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Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose
We introduce the QuanSA method for inducing physically meaningful field-based models of ligand binding pockets based on structure-activity data alone. The method is closely related to the QMOD approach, substituting a learned scoring field for a pocket constructed of molecular fragments. The problem...
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| Publicado no: | J Comput Aided Mol Des |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer International Publishing
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6096883/ https://ncbi.nlm.nih.gov/pubmed/29934750 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10822-018-0126-x |
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