Blind prediction of solvation free energies from the SAMPL4 challenge

By David L. Mobley, Karisa L. Wymer, Nathan M. Lim, J. Guthrie. 2014

140 citations recorded by the source corpus.

Abstract Here, we give an overview of the small molecule hydration portion of the SAMPL4 challenge, which focused on predicting hydration free energies for a series of 47 small molecules. These gas-to-water transfer free energies have in the past proven a valuable test of a variety of computational methods and force fields. Here, in contrast to some previous SAMPL challenges, we find a relatively wide range of methods perform quite well on this test set, with RMS errors in the 1.2 kcal/mol range for several of the best performing methods. Top-performers included a quantum mechanical approach with continuum solvent models and functional group corrections, alchemical molecular dynamics simulations with a classical all-atom force field, and a single-conformation Poisson–Boltzmann approach. While 1.2 kcal/mol is still a significant error, experimental hydration free energies covered a range of nearly 20 kcal/mol, so methods typically showed substantial predictive power. Here, a substantial new focus was on evaluation of error estimates, as predicting when a computational prediction is reliable versus unreliable has considerable practical value. We found, however, that in many cases errors are substantially underestimated, and that typically little effort has been invested in estimating likely error. We believe this is an important area for further research.

Subfields: Atomic and Molecular Physics, and Optics, Materials Chemistry, Molecular Biology

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In Atomic and Molecular Physics, and Optics

1. Deng Cai
2. Junying Li
3. Xiaofei He

In Materials Chemistry

1. Deng Cai
2. Junying Li
3. Xiaofei He

In Molecular Biology

1. Deng Cai
2. Junying Li
3. Xiaofei He
4. Huan Liu
5. Jiliang Tang

Citations in the corpus

• Learning Graph-Level Representation for Drug Discovery (2017, methodology): “FreeSolv contains 643 compounds, a subset of which are also used in the SAMPL blind prediction challenge(Mobley et al. 2014).”
• FreeSolv: A database of experimental and calculated hydration free energies, with input files (2014, unknown): “Specifically, we drew on the Dumont set [34], the Nicholls set [39], the 2008 set [32, 33], the Mobley set [31], the Klimovich set [22], the Liu set [35], and the Wymer set [36].”