Cargando…
Combining Ensemble Learning with a Fragment-Based Topological Approach To Generate New Molecular Diversity in Drug Discovery: In Silico Design of Hsp90 Inhibitors
[Image: see text] Machine learning methods have revolutionized modern science, providing fast and accurate solutions to multiple problems. However, they are commonly treated as “black boxes”. Therefore, in important scientific fields such as medicinal chemistry and drug discovery, machine learning m...
Autor principal: | Speck-Planche, Alejandro |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2018
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289491/ https://www.ncbi.nlm.nih.gov/pubmed/30555986 http://dx.doi.org/10.1021/acsomega.8b02419 |
Ejemplares similares
-
Development of Computational Approaches with a Fragment-Based Drug Design Strategy: In Silico Hsp90 Inhibitors Discovery
por: León, Roberto, et al.
Publicado: (2021) -
PTML Modeling for Pancreatic Cancer Research: In Silico Design of Simultaneous Multi-Protein and Multi-Cell Inhibitors
por: Kleandrova, Valeria V., et al.
Publicado: (2022) -
QSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites
por: Kleandrova, Valeria V., et al.
Publicado: (2021) -
In Silico Discovery and Optimisation of a Novel Structural Class of Hsp90 C-Terminal Domain Inhibitors
por: Zajec, Živa, et al.
Publicado: (2022) -
The urgent need for pan-antiviral agents: from multitarget discovery to multiscale design
por: V Kleandrova, Valeria, et al.
Publicado: (2020)