Platform for ligand-based virtual screening integration

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10368583" target="_blank" >RIV/00216208:11320/17:10368583 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/BIBM.2017.8218015" target="_blank" >https://doi.org/10.1109/BIBM.2017.8218015</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/BIBM.2017.8218015" target="_blank" >10.1109/BIBM.2017.8218015</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Platform for ligand-based virtual screening integration

Popis výsledku v původním jazyce

Ligand-based Virtual screening became a standard in-silico complement to the wet laboratory screening in small molecules discovery. It utilizes prior knowledge about molecules to rank a set of candidate molecules with yet unknown activity. Virtual screening software is often implemented as a specialized screening tool or as a part of a drug-discovery suite where ligand-based screening is one of the available tools. There exist many approaches to virtual screening, but although there exist several free-to-use screening tools, these tools usually provide only single approach to screening or do not provide user with aggregated analyses of multiple (preferably state-of-the-art) screening approaches. Such a functionality would be useful since different screening approaches yield different ranking of the candidate molecules. To the best of our knowledge there is no freely available, easy-to-use, tool that would allow to apply multiple screening approaches to a dataset and subsequently facilitate integration and interpretation of the results. Here, we present the first version of such a tool called ViSeT, available at https://github.com/skodapetr/viset under the MIT licence. ViSeT is a web-based, extensible, ligand-based virtual screening tool supporting multiple screening approaches and subsequent analysis of the results.

Název v anglickém jazyce

Platform for ligand-based virtual screening integration

Popis výsledku anglicky

Ligand-based Virtual screening became a standard in-silico complement to the wet laboratory screening in small molecules discovery. It utilizes prior knowledge about molecules to rank a set of candidate molecules with yet unknown activity. Virtual screening software is often implemented as a specialized screening tool or as a part of a drug-discovery suite where ligand-based screening is one of the available tools. There exist many approaches to virtual screening, but although there exist several free-to-use screening tools, these tools usually provide only single approach to screening or do not provide user with aggregated analyses of multiple (preferably state-of-the-art) screening approaches. Such a functionality would be useful since different screening approaches yield different ranking of the candidate molecules. To the best of our knowledge there is no freely available, easy-to-use, tool that would allow to apply multiple screening approaches to a dataset and subsequently facilitate integration and interpretation of the results. Here, we present the first version of such a tool called ViSeT, available at https://github.com/skodapetr/viset under the MIT licence. ViSeT is a web-based, extensible, ligand-based virtual screening tool supporting multiple screening approaches and subsequent analysis of the results.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2017 IEEE International Conference on Bioinformatics and Biomedicine

ISBN

978-1-5090-3050-7

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

4

Strana od-do

2256-2259

Název nakladatele

IEEE (The Institute of Electrical and Electronics Engineers)

Místo vydání

Neuveden

Místo konání akce

Kansas City, MO, USA

Datum konání akce

13. 11. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—