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Development of Predictive Models for Identifying Potential S100A9 Inhibitors Based on Machine Learning Methods

S100A9 is a potential therapeutic target for various disease including prostate cancer, colorectal cancer, and Alzheimer's disease. However, the sparsity of atomic level data, such as protein-protein interaction of S100A9 with RAGE, TLR4/MD2, or CD147 (EMMPRIN) hinders the rational drug design...

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Detalles Bibliográficos
Autores principales:	Lee, Jihyeun, Kumar, Surendra, Lee, Sang-Yoon, Park, Sung Jean, Kim, Mi-hyun
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2019
Materias:	Chemistry
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886474/ https://www.ncbi.nlm.nih.gov/pubmed/31824919 http://dx.doi.org/10.3389/fchem.2019.00779

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