ArticleJournal of computer-aided molecular design2016
Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge.
Article in Journal of computer-aided molecular design, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
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- Development and test of highly accurate endpoint free energy methods. 3: partition coefficient prediction using a Poisson-Boltzmann method combined with a solvent accessible surface area model for SAMPL challenges.Physical chemistry chemical physics : PCCP · 2023Article
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- An overview of the SAMPL8 host-guest binding challenge.Journal of computer-aided molecular design · 2022Article
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- Implementation and Optimization of the Embedded Cluster Reference Interaction Site Model with Atomic Charges.The journal of physical chemistry. A · 2022Article
- CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding.Nature reviews. Chemistry · 2022Article
- SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction.Journal of computer-aided molecular design · 2022Article
- Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks [Article v0.1].Living journal of computational molecular science · 2022Article
- Automated high throughput pKJournal of computer-aided molecular design · 2021Article
- Ensembles Are Required to Handle Aleatoric and Parametric Uncertainty in Molecular Dynamics Simulation.Journal of chemical theory and computation · 2021Article
- Alkane/Water Partition Coefficient Calculation Based on the Modified AM1 Method and Internal Hydrogen Bonding Sampling Using COSMO-RS.Journal of chemical information and modeling · 2021Article
- Energy-entropy prediction of octanol-water logP of SAMPL7 N-acyl sulfonamide bioisosters.Journal of computer-aided molecular design · 2021Article
- SAMPL7 blind challenge: quantum-mechanical prediction of partition coefficients and acid dissociation constants for small drug-like molecules.Journal of computer-aided molecular design · 2021Article
- Evaluation of log P, pKJournal of computer-aided molecular design · 2021Article
- Evaluation of nine condensed-phase force fields of the GROMOS, CHARMM, OPLS, AMBER, and OpenFF families against experimental cross-solvation free energies.Physical chemistry chemical physics : PCCP · 2021Article
- Uncertainty quantification in classical molecular dynamics.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
4 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
In the recent SAMPL5 challenge, participants submitted predictions for cyclohexane/water distribution coefficients for a set of 53 small molecules. Distribution coefficients (log D) replace the hydration free energies that were a central part of the past five SAMPL challenges. A wide variety of computational methods were represented by the 76 submissions from 18 participating groups. Here, we analyze submissions by a variety of error metrics and provide details for a number of reference calculations we performed. As in the SAMPL4 challenge, we assessed the ability of participants to evaluate not just their statistical uncertainty, but their model uncertainty-how well they can predict the magnitude of their model or force field error for specific predictions. Unfortunately, this remains an area where prediction and analysis need improvement. In SAMPL4 the top performing submissions achieved a root-mean-squared error (RMSE) around 1.5 kcal/mol. If we anticipate accuracy in log D predictions to be similar to the hydration free energy predictions in SAMPL4, the expected error here would be around 1.54 log units. Only a few submissions had an RMSE below 2.5 log units in their predicted log D values. However, distribution coefficients introduced complexities not present in past SAMPL challenges, including tautomer enumeration, that are likely to be important in predicting biomolecular properties of interest to drug discovery, therefore some decrease in accuracy would be expected. Overall, the SAMPL5 distribution coefficient challenge provided great insight into the importance of modeling a variety of physical effects. We believe these types of measurements will be a promising source of data for future blind challenges, especially in view of the relatively straightforward nature of the experiments and the level of insight provided.
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