Literature DB >> 22962344

ChemBioServer: a web-based pipeline for filtering, clustering and visualization of chemical compounds used in drug discovery.

Emmanouil Athanasiadis1, Zoe Cournia, George Spyrou.   

Abstract

SUMMARY: ChemBioServer is a publicly available web application for effectively mining and filtering chemical compounds used in drug discovery. It provides researchers with the ability to (i) browse and visualize compounds along with their properties, (ii) filter chemical compounds for a variety of properties such as steric clashes and toxicity, (iii) apply perfect match substructure search, (iv) cluster compounds according to their physicochemical properties providing representative compounds for each cluster, (v) build custom compound mining pipelines and (vi) quantify through property graphs the top ranking compounds in drug discovery procedures. ChemBioServer allows for pre-processing of compounds prior to an in silico screen, as well as for post-processing of top-ranked molecules resulting from a docking exercise with the aim to increase the efficiency and the quality of compound selection that will pass to the experimental test phase. AVAILABILITY: The ChemBioServer web application is available at: http://bioserver-3.bioacademy.gr/Bioserver/ChemBioServer/. CONTACT: gspyrou@bioacademy.gr

Entities:  

Mesh:

Year:  2012        PMID: 22962344     DOI: 10.1093/bioinformatics/bts551

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

1.  Do Zebrafish Obey Lipinski Rules?

Authors:  Keith Long; Stephen J Kostman; Christian Fernandez; James C Burnett; Donna M Huryn
Journal:  ACS Med Chem Lett       Date:  2019-04-24       Impact factor: 4.345

Review 2.  From gene networks to drugs: systems pharmacology approaches for AUD.

Authors:  Laura B Ferguson; R Adron Harris; Roy Dayne Mayfield
Journal:  Psychopharmacology (Berl)       Date:  2018-03-01       Impact factor: 4.530

3.  Curcumin-Synthetic Analogs Library Screening by Docking and Quantitative Structure-Activity Relationship Studies for AXL Tyrosine Kinase Inhibition in Cancers.

Authors:  Fatima Ghrifi; Loubna Allam; Lakhlili Wiame; Azeddine Ibrahimi
Journal:  J Comput Biol       Date:  2019-06-24       Impact factor: 1.479

4.  Identification of CB1 Ligands among Drugs, Phytochemicals and Natural-Like Compounds: Virtual Screening and In Vitro Verification.

Authors:  Adam Stasiulewicz; Anna Lesniak; Piotr Setny; Magdalena Bujalska-Zadrożny; Joanna I Sulkowska
Journal:  ACS Chem Neurosci       Date:  2022-10-05       Impact factor: 5.780

Review 5.  Structure-based virtual screening for drug discovery: principles, applications and recent advances.

Authors:  Evanthia Lionta; George Spyrou; Demetrios K Vassilatis; Zoe Cournia
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

6.  Discovering gene re-ranking efficiency and conserved gene-gene relationships derived from gene co-expression network analysis on breast cancer data.

Authors:  Marilena M Bourdakou; Emmanouil I Athanasiadis; George M Spyrou
Journal:  Sci Rep       Date:  2016-02-19       Impact factor: 4.379

7.  Structure-activity relationships study of mTOR kinase inhibition using QSAR and structure-based drug design approaches.

Authors:  Wiame Lakhlili; Abdelaziz Yasri; Azeddine Ibrahimi
Journal:  Onco Targets Ther       Date:  2016-12-02       Impact factor: 4.147

8.  ChemBioServer 2.0: an advanced web server for filtering, clustering and networking of chemical compounds facilitating both drug discovery and repurposing.

Authors:  Evangelos Karatzas; Juan Eiros Zamora; Emmanouil Athanasiadis; Dimitris Dellis; Zoe Cournia; George M Spyrou
Journal:  Bioinformatics       Date:  2020-04-15       Impact factor: 6.937

9.  Structure based virtual screening identifies small molecule effectors for the sialoglycan binding protein Hsa.

Authors:  Rupesh Agarwal; Barbara A Bensing; Dehui Mi; Paige N Vinson; Jerome Baudry; Tina M Iverson; Jeremy C Smith
Journal:  Biochem J       Date:  2020-10-16       Impact factor: 3.766

10.  Drug repurposing in idiopathic pulmonary fibrosis filtered by a bioinformatics-derived composite score.

Authors:  E Karatzas; M M Bourdakou; G Kolios; G M Spyrou
Journal:  Sci Rep       Date:  2017-10-03       Impact factor: 4.379

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