput screening (vHTS) applies in silico approaches, such as docking and alignment, to large virtual molecular databases to enrich biologically active compounds in order to yield lead structures. In an industrial environment, the commonly used ligand-based and receptor-based methods outlined here need to be computationally faster to return the utmost benefit. Intelligent database searching using new fast feedback-driven screening methods appears to be particularly rewarding in terms of both cost and time benefits.     

RAI, one candidate gene associated with differentiation of human lung adenocarcinoma cells

From all-trans retinoic acid (ATRA)-treated human lung adenocarcinoma GLC-82 cells and control, subtractive cDNA library has been constructed using subtractive hybridization technique in our laboratory. The screening of the cDNA subtractive library resulted in identification of a clone containing cDNA fragment of one ATRA-induced gene (RAI) in GLC-82 cells. The positive clone with full-length cDNA of RAI was identified by screening fetal brain cDNA library using colony hybridization technique, and then sequenced. RT-PCR results showed that RAI was expressed in many different human fetal tissues. These results suggest that RAI may be involved in cell differentiation and play an important role in vital activities of cells.     

RAI , one candidate gene associated with differentiation of human lung adenocarcinoma cells

From all-trans retinoic acid (ATRA)-treated human lung adenocarcinoma GLC-82 cells and control, subtractive cDNA library has been constructed using subtractive hybridization technique in our laboratory. The screening of the cDNA subtractive library resulted in identification of a clone containing cDNA fragment of one ATRA-induced gene (RAI) in GLC-82 cells. The positive clone with full-length cDNA of RAI was identified by screening fetal brain cDNA library using colony hybridization technique, and then sequenced. RT-PCR results showed that RAI was expressed in many different human fetal tissues. These results suggest that RAI may be involved in cell differentiation and play an important role in vital activities of cells.     

肺腺癌预后相关miRNA生物信息学筛选及其临床意义

目的：探讨肺腺癌预后相关miRNA组学特征及其临床意义。方法：应用癌症基因组图谱（TCGA）数据库,检索人肺腺癌miRNA表达谱数据,进行差异分析,再利用Cox风险回归模型筛选预后相关miRNA;利用mirwalk分析平台,对筛选出的miRNA进行靶向调控基因预测、KEGG功能富集分析,最后,预测出预后相关miRNA的功能。结果：共筛选肺腺癌差异miRNA46个,其中,上调19个、下调27个;通过Cox生存分析筛选到预后相关miRNA有6个,即hsa-mir-21、hsa-mir-142、hsa-mir-200a高表达,hsa-mir-101、hsa-let-7c、hsa-mir-378e低表达,其中hsa-mir-21、hsa-mir-378e与肺腺癌患者不良预后有关,生存期显著缩短（P<0.05,AUC=0.618）。KEGG分析上述预后相关miRNA靶向调控基因与免疫反应通路、miRNA与癌症通路、代谢通路等有关。结论：hsa-mir-21、hsa-mir-378e与肺腺癌预后不良有关,未来经进一步临床验证有可能作为肺腺癌预后相关的分子标记物。     

SARS-CoV-2-induced lung pathology:AHR as a candidate therapeutic target

The aryl hydrocarbon receptor(AHR)is activated by multiple viruses to evade the host immune response,a strategy exploited in pre-clinical models to limit the re...     

Selection of potential natural compounds for poly-ADP-ribose polymerase (PARP) inhibition in glioblastoma therapy by in silico screening methods

Glioblastoma (GBM), the most prevalent brain tumor, is one of the least treatable malignancies due to its propensity for intracranial spread, high proliferative potential, and innate resistance to radiation and chemotherapy. Current GBM therapy is limited due to unfavorable, non-specific therapeutic effects in healthy cells and the difficulty of small molecules to penetrate the blood brain barrier (BBB) and reach the tumor microenvironment. Adding PARP-1 inhibitors inhibit DNA repair enzymes thereby increasing the cytotoxicity of anticancer agents. Hence, we aimed to discover potential naturally occurring PARP-1 inhibitors that can be utilized in the treatment of glioma by using multiple in silico tools like molecular docking, absorption, distribution, metabolism, and excretion (ADME) profile, pharmacophore modeling, and molecular dynamic (MD) simulations. Among 43 phytocompounds we screened, two of them (Ellagic acid and Naringin) were discovered to be bound to the catalytic site of PARP-1 with an affinity more remarkable than commercially available PARP-1 inhibitors (Talazoparib, Niraparib, and Rucaparib) except Olaparib. The molecular interactions were analyzed, and data shows that bound entity attained a conserved domain via hydrogen bond interactions, polar interactions, and π-π stacking. Pharmacophore modeling studies showed electronic and steric features of ligands responsible for supramolecular interaction with PARP-1. ADME properties were studied, to assess drug-likeness, hydrophilic nature, hydrophobicity, brain permeability, and oral bioavailability of the natural PARP-1 inhibitors. The simulation study demonstrated the development of a stable complex between Naringin, Ellagic acid, and PARP-1 protein. Moreover, cell culture studies and animal investigations are essential to determine pharmacokinetics and pharmacodynamics.     

In silico screening of drug databases for TSE inhibitors

Today, thousands of different chemical compounds are used as drugs for a wealth of different indications. Here, we demonstrate the use of a novel conformational drug database for the search of compounds with a positive influence on Transmissible Spongiform Encephalopathies (TSEs) by using two- and three-dimensional structural similarity to compounds with known effect. Both methods are combined to deduce a list of 16 candidate drugs. The proposal of a small number of putative inhibitors out of about 2300 approved essential drugs allows testing by expensive or time-consuming methods with the advantage that all agents are well known and suitable for use in humans.     

Marine-derived sea urchin compounds as potential anti-cancer drug candidate against colorectal cancer: In silico and in vitro studies

Sea urchin-derived compounds are potential candidates for the development of effective drugs for the treatment of cancer diseases. In this study, 19 compounds derived from sea urchin (Diadema savignyi) were used to treat colorectal cancer using the HCT116 cell line. However, molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamic (MD) simulation, and molecular mechanics generalized Born surface area (MM-GBSA) were used to confirm the ligand–protein interaction. Interactions of Importin-11 receptor with sea urchin compounds reveal that four compounds have higher binding affinities (ranging from -8.6 to -7.1 kcal/mol). In vitro testing revealed that the CID 6432458 compound was effective (docking score of −8.6 kcal/mol) against the HCT116 cell line. The cytotoxicity of HCT116 has been documented, with an IC50 value of 6.885 ± 4. MTT assay, apoptosis analysis, and cell cycle assay were utilized to examine cell death in colorectal cancer. In the MTT experiment, 15 µM and 20 µM dosages were associated with 77% cell death; however, flow cytometry analysis using the IC50 value revealed that the selected chemical induced greater apoptosis in the HCT116 cell line (58.5%). The gene expression data revealed that the apoptotic gene BAX is expressed at a higher level than the BCL-2 gene. The IPO11 gene was downregulated during treatment. In the experiment involving the cell cycle, the S phase for the 30  µM dose showed 75.1% apoptosis, which was greater than the other concentrations used alone. These in silico and in vitro analysis will not only provide new information about Importin-11 receptor and insight into colorectal cancer but will also facilitate the development of natural compounds in a significant and worthwhile manner.     

In silico screening of quadruplex-binding ligands

Recent advances in computational processing power and molecular docking algorithms have facilitated the development of computer-aided methods for the rapid and efficient discovery of G-quadruplex-interacting molecules. In this article, we provide an introductory framework for the methodology of in silico screening for the identification of novel DNA G-quadruplex ligands from chemical libraries. We discuss aspects of model construction, database selection and molecular docking techniques, and highlight representative examples from this field. Finally, we offer a perspective on the potential application of in silico techniques for the discovery of RNA G-quadruplex-binding ligands in the future.     

Current therapeutic options for gastric adenocarcinoma

Gastric cancer inflicts significant health issues globally despite its declining incidence. The disease is known to be diagnosed at its advanced stages also corresponding with a poor prognosis for patients. The integral therapeutic choices to cure advanced gastric cancer have progressed swiftly in modern days. The preface of molecularly targeted therapeutic techniques would potentiate the personalized approach depending on patient-specific and tumor-specific features, exasperating the advantages of chemotherapy. Here we have reviewed the modern therapeutics such as immune therapy, chemotherapy, m-RNA based therapeutics, alongside evaluating the influence of age, sex and comorbidities-like factors on the occurrence of gastric cancer. Gastric cancer therapy consolidated target agents comprising inhibitors of programmed death-1(PD-1), human epidermal growth factor receptor 2 (HER2), mRNA, and epidermal growth factor receptor (EPGF). A combination of trastuzumab to platinum-mediated chemotherapy evolved has a typical front-line therapy in advanced gastric cancer. An attempt has been made to epitomize the contemporary-modern research on targeted therapy for advanced gastric cancer.     

Pharmacophore modeling and in silico screening for new KDR kinase inhibitors

In order to elucidate the essential structural features for KDR kinase inhibitors, three-dimensional pharmacophore hypotheses were built on the basis of a set of known KDR kinase inhibitors selected from the literature with CATALYST program. Several methods tools used in validation of pharmacophore hypothsis were presented, and the first hypothesis (Hypo1) was considered to be the best pharmacophore hypothesis. The model (Hypo1) was then employed as 3D search query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit illustrated high binding affinity with KDR kinase measured by the surface plasmon resonance biosensor. Docking studies may help elucidate the mechanisms of KDR kinase receptor-ligand interactions.     

In silico screening for tumour-specific expressed sequences in human genome.

A computer-based differential display tool named HsAnalyst has been developed and successfully used for the comparison of expression patterns in a set of tumours versus a set of normal tissues. A list of EST clusters highly represented in tumours and rarely observed in normal tissues has been developed as a resulting output file of the program. These differentially expressed EST clusters (genes) can be useful for developing new tumour markers and prognostic indicators for a wide set of human malignancies. Tumour-specific protein-coding genes may be considered a manifestation of tumour-specific gene expression.     

In silico studies for the rational discovery of anticonvulsant compounds

Theoretical models to virtual screening and rational design of anticonvulsant compounds based on a topological sub-structural molecular design (TOSS-MODE) approach are developed. These models, developed on the basis of data sets of great structural variability, permit the classification of compounds as active/inactive anticonvulsants and predict the quantitative anticonvulsant potency of such compounds. The classification model is applied to a virtual screening of anticonvulsant compounds by analyzing a data set of molecules reported in the literature. More than 88% of them were well classified by the current model. Active and inactive fragments are identified by using the present approach. Some of the active fragments are identified in anticonvulsant molecules as potential pharmacophores and one of them is analyzed in detail. The three-dimensional (3-D) features of this fragment are investigated in a series of five anticonvulsant compounds. Some structure–anticonvulsant activity relationships are derived on the basis of the 3-D structure of this fragment and some findings reported in the literature that indicate that it is an important pharamacophore are outlined.     

In silico multi-filter screening approaches for developing novel beta-secretase inhibitors

A large database of chemical structures was screened for potential inhibitors of β-secretase was carried out using in silico multi-filter techniques. Substructure screening, computer-aided ligand docking, binding free energy calculations, and partial interaction energy analyses were performed successively to identify chemical compounds which could serve as different scaffolds from known β-secretase inhibitors for future drug design. We showed that our in silico multi-filter screening retrieved all known inhibitors from the compound database investigated, which suggests that the other compounds identified as inhibitors by this computerized screening process are potential β-secretase inhibitors.