Deep Boosted Molecular Dynamics (DBMD): Accelerating molecular simulations with Gaussian boost potentials generated using probabilistic Bayesian deep neural network

We have developed a new Deep Boosted Molecular Dynamics (DBMD) method. Probabilistic Bayesian neural network models were implemented to construct boost potentials that exhibit Gaussian distribution with minimized anharmonicity, thereby allowing for accurate energetic reweighting and enhanced samplin...

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Detalles Bibliográficos
Autores principales: Do, Hung N., Miao, Yinglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10081221/
https://www.ncbi.nlm.nih.gov/pubmed/37034713
http://dx.doi.org/10.1101/2023.03.25.534210

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10081221/
https://www.ncbi.nlm.nih.gov/pubmed/37034713
http://dx.doi.org/10.1101/2023.03.25.534210

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