SAMPL6 logP challenge: machine learning and quantum mechanical approaches
Author:
Publisher
Springer Science and Business Media LLC
Subject
Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery
Link
http://link.springer.com/content/pdf/10.1007/s10822-020-00287-0.pdf
Reference57 articles.
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2. Nicholls A, Wlodek S, Grant JA (2009) The SAMP1 solvation challenge: further lessons regarding the pitfalls of parametrization†. J Phys Chem B 113:4521–4532. https://doi.org/10.1021/jp806855q
3. Geballe MT, Skillman a G, Nicholls A et al (2010) The SAMPL2 blind prediction challenge: introduction and overview. J Comput Aided Mol Des 24:259–279. https://doi.org/10.1007/s10822-010-9350-8
4. Geballe MT, Guthrie JP (2012) The SAMPL3 blind prediction challenge: transfer energy overview. J Comput Aided Mol Des 26:489–496. https://doi.org/10.1007/s10822-012-9568-8
5. Muddana HS, Fenley AT, Mobley DL, Gilson MK (2014) The SAMPL4 host–guest blind prediction challenge: an overview. J Comput Aided Mol Des 28:305–317. https://doi.org/10.1007/s10822-014-9735-1
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