Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
A virtual screening approach to identifying the greenest compound for a task: application to switchable-hydrophilicity solventsElectronic supplementary information (ESI) available: Synthetic methods, details on prediction software, acceptability functions, and comparison of predicted and experimental solubilities. See DOI: 10.1039/c5gc01022e
Erscheinungsjahr
2015-11
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
A virtual or
in silico
screening approach makes it much easier to identify the molecular structure that best combines efficacy for a specific task with safety and minimum environmental or health impacts. In this approach, software is used to generate a larger number of possible molecular structures and then to use QSARs (quantitative structure-activity relationships) to predict properties related to performance, safety, health and environmental impact. The structures are then given scores on criteria (such as flash point or toxicity) and an overall score. The method identifies compounds that have high scores for the 3 performance criteria and 7 health, safety, and environmental criteria. This method allows for larger-scale and faster screening than can be performed using human intellect and a benchtop approach. The success of this approach is demonstrated by its application to the identification of new and possibly greener switchable-hydrophilicity solvents (SHS). Three SHS were identified using this method. This approach to molecular design is entirely modular and can be applied to the design of almost any type of chemical. However, limitations of the method include the fact that it does not take into consideration the health and environmental costs of manufacturing the chemical.
QSAR-based virtual screening makes it easier to identify lead structures that could simultaneously satisfy several performance criteria and several green criteria.
Sprache
Englisch
Identifikatoren
ISSN: 1463-9262
eISSN: 1463-9270
DOI: 10.1039/c5gc01022e
Titel-ID: cdi_rsc_primary_c5gc01022e
Format
–
Weiterführende Literatur
Empfehlungen zum selben Thema automatisch vorgeschlagen von bX