Extrapolative prediction using physically-based QSAR

Surflex-QMOD integrates chemical structure and activity data to produce physically-realistic models for binding affinity prediction . Here, we apply QMOD to a 3D-QSAR benchmark dataset and show broad applicability to a diverse set of targets. Testing new ligands within the QMOD model employs automat...

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Detalles Bibliográficos
Autores principales: Cleves, Ann E., Jain, Ajay N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4796382/
https://www.ncbi.nlm.nih.gov/pubmed/26860112
http://dx.doi.org/10.1007/s10822-016-9896-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4796382/
https://www.ncbi.nlm.nih.gov/pubmed/26860112
http://dx.doi.org/10.1007/s10822-016-9896-1

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