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Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections

Frank C. Pickard, Gerhard König, Florentina Tofoleanu, Juyong Lee, Andrew C. Simmonett, Yihan Shao, Jay W. Ponder, Bernard R. Brooks
2016 Journal of Computer-Aided Molecular Design  
Our free energy corrections based on QM protomer and pK a calculations increase the correlation between predicted and experimental distribution coefficients, for all methods used.  ...  We present a protocol for accurately predicting partition coefficients between two immiscible phases, and then apply it to 53 druglike molecules in the SAMPL5 blind prediction challenge.  ...  Acknowledgments This work was supported by the intramural research program of the National Heart, Lung and Blood Institute of the National Institutes of Health and utilized the high-performance computational  ... 
doi:10.1007/s10822-016-9955-7 pmid:27646286 fatcat:2uuv7e3r5zfifnq24ghozmscpq

Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge

Teresa Danielle Bergazin, Nicolas Tielker, Yingying Zhang, Junjun Mao, M. R. Gunner, Karol Francisco, Carlo Ballatore, Stefan M. Kast, David L. Mobley
2021 Journal of Computer-Aided Molecular Design  
The dataset was composed of a series of N-acylsulfonamides and related bioisosteres. 17 research groups participated in the log P challenge, submitting 33 blind submissions total.  ...  Overall, the accuracy of octanol-water log P predictions in the SAMPL7 challenge was lower than octanol-water log P predictions in SAMPL6, likely due to a more diverse dataset.  ...  TDB and DLM gratefully acknowledge support from NIH Grant R01GM124270 supporting the SAMPL Blind challenges.  ... 
doi:10.1007/s10822-021-00397-3 pmid:34169394 pmcid:PMC8224998 fatcat:foz35hwhzndmtmobdjkr7cdg6y

Blind prediction of cyclohexane–water distribution coefficients from the SAMPL5 challenge

Caitlin C. Bannan, Kalistyn H. Burley, Michael Chiu, Michael R. Shirts, Michael K. Gilson, David L. Mobley
2016 Journal of Computer-Aided Molecular Design  
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.  ...  M.K.G. has an equity interest in and is a cofounder and scientific advisor of VeraChem LLC.  ... 
doi:10.1007/s10822-016-9954-8 pmid:27677750 pmcid:PMC5209301 fatcat:jywumgfy65ex3c2kzr7iboxzxu

An efficient protocol for obtaining accurate hydration free energies using quantum chemistry and reweighting from molecular dynamics simulations

Frank C. Pickard, Gerhard König, Andrew C. Simmonett, Yihan Shao, Bernard R. Brooks
2016 Bioorganic & Medicinal Chemistry  
Acknowledgments The authors would like to thank Tim Miller, Richard Venable and John Legato for technical assistance with the parallelization of the QM/MM calculations.  ...  This work was supported by the intramural research program of the National Heart, Lung and Blood Institute of the National Institutes of Health and utilized the high-performance computational capabilities  ...  We have applied this QM method together with the NBB free energy estimator in the recently completed SAMPL5 distribution coefficient challenge, Rustenburg et al. [2016] and strongly endorse it for making  ... 
doi:10.1016/j.bmc.2016.08.031 pmid:27667551 pmcid:PMC5068830 fatcat:aagocajwsnetvebe5zy6jwbhci

Octanol-water partition coefficient measurements for the SAMPL6 Blind Prediction Challenge [article]

Mehtap Işık, Dorothy Levorse, David L Mobley, Timothy Rhodes, John D Chodera
2019 bioRxiv   pre-print
The SAMPL6 Part II Octanol-Water Partition Coefficient Prediction Challenge used a subset of kinase inhibitor fragment-like compounds from the SAMPL6 pKa Prediction Challenge in a blind experimental benchmark  ...  The partition coefficient is a physicochemical property that captures the thermodynamics of relative solvation between aqueous and nonpolar phases, and therefore provides an excellent test for physics-based  ...  Blind Prediction of Distribution in the SAMPL5 522 Challenge with QM Based Protomer and pKa Corrections.  ... 
doi:10.1101/757393 fatcat:odu45gvr55acvg6nvkn6ty4qom