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  1. Article ; Online: An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through

    Modanwal, Shristi / Mishra, Ashutosh / Mishra, Nidhi

    Journal of biomolecular structure & dynamics

    2023  , Page(s) 1–21

    Abstract: Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are ... ...

    Abstract Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.
    Language English
    Publishing date 2023-11-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 49157-3
    ISSN 1538-0254 ; 0739-1102
    ISSN (online) 1538-0254
    ISSN 0739-1102
    DOI 10.1080/07391102.2023.2283163
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2093: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: Structure-guided Design and Optimization of small Molecules as Pancreatic Lipase Inhibitors using Pharmacophore, 3D-QSAR, Molecular Docking, and Molecular Dynamics Simulation Studies.

    Modanwal, Shristi / Mulpuru, Viswajit / Mishra, Nidhi

    Current computer-aided drug design

    2023  Volume 19, Issue 4, Page(s) 258–277

    Abstract: Background: Obesity has now become a global issue due to the increase in the population of obese people. It also substantially impacts the individual's social, financial, and psychological well-being, which may contribute to depression. Being overweight ...

    Abstract Background: Obesity has now become a global issue due to the increase in the population of obese people. It also substantially impacts the individual's social, financial, and psychological well-being, which may contribute to depression. Being overweight induces many metabolic and chronic disorders, urging many researchers to focus on developing the drug for obesity treatment. Pancreatic lipase inhibitors and natural product/compound-derived pancreatic lipase inhibitors have recently received much attention because of their structural variety and low toxicity.
    Objective: This study aimed to build pharmacophores and QSAR for analyzing the necessary structure of pancreatic lipase inhibitors and designing new molecules with the best activity.
    Methods: Ligand-based pharmacophore modeling and Atom-Based 3D-QSAR were carried out using the PHASE module of Schrodinger to determine the critical structural properties necessary for pancreatic lipase (PL) inhibitory activity. A total of 157 phytoconstituents and a standard drug, orlistat, were selected for the present study. Considering the important features for pancreatic lipase inhibition, 15 new molecules were designed and subjected to molecular docking studies and molecular dynamics simulations. The activity of designed molecules was predicted using the Atom- Based QSAR tool of the PHASE module.
    Results: The top docked score molecule is structure-7 with a docking score of -6.094 Kcal/mol, whereas the docking score of orlistat and tristin is -3.80Kcal/mol and -5.63Kcal/mol, respectively.
    Conclusion: The designed molecules have a high docking score and good stability, are in the desirable ADME range and are derived from natural products, so they might be used as lead molecules for anti-obesity drug development.
    MeSH term(s) Humans ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Quantitative Structure-Activity Relationship ; Pharmacophore ; Orlistat ; Lipase
    Chemical Substances Orlistat (95M8R751W8) ; Lipase (EC 3.1.1.3)
    Language English
    Publishing date 2023-01-04
    Publishing country United Arab Emirates
    Document type Journal Article
    ISSN 1875-6697
    ISSN (online) 1875-6697
    DOI 10.2174/1573409919666230103144045
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Identification of common genes in obesity and cancer through network interaction and targeting those genes by virtual screening approach.

    Modanwal, Shristi / Mishra, Nidhi

    Journal of biomolecular structure & dynamics

    2021  Volume 41, Issue 3, Page(s) 1109–1127

    Abstract: Obesity may have an effect on cancer outcomes, resulting in global inequalities in cancer survival and death. Microarray data analysis was done to identify differentially expressed genes (DEGs) in obese and cancer patients. Total 1977 differentially ... ...

    Abstract Obesity may have an effect on cancer outcomes, resulting in global inequalities in cancer survival and death. Microarray data analysis was done to identify differentially expressed genes (DEGs) in obese and cancer patients. Total 1977 differentially expressed genes among obesity and gastric cancer, breast cancer, pancreatic cancer, and colorectal cancer were used to build a gene interaction network, which was then analyzed by using Cytoscape software. It has been identified that JUN, CXCL12, and LEP genes show a higher degree and stress, and play an important role in obesity and cancer progression. Further, CXCL12 and LEP were taken for virtual screening study with coumarin and its derivatives to develop a drug against obesity and cancer. The interactions of CXCL12 and LEP with coumarins were studied by molecular docking and it shows good interaction as well as docking score as compared to the standard one. The ADME properties were predicted to check the drug-likeness activity of coumarins and the most of the drug-likeness activities are in admire range. The Binding free energy of the docked complex was calculated by performing MM-GBSA. The molecular docking, ADME properties prediction, and MM-GBSA was performed on Maestro 12.6. The top docked score compounds were further subjected to molecular dynamic simulation to check the stability by using GROMACS. The MM-PBSA study was performed to calculate the binding energy components as well as the energy contributions of specific amino acids. The resultant compounds could be a potent anti-obesity and anti-cancer drug.Communicated by Ramaswamy H. Sarma.
    MeSH term(s) Humans ; Female ; Early Detection of Cancer ; Molecular Docking Simulation ; Breast Neoplasms ; Pancreatic Neoplasms ; Coumarins ; Molecular Dynamics Simulation
    Chemical Substances Coumarins
    Language English
    Publishing date 2021-12-28
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 49157-3
    ISSN 1538-0254 ; 0739-1102
    ISSN (online) 1538-0254
    ISSN 0739-1102
    DOI 10.1080/07391102.2021.2020169
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2093: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
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  4. Article ; Online: Development of QSAR model using machine learning and molecular docking study of polyphenol derivatives against obesity as pancreatic lipase inhibitor.

    Modanwal, Shristi / Maurya, Akhilesh Kumar / Mishra, Saurav Kumar / Mishra, Nidhi

    Journal of biomolecular structure & dynamics

    2022  Volume 41, Issue 14, Page(s) 6569–6580

    Abstract: In developed countries and developing countries, obesity/overweight is considered a major problem, in fact, it is now recognized as a major metabolic disorder. Additionally, obesity is connected with other metabolic diseases, including cardiovascular ... ...

    Abstract In developed countries and developing countries, obesity/overweight is considered a major problem, in fact, it is now recognized as a major metabolic disorder. Additionally, obesity is connected with other metabolic diseases, including cardiovascular disorders, type 2 diabetes, some types of cancer, etc. Therefore, the development of novel drugs/medications for obesity is essential. The best target for treating obesity is Pancreatic Lipase (PL), it breaks 50-70% triglycerides into monoglycerol and free fatty acids.The major aim of this in silico study is to generate a QSAR model by using Multiple Linear Regression (MLR) and to inhibit pancreatic lipase by polyphenol derivatives mainly flavonoids, plant secondary metabolites shows good inhibitory activity against PL, maybe with less unpleasant side effects.In this in silico study, a potent inhibitor was found through calculating drug likness, QSAR (Quantitative structure-activity relationship) and molecular docking. The docking was performed in Maestro 12.0 and the ADME (absorption, distribution, metabolism, and excretion) properties (drug-likeness) of compounds/ligands were predicted by the Qikprop module of Maestro 12.0. The QSAR model was developed to show the relationship between the chemical/structural properties and the compound's biological activity. We have found the best interaction between pancreatic lipase and flavonoids. The best docked compound is Epigallocatechin 3,5,-di-O-gallate with docking score -10.935 kcal/mol .All compounds also show drug-likeness activity.The developed model has satisfied all internal and external validation criteria and has square correlation coefficient (r2) 0.8649, which shows its predictive ability and has good acceptability, predictive ability, and statistical robustness.Communicated by Ramaswamy H. Sarma.
    Language English
    Publishing date 2022-08-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 49157-3
    ISSN 1538-0254 ; 0739-1102
    ISSN (online) 1538-0254
    ISSN 0739-1102
    DOI 10.1080/07391102.2022.2109753
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 2093: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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