iSEE: Interface structure, evolution, and energy‐based machine learning predictor of binding affinity changes upon mutations

Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning‐based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using a small number of sensitive predictive features i...

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Detalles Bibliográficos
Autores principales: Geng, Cunliang, Vangone, Anna, Folkers, Gert E., Xue, Li C., Bonvin, Alexandre M. J. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2018
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587874/
https://www.ncbi.nlm.nih.gov/pubmed/30417935
http://dx.doi.org/10.1002/prot.25630

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587874/
https://www.ncbi.nlm.nih.gov/pubmed/30417935
http://dx.doi.org/10.1002/prot.25630

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