ArticleJournal of computer-aided molecular design2016
Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK
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 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Evaluation of log P, pKJournal of computer-aided molecular design · 2021Article
- Overview of the SAMPL6 pKJournal of computer-aided molecular design · 2021Article
- On the faithfulness of molecular mechanics representations of proteins towards quantum-mechanical energy surfaces.Interface focus · 2020Article
- Quantum chemical predictions of water-octanol partition coefficients applied to the SAMPL6 logP blind challenge.Journal of computer-aided molecular design · 2020Article
- Multi-phase Boltzmann weighting: accounting for local inhomogeneity in molecular simulations of water-octanol partition coefficients in the SAMPL6 challenge.Journal of computer-aided molecular design · 2020Article
- Standard state free energies, not pKJournal of computer-aided molecular design · 2020Article
- Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.Journal of computer-aided molecular design · 2020Article
- Predicting partition coefficients of drug-like molecules in the SAMPL6 challenge with Drude polarizable force fields.Journal of computer-aided molecular design · 2020Article
- Use of Interaction Energies in QM/MM Free Energy Simulations.Journal of chemical theory and computation · 2019Article
- A Comparison of QM/MM Simulations with and without the Drude Oscillator Model Based on Hydration Free Energies of Simple Solutes.Molecules (Basel, Switzerland) · 2018Article
- An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge.Journal of computer-aided molecular design · 2018Article
- SAMPL6 challenge results fromJournal of computer-aided molecular design · 2018Article
- pKJournal of computer-aided molecular design · 2018Article
- On the convergence of multi-scale free energy simulations.Molecular simulation · 2018Article
- Origin of pKThe journal of physical chemistry. B · 2017Article
- Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge.Journal of computer-aided molecular design · 2016Article
- Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge.Journal of computer-aided molecular design · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The computation of distribution coefficients between polar and apolar phases requires both an accurate characterization of transfer free energies between phases and proper accounting of ionization and protomerization. We present a protocol for accurately predicting partition coefficients between two immiscible phases, and then apply it to 53 drug-like molecules in the SAMPL5 blind prediction challenge. Our results combine implicit solvent QM calculations with classical MD simulations using the non-Boltzmann Bennett free energy estimator. The OLYP/DZP/SMD method yields predictions that have a small deviation from experiment (RMSD = 2.3 [Formula: see text] D units), relative to other participants in the challenge. Our free energy corrections based on QM protomer and [Formula: see text] calculations increase the correlation between predicted and experimental distribution coefficients, for all methods used. Unfortunately, these corrections are overly hydrophilic, and fail to account for additional effects such as aggregation, water dragging and the presence of polar impurities in the apolar phase. We show that, although expensive, QM-NBB free energy calculations offer an accurate and robust method that is superior to standard MM and QM techniques alone.
Indexed as
Identifiers
27646286What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.