List of all SAMPL references

A working list of all SAMPL references is provided below. If you are aware of a paper relating to SAMPL which is not listed here, please e-mail details to David Mobley for addition.

Typically all original SAMPL papers cite “SAMPLN” in their titles, where N is a number, e.g. “SAMPL7”, making these easy to discover via Google Scholar, Web of Science or similar search engines. However, later papers using the SAMPL datasets do not necessarily follow this convention.

  1. Relative Binding Free Energy Calculations for Ligands with Diverse Scaffolds with the Alchemical Transfer Method
    Solmaz Azimi, Sheenam Khuttan, Joe Z. Wu, Rajat K. Pal, Emilio Gallicchio
    Journal of Chemical Information and Modeling (2022-01-06) https://doi.org/gpjnv9
    DOI: 10.1021/acs.jcim.1c01129 · PMID: 34990555

  2. Binding free energies for the SAMPL8 CB8 “Drugs of Abuse” challenge from umbrella sampling combined with Hamiltonian replica exchange
    Daniel Markthaler, Hamzeh Kraus, Niels Hansen
    Journal of Computer-Aided Molecular Design (2022-01) https://doi.org/gpjnwb
    DOI: 10.1007/s10822-021-00439-w · PMID: 34978001 · PMCID: PMC8831271

  3. Thermodynamics of pillararene·guest complexation: blinded dataset for the SAMPL9 challenge
    Chun-Lin Deng, Ming Cheng, Peter Y. Zavalij, Lyle Isaacs
    New Journal of Chemistry (2022) https://doi.org/gpjnwc
    DOI: 10.1039/d1nj05209h · PMCID: PMC8896905

  4. Free energy methods in drug discovery: current state and future directions
    Kira A. Armacost, David C. Thompson (editors)
    American Chemical Society (2021)
    ISBN: 9780841298064

  5. Automated high throughput pKa and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge
    Matthew N. Bahr, Aakankschit Nandkeolyar, John K. Kenna, Neysa Nevins, Luigi Da Vià, Mehtap Işık, John D. Chodera, David L. Mobley
    Journal of Computer-Aided Molecular Design (2021-10-29) https://doi.org/gpjnwd
    DOI: 10.1007/s10822-021-00427-0 · PMID: 34714468

  6. Molecular Environment-Specific Atomic Charges Improve Binding Affinity Predictions of SAMPL5 Host–Guest Systems
    Duván González, Luis Macaya, Esteban Vöhringer-Martinez
    Journal of Chemical Information and Modeling (2021-08-31) https://doi.org/gpjvrw
    DOI: 10.1021/acs.jcim.1c00655 · PMID: 34464129

  7. Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge
    Eelke B. Lenselink, Pieter F. W. Stouten
    Journal of Computer-Aided Molecular Design (2021-07-17) https://doi.org/gpjvrx
    DOI: 10.1007/s10822-021-00405-6 · PMID: 34273053 · PMCID: PMC8367913

  8. Energy–entropy method using multiscale cell correlation to calculate binding free energies in the SAMPL8 host–guest challenge
    Hafiz Saqib Ali, Arghya Chakravorty, Jas Kalayan, Samuel P. de Visser, Richard H. Henchman
    Journal of Computer-Aided Molecular Design (2021-07-15) https://doi.org/gpjnwf
    DOI: 10.1007/s10822-021-00406-5 · PMID: 34264476 · PMCID: PMC8367938

  9. Precise force-field-based calculations of octanol-water partition coefficients for the SAMPL7 molecules
    Shujie Fan, Hristo Nedev, Ranjit Vijayan, Bogdan I. Iorga, Oliver Beckstein
    Journal of Computer-Aided Molecular Design (2021-07) https://doi.org/gpkddh
    DOI: 10.1007/s10822-021-00407-4 · PMID: 34232435 · PMCID: PMC8397498

  10. Predicting partition coefficients for the SAMPL7 physical property challenge using the ClassicalGSG method
    Nazanin Donyapour, Alex Dickson
    Journal of Computer-Aided Molecular Design (2021-06-28) https://doi.org/gndrh6
    DOI: 10.1007/s10822-021-00400-x · PMID: 34181200 · PMCID: PMC8295205

  11. 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
    Journal of Computer-Aided Molecular Design (2021-06-24) https://doi.org/gkvkqs
    DOI: 10.1007/s10822-021-00397-3 · PMID: 34169394 · PMCID: PMC8224998

  12. Alchemical Transfer Approach to Absolute Binding Free Energy Estimation
    Joe Z. Wu, Solmaz Azimi, Sheenam Khuttan, Nanjie Deng, Emilio Gallicchio
    Journal of Chemical Theory and Computation (2021-05-13) https://doi.org/gj2n9n
    DOI: 10.1021/acs.jctc.1c00266 · PMID: 33983730

  13. Binding free energy predictions in host-guest systems using Autodock4. A retrospective analysis on SAMPL6, SAMPL7 and SAMPL8 challenges
    Lorenzo Casbarra, Piero Procacci
    Journal of Computer-Aided Molecular Design (2021-05-24) https://doi.org/gpjnwg
    DOI: 10.1007/s10822-021-00388-4 · PMID: 34027592 · PMCID: PMC8141411

  14. A replica exchange umbrella sampling (REUS) approach to predict host–guest binding free energies in SAMPL8 challenge
    Mahdi Ghorbani, Phillip S. Hudson, Michael R. Jones, Félix Aviat, Rubén Meana-Pañeda, Jeffery B. Klauda, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2021-05) https://doi.org/gpjnwh
    DOI: 10.1007/s10822-021-00385-7 · PMID: 33939083 · PMCID: PMC8131287

  15. DeepBAR: A Fast and Exact Method for Binding Free Energy Computation
    Xinqiang Ding, Bin Zhang
    The Journal of Physical Chemistry Letters (2021-03-15) https://doi.org/gnzjd7
    DOI: 10.1021/acs.jpclett.1c00189 · PMID: 33719449 · PMCID: PMC8030779

  16. Experimental characterization of the association of β-cyclodextrin and eight novel cyclodextrin derivatives with two guest compounds
    K. Kellett, D. R. Slochower, M. Schauperl, B. M. Duggan, M. K. Gilson
    Journal of Computer-Aided Molecular Design (2020-10-10) https://doi.org/gpjnwj
    DOI: 10.1007/s10822-020-00350-w · PMID: 33037548 · PMCID: PMC7867601

  17. Accurate Receptor-Ligand Binding Free Energies from Fast QM Conformational Chemical Space Sampling
    Esra Boz, Matthias Stein
    International Journal of Molecular Sciences (2021-03-17) https://doi.org/gpjvrz
    DOI: 10.3390/ijms22063078 · PMID: 33802920 · PMCID: PMC8002627

  18. Quantum–mechanical property prediction of solvated drug molecules: what have we learned from a decade of SAMPL blind prediction challenges?
    Nicolas Tielker, Lukas Eberlein, Gerhard Hessler, K. Friedemann Schmidt, Stefan Güssregen, Stefan M. Kast
    Journal of Computer-Aided Molecular Design (2020-10-20) https://doi.org/gmjgs2
    DOI: 10.1007/s10822-020-00347-5 · PMID: 33079358 · PMCID: PMC8018924

  19. Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions
    Mehtap Işık, Ariën S. Rustenburg, Andrea Rizzi, M. R. Gunner, David L. Mobley, John D. Chodera
    Journal of Computer-Aided Molecular Design (2021-01-04) https://doi.org/gpjnwk
    DOI: 10.1007/s10822-020-00362-6 · PMID: 33394238 · PMCID: PMC7904668

  20. AMOEBA binding free energies for the SAMPL7 TrimerTrip host–guest challenge
    Yuanjun Shi, Marie L. Laury, Zhi Wang, Jay W. Ponder
    Journal of Computer-Aided Molecular Design (2020-11-03) https://doi.org/gjv786
    DOI: 10.1007/s10822-020-00358-2 · PMID: 33140208 · PMCID: PMC7867568

  21. Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software
    Yuriy Khalak, Gary Tresadern, Bert L. de Groot, Vytautas Gapsys
    Journal of Computer-Aided Molecular Design (2020-11-24) https://doi.org/gjv782
    DOI: 10.1007/s10822-020-00359-1 · PMID: 33230742 · PMCID: PMC7862541

  22. SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations
    Martin Amezcua, Léa El Khoury, David L. Mobley
    Journal of Computer-Aided Molecular Design (2021-01) https://doi.org/gpjnwm
    DOI: 10.1007/s10822-020-00363-5 · PMID: 33392951 · PMCID: PMC8121194

  23. Hybrid Alchemical Free Energy/Machine-Learning Methodology for the Computation of Hydration Free Energies
    Jenke Scheen, Wilson Wu, Antonia S. J. S. Mey, Paolo Tosco, Mark Mackey, Julien Michel
    Journal of Chemical Information and Modeling (2020-07-08) https://doi.org/gmjgfd
    DOI: 10.1021/acs.jcim.0c00600 · PMID: 32639733

  24. On Calculating Free Energy Differences Using Ensembles of Transition Paths
    Robert Hall, Tom Dixon, Alex Dickson
    Frontiers in Molecular Biosciences (2020-06-05) https://doi.org/gh6mkn
    DOI: 10.3389/fmolb.2020.00106 · PMID: 32582764 · PMCID: PMC7291376

  25. The SAMPL7 Host-Guest Challenge Virtual Workshop
    David L. Mobley, Martin Amezcua, Jay Ponder, Yuriy Khalak, Yigitkan Eken, Nuno Almeida, Lyle Isaacs, Bruce Gibb, Katy Kellett, Dylan Serrilon
    Zenodo (2020-02-19) https://zenodo.org/record/3674155

  26. The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations
    Andrea Rizzi, Travis Jensen, David R. Slochower, Matteo Aldeghi, Vytautas Gapsys, Dimitris Ntekoumes, Stefano Bosisio, Michail Papadourakis, Niel M. Henriksen, Bert L. de Groot, … John D. Chodera
    Journal of Computer-Aided Molecular Design (2020-01-27) https://doi.org/gjs8dn
    DOI: 10.1007/s10822-020-00290-5 · PMID: 31984465 · PMCID: PMC7282318

  27. Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states
    M. R. Gunner, Taichi Murakami, Ariën S. Rustenburg, Mehtap Işık, John D. Chodera
    Journal of Computer-Aided Molecular Design (2020-02-12) https://doi.org/gn265b
    DOI: 10.1007/s10822-020-00280-7 · PMID: 32052350 · PMCID: PMC7556740

  28. Quantum chemical predictions of water–octanol partition coefficients applied to the SAMPL6 logP blind challenge
    Michael R. Jones, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2020-01-30) https://doi.org/gpjnwn
    DOI: 10.1007/s10822-020-00286-1 · PMID: 32002778 · PMCID: PMC8690632

  29. A deep learning approach for the blind logP prediction in SAMPL6 challenge
    Samarjeet Prasad, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2020-01-30) https://doi.org/gpjnwp
    DOI: 10.1007/s10822-020-00292-3 · PMID: 32002779 · PMCID: PMC8689685

  30. Prediction of octanol-water partition coefficients for the SAMPL6- log P molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields
    Shujie Fan, Bogdan I. Iorga, Oliver Beckstein
    Journal of Computer-Aided Molecular Design (2020-01-20) https://doi.org/gpjnwq
    DOI: 10.1007/s10822-019-00267-z · PMID: 31960254 · PMCID: PMC7667952

  31. Assessing the accuracy of octanol–water partition coefficient predictions in the SAMPL6 Part II log P Challenge
    Mehtap Işık, Teresa Danielle Bergazin, Thomas Fox, Andrea Rizzi, John D. Chodera, David L. Mobley
    Journal of Computer-Aided Molecular Design (2020-02-27) https://doi.org/gpjnwr
    DOI: 10.1007/s10822-020-00295-0 · PMID: 32107702 · PMCID: PMC7138020

  32. Octanol–water partition coefficient measurements for the SAMPL6 blind prediction challenge
    Mehtap Işık, Dorothy Levorse, David L. Mobley, Timothy Rhodes, John D. Chodera
    Journal of Computer-Aided Molecular Design (2019-12-19) https://doi.org/gpjnws
    DOI: 10.1007/s10822-019-00271-3 · PMID: 31858363 · PMCID: PMC7301889

  33. Prediction of the n-octanol/water partition coefficients in the SAMPL6 blind challenge from MST continuum solvation calculations
    William J. Zamora, Silvana Pinheiro, Kilian German, Clara Ràfols, Carles Curutchet, F. Javier Luque
    Journal of Computer-Aided Molecular Design (2019-11-27) https://doi.org/gpjnwt
    DOI: 10.1007/s10822-019-00262-4 · PMID: 31776809

  34. SAMPL7: Host–guest binding prediction by molecular dynamics and quantum mechanics
    Yiğitcan Eken, Nuno M. S. Almeida, Cong Wang, Angela K. Wilson
    Journal of Computer-Aided Molecular Design (2020-11-05) https://doi.org/gpjnzn
    DOI: 10.1007/s10822-020-00357-3 · PMID: 33150463

  35. SAMPL7 blind predictions using nonequilibrium alchemical approaches
    Piero Procacci, Guido Guarnieri
    Journal of Computer-Aided Molecular Design (2021-01) https://doi.org/gpjnzp
    DOI: 10.1007/s10822-020-00365-3 · PMID: 33392950

  36. Testing automatic methods to predict free binding energy of host–guest complexes in SAMPL7 challenge
    Dylan Serillon, Carles Bo, Xavier Barril
    Journal of Computer-Aided Molecular Design (2021-01-19) https://doi.org/gpjnzq
    DOI: 10.1007/s10822-020-00370-6 · PMID: 33464434 · PMCID: PMC7904704

  37. Triptycene walled glycoluril trimer: synthesis and recognition properties
    Sandra Zebaze Ndendjio, Wenjin Liu, Nicolas Yvanez, Zihui Meng, Peter Y. Zavalij, Lyle Isaacs
    New Journal of Chemistry (2020) https://doi.org/gpjnwv
    DOI: 10.1039/c9nj05336k · PMID: 33867799 · PMCID: PMC8049523

  38. SAMPL6 Part II Partition Coefficient Challenge Overview
    Mehtap Işık
    Zenodo (2019-09-05) https://doi.org/gpjnww
    DOI: 10.5281/zenodo.3386592

  39. SAMPL: Its present and future, and some work on the logP challenge
    David L. Mobley
    Zenodo (2019-08-23) https://doi.org/gpjnwx
    DOI: 10.5281/zenodo.3376196

  40. Predicting Octanol–Water Partition Coefficients: Are Quantum Mechanical Implicit Solvent Models Better than Empirical Fragment-Based Methods?
    Varun Kundi, Junming Ho
    The Journal of Physical Chemistry B (2019-06-25) https://doi.org/gpjnwz
    DOI: 10.1021/acs.jpcb.9b04061 · PMID: 31343883

  41. pKa calculations for tautomerizable and conformationally flexible molecules: partition function vs. state transition approach
    Nicolas Tielker, Lukas Eberlein, Christian Chodun, Stefan Güssregen, Stefan M. Kast
    Journal of Molecular Modeling (2019-04-30) https://doi.org/gpjnw2
    DOI: 10.1007/s00894-019-4033-4 · PMID: 31041535

  42. SAMPL6 challenge results from p**K_(a) predictions based on a general Gaussian process model
    Caitlin C. Bannan, David L. Mobley, A. Geoffrey Skillman
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfp46p
    DOI: 10.1007/s10822-018-0169-z · PMID: 30324305 · PMCID: PMC6438616

  43. Overview of the SAMPL6 host–guest binding affinity prediction challenge
    Andrea Rizzi, Steven Murkli, John N. McNeill, Wei Yao, Matthew Sullivan, Michael K. Gilson, Michael W. Chiu, Lyle Isaacs, Bruce C. Gibb, David L. Mobley, John D. Chodera
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfpzh5
    DOI: 10.1007/s10822-018-0170-6 · PMID: 30415285 · PMCID: PMC6301044

  44. Improving Prediction Accuracy of Binding Free Energies and Poses of HIV Integrase Complexes Using the Binding Energy Distribution Analysis Method with Flattening Potentials
    Junchao Xia, William Flynn, Ronald M. Levy
    Journal of Chemical Information and Modeling (2018-06-21) https://doi.org/gd3g7m
    DOI: 10.1021/acs.jcim.8b00194 · PMID: 29927237 · PMCID: PMC6287956

  45. Atomic Radius and Charge Parameter Uncertainty in Biomolecular Solvation Energy Calculations
    Xiu Yang, Huan Lei, Peiyuan Gao, Dennis G. Thomas, David L. Mobley, Nathan A. Baker
    Journal of Chemical Theory and Computation (2018-01-29) https://doi.org/gpjnw3
    DOI: 10.1021/acs.jctc.7b00905 · PMID: 29293342 · PMCID: PMC6906122

  46. Absolute binding free energies for the SAMPL6 cucurbit[8]uril host–guest challenge via the AMOEBA polarizable force field
    Marie L. Laury, Zhi Wang, Aaron S. Gordon, Jay W. Ponder
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfqbbk
    DOI: 10.1007/s10822-018-0147-5 · PMID: 30324303 · PMCID: PMC6240481

  47. SAMPL6 host–guest blind predictions using a non equilibrium alchemical approach
    Piero Procacci, Massimiliano Guarrasi, Guido Guarnieri
    Journal of Computer-Aided Molecular Design (2018-08-20) https://doi.org/gfktn5
    DOI: 10.1007/s10822-018-0151-9 · PMID: 30128927

  48. High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge
    Philipp Pracht, Rainer Wilcken, Anikó Udvarhelyi, Stephane Rodde, Stefan Grimme
    Journal of Computer-Aided Molecular Design (2018-08-23) https://doi.org/gd3wz6
    DOI: 10.1007/s10822-018-0145-7 · PMID: 30141103

  49. The SAMPL6 challenge on predicting aqueous pKa values from EC-RISM theory
    Nicolas Tielker, Lukas Eberlein, Stefan Güssregen, Stefan M. Kast
    Journal of Computer-Aided Molecular Design (2018-08-02) https://doi.org/gfpw92
    DOI: 10.1007/s10822-018-0140-z · PMID: 30073500

  50. SAMPL6: calculation of macroscopic pKa values from ab initio quantum mechanical free energies
    Edithe Selwa, Ian M. Kenney, Oliver Beckstein, Bogdan I. Iorga
    Journal of Computer-Aided Molecular Design (2018-08-06) https://doi.org/gfpwc9
    DOI: 10.1007/s10822-018-0138-6 · PMID: 30084080 · PMCID: PMC6240492

  51. pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments
    Mehtap Işık, Dorothy Levorse, Ariën S. Rustenburg, Ikenna E. Ndukwe, Heather Wang, Xiao Wang, Mikhail Reibarkh, Gary E. Martin, Alexey A. Makarov, David L. Mobley, … John D. Chodera
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfpt98
    DOI: 10.1007/s10822-018-0168-0 · PMID: 30406372 · PMCID: PMC6367941

  52. SAMPL6 host–guest challenge: binding free energies via a multistep approach
    Yiğitcan Eken, Prajay Patel, Thomas Díaz, Michael R. Jones, Angela K. Wilson
    Journal of Computer-Aided Molecular Design (2018-09-17) https://doi.org/gfpxq8
    DOI: 10.1007/s10822-018-0159-1 · PMID: 30225724

  53. Binding free energies in the SAMPL6 octa-acid host–guest challenge calculated with MM and QM methods
    Octav Caldararu, Martin A. Olsson, Majda Misini Ignjatović, Meiting Wang, Ulf Ryde
    Journal of Computer-Aided Molecular Design (2018-09-10) https://doi.org/gfpwdb
    DOI: 10.1007/s10822-018-0158-2 · PMID: 30203229

  54. An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge
    Samarjeet Prasad, Jing Huang, Qiao Zeng, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfp24q
    DOI: 10.1007/s10822-018-0167-1 · PMID: 30276503 · PMCID: PMC6342563

  55. Absolute and relative pKa predictions via a DFT approach applied to the SAMPL6 blind challenge
    Qiao Zeng, Michael R. Jones, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2018-08-20) https://doi.org/gfktpc
    DOI: 10.1007/s10822-018-0150-x · PMID: 30128926 · PMCID: PMC6720109

  56. Prediction of CB[8] host–guest binding free energies in SAMPL6 using the double-decoupling method
    Kyungreem Han, Phillip S. Hudson, Michael R. Jones, Naohiro Nishikawa, Florentina Tofoleanu, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2018-08-06) https://doi.org/gfpzp2
    DOI: 10.1007/s10822-018-0144-8 · PMID: 30084077 · PMCID: PMC6347468

  57. Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale
    Phillip S. Hudson, Kyungreem Han, H. Lee Woodcock, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfp3pn
    DOI: 10.1007/s10822-018-0165-3 · PMID: 30276502 · PMCID: PMC6867086

  58. Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host–guest challenges
    Naohiro Nishikawa, Kyungreem Han, Xiongwu Wu, Florentina Tofoleanu, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2018-10) https://doi.org/gfz352
    DOI: 10.1007/s10822-018-0166-2 · PMID: 30324304 · PMCID: PMC6413509

  59. Detailed potential of mean force studies on host–guest systems from the SAMPL6 challenge
    Lin Frank Song, Nupur Bansal, Zheng Zheng, Kenneth M. Merz Jr.
    Journal of Computer-Aided Molecular Design (2018-08-24) https://doi.org/gfpw5t
    DOI: 10.1007/s10822-018-0153-7 · PMID: 30143917

  60. Predicting ligand binding affinity using on- and off-rates for the SAMPL6 SAMPLing challenge
    Tom Dixon, Samuel D. Lotz, Alex Dickson
    Journal of Computer-Aided Molecular Design (2018-08-23) https://doi.org/gfp3pw
    DOI: 10.1007/s10822-018-0149-3 · PMID: 30141102 · PMCID: PMC8299730

  61. Blinded predictions of standard binding free energies: lessons learned from the SAMPL6 challenge
    Michail Papadourakis, Stefano Bosisio, Julien Michel
    Journal of Computer-Aided Molecular Design (2018-08-29) https://doi.org/gfpbrc
    DOI: 10.1007/s10822-018-0154-6 · PMID: 30159717

  62. Bayesian Model Averaging for Ensemble-Based Estimates of Solvation-Free Energies
    Luke J. Gosink, Christopher C. Overall, Sarah M. Reehl, Paul D. Whitney, David L. Mobley, Nathan A. Baker
    The Journal of Physical Chemistry B (2017-01-04) https://doi.org/f9mn4p
    DOI: 10.1021/acs.jpcb.6b09198 · PMID: 27966363 · PMCID: PMC5398953

  63. Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset
    Michael R. Shirts, Christoph Klein, Jason M. Swails, Jian Yin, Michael K. Gilson, David L. Mobley, David A. Case, Ellen D. Zhong
    Journal of Computer-Aided Molecular Design (2016-10-27) https://doi.org/f9m3wn
    DOI: 10.1007/s10822-016-9977-1 · PMID: 27787702 · PMCID: PMC5581938

  64. On the fly estimation of host–guest binding free energies using the movable type method: participation in the SAMPL5 blind challenge
    Nupur Bansal, Zheng Zheng, David S. Cerutti, Kenneth M. Merz
    Journal of Computer-Aided Molecular Design (2016-10-03) https://doi.org/f9m84j
    DOI: 10.1007/s10822-016-9980-6 · PMID: 27699553

  65. Absolute binding free energy calculations of CBClip host–guest systems in the SAMPL5 blind challenge
    Juyong Lee, Florentina Tofoleanu, Frank C. Pickard IV, Gerhard König, Jing Huang, Ana Damjanović, Minkyung Baek, Chaok Seok, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2016-09-27) https://doi.org/f9m9gg
    DOI: 10.1007/s10822-016-9968-2 · PMID: 27677749 · PMCID: PMC5241186

  66. Overview of the SAMPL5 host–guest challenge: Are we doing better?
    Jian Yin, Niel M. Henriksen, David R. Slochower, Michael R. Shirts, Michael W. Chiu, David L. Mobley, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2016-09-22) https://doi.org/f9m82x
    DOI: 10.1007/s10822-016-9974-4 · PMID: 27658802 · PMCID: PMC5241188

  67. Binding free energies in the SAMPL5 octa-acid host–guest challenge calculated with DFT-D3 and CCSD(T)
    Octav Caldararu, Martin A. Olsson, Christoph Riplinger, Frank Neese, Ulf Ryde
    Journal of Computer-Aided Molecular Design (2016-09-06) https://doi.org/f9m8zz
    DOI: 10.1007/s10822-016-9957-5 · PMID: 27600554 · PMCID: PMC5239813

  68. Binding of carboxylate and trimethylammonium salts to octa-acid and TEMOA deep-cavity cavitands
    Matthew R. Sullivan, Punidha Sokkalingam, Thong Nguyen, James P. Donahue, Bruce C. Gibb
    Journal of Computer-Aided Molecular Design (2016-07-18) https://doi.org/f9m84c
    DOI: 10.1007/s10822-016-9925-0 · PMID: 27432339 · PMCID: PMC5571645

  69. Absolute binding free energies for octa-acids and guests in SAMPL5
    Florentina Tofoleanu, Juyong Lee, Frank C. Pickard IV, Gerhard König, Jing Huang, Minkyung Baek, Chaok Seok, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2016-09-30) https://doi.org/f9m9c2
    DOI: 10.1007/s10822-016-9965-5 · PMID: 27696242 · PMCID: PMC6472255

  70. Blinded predictions of host-guest standard free energies of binding in the SAMPL5 challenge
    Stefano Bosisio, Antonia S. J. S. Mey, Julien Michel
    Journal of Computer-Aided Molecular Design (2016-08-08) https://doi.org/f9nhw8
    DOI: 10.1007/s10822-016-9933-0 · PMID: 27503495

  71. The SAMPL5 host–guest challenge: computing binding free energies and enthalpies from explicit solvent simulations by the attach-pull-release (APR) method
    Jian Yin, Niel M. Henriksen, David R. Slochower, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2016-09-16) https://doi.org/f9m9fb
    DOI: 10.1007/s10822-016-9970-8 · PMID: 27638809 · PMCID: PMC5241238

  72. A combined treatment of hydration and dynamical effects for the modeling of host–guest binding thermodynamics: the SAMPL5 blinded challenge
    Rajat Kumar Pal, Kamran Haider, Divya Kaur, William Flynn, Junchao Xia, Ronald M Levy, Tetiana Taran, Lauren Wickstrom, Tom Kurtzman, Emilio Gallicchio
    Journal of Computer-Aided Molecular Design (2016-09-30) https://doi.org/f9nhc6
    DOI: 10.1007/s10822-016-9956-6 · PMID: 27696239 · PMCID: PMC5477994

  73. Resolving the problem of trapped water in binding cavities: prediction of host–guest binding free energies in the SAMPL5 challenge by funnel metadynamics
    Soumendranath Bhakat, Pär Söderhjelm
    Journal of Computer-Aided Molecular Design (2016-08-29) https://doi.org/f9m894
    DOI: 10.1007/s10822-016-9948-6 · PMID: 27573983 · PMCID: PMC5239820

  74. SAMPL5: 3D-RISM partition coefficient calculations with partial molar volume corrections and solute conformational sampling
    Tyler Luchko, Nikolay Blinov, Garrett C. Limon, Kevin P. Joyce, Andriy Kovalenko
    Journal of Computer-Aided Molecular Design (2016-09-01) https://doi.org/f9k5s7
    DOI: 10.1007/s10822-016-9947-7 · PMID: 27585474

  75. Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections
    Frank C. Pickard IV, Gerhard König, Florentina Tofoleanu, Juyong Lee, Andrew C. Simmonett, Yihan Shao, Jay W. Ponder, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2016-09-19) https://doi.org/f9k5nb
    DOI: 10.1007/s10822-016-9955-7 · PMID: 27646286

  76. Partition coefficients for the SAMPL5 challenge using transfer free energies
    Michael R. Jones, Bernard R. Brooks, Angela K. Wilson
    Journal of Computer-Aided Molecular Design (2016-09-19) https://doi.org/f9k83r
    DOI: 10.1007/s10822-016-9964-6 · PMID: 27646287 · PMCID: PMC6561331

  77. Adapting the semi-explicit assembly solvation model for estimating water-cyclohexane partitioning with the SAMPL5 molecules
    Emiliano Brini, S. Shanaka Paranahewage, Christopher J. Fennell, Ken A. Dill
    Journal of Computer-Aided Molecular Design (2016-09-08) https://doi.org/f9k5h2
    DOI: 10.1007/s10822-016-9961-9 · PMID: 27632227 · PMCID: PMC5261860

  78. Prediction of cyclohexane-water distribution coefficient for SAMPL5 drug-like compounds with the QMPFF3 and ARROW polarizable force fields
    Ganesh Kamath, Igor Kurnikov, Boris Fain, Igor Leontyev, Alexey Illarionov, Oleg Butin, Michael Olevanov, Leonid Pereyaslavets
    Journal of Computer-Aided Molecular Design (2016-09-01) https://doi.org/f9k5cd
    DOI: 10.1007/s10822-016-9958-4 · PMID: 27585472

  79. Calculation of distribution coefficients in the SAMPL5 challenge from atomic solvation parameters and surface areas
    Diogo Santos-Martins, Pedro Alexandrino Fernandes, Maria João Ramos
    Journal of Computer-Aided Molecular Design (2016-09-01) https://doi.org/f9k49n
    DOI: 10.1007/s10822-016-9951-y · PMID: 27585473

  80. Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field
    Ian M. Kenney, Oliver Beckstein, Bogdan I. Iorga
    Journal of Computer-Aided Molecular Design (2016-08-31) https://doi.org/f9md6z
    DOI: 10.1007/s10822-016-9949-5 · PMID: 27581968

  81. 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
    Gerhard König, Frank C. Pickard  IV, Jing Huang, Andrew C. Simmonett, Florentina Tofoleanu, Juyong Lee, Pavlo O. Dral, Samarjeet Prasad, Michael Jones, Yihan Shao, … Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2016-08-30) https://doi.org/f9k8x6
    DOI: 10.1007/s10822-016-9936-x · PMID: 27577746

  82. Predicting water-to-cyclohexane partitioning of the SAMPL5 molecules using dielectric balancing of force fields
    S. Shanaka Paranahewage, Cassidy S. Gierhart, Christopher J. Fennell
    Journal of Computer-Aided Molecular Design (2016-08-29) https://doi.org/f9k49f
    DOI: 10.1007/s10822-016-9950-z · PMID: 27573982 · PMCID: PMC5206264

  83. Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model
    Sebastian Diaz-Rodriguez, Samantha M. Bozada, Jeremy R. Phifer, Andrew S. Paluch
    Journal of Computer-Aided Molecular Design (2016-08-26) https://doi.org/f9k82v
    DOI: 10.1007/s10822-016-9945-9 · PMID: 27565796

  84. The SAMPL5 challenge for embedded-cluster integral equation theory: solvation free energies, aqueous pK a, and cyclohexane–water log D
    Nicolas Tielker, Daniel Tomazic, Jochen Heil, Thomas Kloss, Sebastian Ehrhart, Stefan Güssregen, K. Friedemann Schmidt, Stefan M. Kast
    Journal of Computer-Aided Molecular Design (2016-08-23) https://doi.org/f9k496
    DOI: 10.1007/s10822-016-9939-7 · PMID: 27554666

  85. Evaluating Parametrization Protocols for Hydration Free Energy Calculations with the AMOEBA Polarizable Force Field
    Richard T. Bradshaw, Jonathan W. Essex
    Journal of Chemical Theory and Computation (2016-07-29) https://doi.org/f83ghv
    DOI: 10.1021/acs.jctc.6b00276 · PMID: 27341007

  86. All-atom/coarse-grained hybrid predictions of distribution coefficients in SAMPL5
    Samuel Genheden, Jonathan W. Essex
    Journal of Computer-Aided Molecular Design (2016-07-26) https://doi.org/f3r3jk
    DOI: 10.1007/s10822-016-9926-z · PMID: 27460060 · PMCID: PMC5206257

  87. Prediction of cyclohexane-water distribution coefficients with COSMO-RS on the SAMPL5 data set
    Andreas Klamt, Frank Eckert, Jens Reinisch, Karin Wichmann
    Journal of Computer-Aided Molecular Design (2016-07-26) https://doi.org/f9k824
    DOI: 10.1007/s10822-016-9927-y · PMID: 27460058

  88. Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules
    Kee-Choo Chung, Hwangseo Park
    Journal of Computer-Aided Molecular Design (2016-07-23) https://doi.org/f9k5wq
    DOI: 10.1007/s10822-016-9928-x · PMID: 27448686

  89. Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge
    Ariën S. Rustenburg, Justin Dancer, Baiwei Lin, Jianwen A. Feng, Daniel F. Ortwine, David L. Mobley, John D. Chodera
    Journal of Computer-Aided Molecular Design (2016-10-07) https://doi.org/f9k5mr
    DOI: 10.1007/s10822-016-9971-7 · PMID: 27718028 · PMCID: PMC5209288

  90. BEDAM binding free energy predictions for the SAMPL4 octa-acid host challenge
    Emilio Gallicchio, Haoyuan Chen, He Chen, Michael Fitzgerald, Yang Gao, Peng He, Malathi Kalyanikar, Chuan Kao, Beidi Lu, Yijie Niu, … Ronald M. Levy
    Journal of Computer-Aided Molecular Design (2015-03-01) https://doi.org/f657sv
    DOI: 10.1007/s10822-014-9795-2 · PMID: 25726024 · PMCID: PMC4832917

  91. Distinguishing Binders from False Positives by Free Energy Calculations: Fragment Screening Against the Flap Site of HIV Protease
    Nanjie Deng, Stefano Forli, Peng He, Alex Perryman, Lauren Wickstrom, R. S. K. Vijayan, Theresa Tiefenbrunn, David Stout, Emilio Gallicchio, Arthur J. Olson, Ronald M. Levy
    The Journal of Physical Chemistry B (2014-09-17) https://doi.org/f66q9b
    DOI: 10.1021/jp506376z · PMID: 25189630 · PMCID: PMC4306491

  92. SAMPL4, a blind challenge for computational solvation free energies: the compounds considered
    J. Peter Guthrie
    Journal of Computer-Aided Molecular Design (2014-03) https://doi.org/f52knt
    DOI: 10.1007/s10822-014-9738-y · PMID: 24706106

  93. Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host–guest binding energies
    Paulius Mikulskis, Daniela Cioloboc, Milica Andrejić, Sakshi Khare, Joakim Brorsson, Samuel Genheden, Ricardo A. Mata, Pär Söderhjelm, Ulf Ryde
    Journal of Computer-Aided Molecular Design (2014-04) https://doi.org/f229ks
    DOI: 10.1007/s10822-014-9739-x · PMID: 24700414

  94. Absolute and relative binding affinity of cucurbit[7]uril towards a series of cationic guests
    Liping Cao, Lyle Isaacs
    Supramolecular Chemistry (2013-11-19) https://doi.org/gpjn6r
    DOI: 10.1080/10610278.2013.852674

  95. Efficient calculation of SAMPL4 hydration free energies using OMEGA, SZYBKI, QUACPAC, and Zap TK
    Benjamin A. Ellingson, Matthew T. Geballe, Stanislaw Wlodek, Christopher I. Bayly, A. Geoffrey Skillman, Anthony Nicholls
    Journal of Computer-Aided Molecular Design (2014-03) https://doi.org/f52kcs
    DOI: 10.1007/s10822-014-9720-8 · PMID: 24633516 · PMCID: PMC4003403

  96. Converging free energies of binding in cucurbit[7]uril and octa-acid host–guest systems from SAMPL4 using expanded ensemble simulations
    Jacob I. Monroe, Michael R. Shirts
    Journal of Computer-Aided Molecular Design (2014-03-08) https://doi.org/f559fx
    DOI: 10.1007/s10822-014-9716-4 · PMID: 24610238

  97. The SAMPL4 host–guest blind prediction challenge: an overview
    Hari S. Muddana, Andrew T. Fenley, David L. Mobley, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2014-03-06) https://doi.org/f5585s
    DOI: 10.1007/s10822-014-9735-1 · PMID: 24599514 · PMCID: PMC4053502

  98. Prediction of hydration free energies for the SAMPL4 data set with the AMOEBA polarizable force field
    Francesco Manzoni, Pär Söderhjelm
    Journal of Computer-Aided Molecular Design (2014-03) https://doi.org/f2378s
    DOI: 10.1007/s10822-014-9733-3 · PMID: 24577872

  99. Blind prediction of solvation free energies from the SAMPL4 challenge
    David L. Mobley, Karisa L. Wymer, Nathan M. Lim, J. Peter Guthrie
    Journal of Computer-Aided Molecular Design (2014-03) https://doi.org/gmjg9j
    DOI: 10.1007/s10822-014-9718-2 · PMID: 24615156 · PMCID: PMC4006301

  100. Prediction of hydration free energies for the SAMPL4 diverse set of compounds using molecular dynamics simulations with the OPLS-AA force field
    Oliver Beckstein, Anaïs Fourrier, Bogdan I. Iorga
    Journal of Computer-Aided Molecular Design (2014-02-21) https://doi.org/f5z48p
    DOI: 10.1007/s10822-014-9727-1 · PMID: 24557853

  101. Extended solvent-contact model approach to SAMPL4 blind prediction challenge for hydration free energies
    Hwangseo Park
    Journal of Computer-Aided Molecular Design (2014-02-20) https://doi.org/f52kxd
    DOI: 10.1007/s10822-014-9729-z · PMID: 24554191

  102. Predicting hydration free energies with chemical accuracy: the SAMPL4 challenge
    Lars Sandberg
    Journal of Computer-Aided Molecular Design (2014-02-19) https://doi.org/gpjn6s
    DOI: 10.1007/s10822-014-9725-3 · PMID: 24550133

  103. Prediction of SAMPL4 host–guest binding affinities using funnel metadynamics
    Ya-Wen Hsiao, Pär Söderhjelm
    Journal of Computer-Aided Molecular Design (2014-02-18) https://doi.org/f24mqd
    DOI: 10.1007/s10822-014-9724-4 · PMID: 24535628

  104. Interrogating HIV integrase for compounds that bind- a SAMPL challenge
    Thomas S. Peat, Olan Dolezal, Janet Newman, David Mobley, John J. Deadman
    Journal of Computer-Aided Molecular Design (2014-02-16) https://doi.org/f55ks9
    DOI: 10.1007/s10822-014-9721-7 · PMID: 24532034 · PMCID: PMC4346355

  105. SAMPL4 & DOCK3.7: lessons for automated docking procedures
    Ryan G. Coleman, Teague Sterling, Dahlia R. Weiss
    Journal of Computer-Aided Molecular Design (2014-02-11) https://doi.org/gpjn6t
    DOI: 10.1007/s10822-014-9722-6 · PMID: 24515818 · PMCID: PMC4006303

  106. Blind prediction of SAMPL4 cucurbit[7]uril binding affinities with the mining minima method
    Hari S. Muddana, Jian Yin, Neil V. Sapra, Andrew T. Fenley, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2014-02-08) https://doi.org/f5585x
    DOI: 10.1007/s10822-014-9726-2 · PMID: 24510191 · PMCID: PMC4053532

  107. Predicting hydration free energies with a hybrid QM/MM approach: an evaluation of implicit and explicit solvation models in SAMPL4
    Gerhard König, Frank C. Pickard IV, Ye Mei, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2014-02-07) https://doi.org/f52hpf
    DOI: 10.1007/s10822-014-9708-4 · PMID: 24504703 · PMCID: PMC4199574

  108. Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge
    Emilio Gallicchio, Nanjie Deng, Peng He, Lauren Wickstrom, Alexander L. Perryman, Daniel N. Santiago, Stefano Forli, Arthur J. Olson, Ronald M. Levy
    Journal of Computer-Aided Molecular Design (2014-02-07) https://doi.org/f55vmc
    DOI: 10.1007/s10822-014-9711-9 · PMID: 24504704 · PMCID: PMC4137862

  109. Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein–ligand binding challenge
    Alexander L. Perryman, Daniel N. Santiago, Stefano Forli, Diogo Santos-Martins, Arthur J. Olson
    Journal of Computer-Aided Molecular Design (2014-02-04) https://doi.org/f55kvn
    DOI: 10.1007/s10822-014-9709-3 · PMID: 24493410 · PMCID: PMC4053500

  110. Extensive all-atom Monte Carlo sampling and QM/MM corrections in the SAMPL4 hydration free energy challenge
    Samuel Genheden, Ana I. Cabedo Martinez, Michael P. Criddle, Jonathan W. Essex
    Journal of Computer-Aided Molecular Design (2014-02-01) https://doi.org/f52k2v
    DOI: 10.1007/s10822-014-9717-3 · PMID: 24488307

  111. Testing and validation of the Automated Topology Builder (ATB) version 2.0: prediction of hydration free enthalpies
    Katarzyna B. Koziara, Martin Stroet, Alpeshkumar K. Malde, Alan E. Mark
    Journal of Computer-Aided Molecular Design (2014-01-30) https://doi.org/f52hnr
    DOI: 10.1007/s10822-014-9713-7 · PMID: 24477799

  112. The SAMPL4 hydration challenge: evaluation of partial charge sets with explicit-water molecular dynamics simulations
    Hari S. Muddana, Neil V. Sapra, Andrew T. Fenley, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2014-01-30) https://doi.org/f5z6vh
    DOI: 10.1007/s10822-014-9714-6 · PMID: 24477800 · PMCID: PMC4006311

  113. Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge
    Hervé Hogues, Traian Sulea, Enrico O. Purisima
    Journal of Computer-Aided Molecular Design (2014-01-29) https://doi.org/f55kp7
    DOI: 10.1007/s10822-014-9715-5 · PMID: 24474162

  114. Testing the semi-explicit assembly model of aqueous solvation in the SAMPL4 challenge
    Libo Li, Ken A. Dill, Christopher J. Fennell
    Journal of Computer-Aided Molecular Design (2014-01-29) https://doi.org/f56g9z
    DOI: 10.1007/s10822-014-9712-8 · PMID: 24474161

  115. Virtual screening of the SAMPL4 blinded HIV integrase inhibitors dataset
    Claire Colas, Bogdan I. Iorga
    Journal of Computer-Aided Molecular Design (2014-01-24) https://doi.org/f55knd
    DOI: 10.1007/s10822-014-9707-5 · PMID: 24458507

  116. Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4
    Arnout R. D. Voet, Ashutosh Kumar, Francois Berenger, Kam Y. J. Zhang
    Journal of Computer-Aided Molecular Design (2014-01-21) https://doi.org/f5587p
    DOI: 10.1007/s10822-013-9702-2 · PMID: 24446075

  117. Prediction of free energies of hydration with COSMO-RS on the SAMPL4 data set
    Jens Reinisch, Andreas Klamt
    Journal of Computer-Aided Molecular Design (2014-01-14) https://doi.org/gpjn6v
    DOI: 10.1007/s10822-013-9701-3 · PMID: 24420026

  118. Blind prediction of HIV integrase binding from the SAMPL4 challenge
    David L. Mobley, Shuai Liu, Nathan M. Lim, Karisa L. Wymer, Alexander L. Perryman, Stefano Forli, Nanjie Deng, Justin Su, Kim Branson, Arthur J. Olson
    Journal of Computer-Aided Molecular Design (2014-03-05) https://doi.org/gpjn6w
    DOI: 10.1007/s10822-014-9723-5 · PMID: 24595873 · PMCID: PMC4331050

  119. Binding of cyclic carboxylates to octa-acid deep-cavity cavitand
    Corinne L. D. Gibb, Bruce C. Gibb
    Journal of Computer-Aided Molecular Design (2013-11-12) https://doi.org/f557xs
    DOI: 10.1007/s10822-013-9690-2 · PMID: 24218290 · PMCID: PMC4018434

  120. SAMPL3: blinded prediction of host–guest binding affinities, hydration free energies, and trypsin inhibitors
    A. Geoffrey Skillman
    Journal of Computer-Aided Molecular Design (2012-05) https://doi.org/gpcdf5
    DOI: 10.1007/s10822-012-9580-z · PMID: 22622621

  121. Prediction of free energies of hydration with COSMO-RS on the SAMPL3 data set
    Jens Reinisch, Andreas Klamt, Michael Diedenhofen
    Journal of Computer-Aided Molecular Design (2012-05) https://doi.org/ggddnc
    DOI: 10.1007/s10822-012-9576-8 · PMID: 22581451

  122. The SAMPL3 blind prediction challenge: transfer energy overview
    Matthew T. Geballe, J. Peter Guthrie
    Journal of Computer-Aided Molecular Design (2012-04-03) https://doi.org/f33w36
    DOI: 10.1007/s10822-012-9568-8 · PMID: 22476552

  123. Force-field and quantum-mechanical binding study of selected SAMPL3 host-guest complexes
    Nobuko Hamaguchi, Laszlo Fusti-Molnar, Stanislaw Wlodek
    Journal of Computer-Aided Molecular Design (2012-02-25) https://doi.org/f33jzz
    DOI: 10.1007/s10822-012-9553-2 · PMID: 22366954

  124. Blind prediction of host–guest binding affinities: a new SAMPL3 challenge
    Hari S. Muddana, C. Daniel Varnado, Christopher W. Bielawski, Adam R. Urbach, Lyle Isaacs, Matthew T. Geballe, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2012-02-25) https://doi.org/f33gww
    DOI: 10.1007/s10822-012-9554-1 · PMID: 22366955 · PMCID: PMC3383923

  125. Prediction of SAMPL3 host-guest affinities with the binding energy distribution analysis method (BEDAM)
    Emilio Gallicchio, Ronald M. Levy
    Journal of Computer-Aided Molecular Design (2012-02-22) https://doi.org/f33zq2
    DOI: 10.1007/s10822-012-9552-3 · PMID: 22354755 · PMCID: PMC3383899

  126. Thermodynamic integration to predict host-guest binding affinities
    Morgan Lawrenz, Jeff Wereszczynski, Juan Manuel Ortiz-Sánchez, Sara E. Nichols, J. Andrew McCammon
    Journal of Computer-Aided Molecular Design (2012-02-16) https://doi.org/f33w8c
    DOI: 10.1007/s10822-012-9542-5 · PMID: 22350568 · PMCID: PMC4113475

  127. A fragment-based approach to the SAMPL3 Challenge
    John L. Kulp III, Seth N. Blumenthal, Qiang Wang, Richard L. Bryan, Frank Guarnieri
    Journal of Computer-Aided Molecular Design (2012-01-31) https://doi.org/fxz566
    DOI: 10.1007/s10822-012-9546-1 · PMID: 22290624

  128. Prediction of SAMPL3 host–guest binding affinities: evaluating the accuracy of generalized force-fields
    Hari S. Muddana, Michael K. Gilson
    Journal of Computer-Aided Molecular Design (2012-01-25) https://doi.org/fxwh8w
    DOI: 10.1007/s10822-012-9544-3 · PMID: 22274835 · PMCID: PMC3383906

  129. Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge
    Ashutosh Kumar, Kam Y. J. Zhang
    Journal of Computer-Aided Molecular Design (2012-01-15) https://doi.org/fzr9mp
    DOI: 10.1007/s10822-011-9523-0 · PMID: 22246345

  130. Alchemical prediction of hydration free energies for SAMPL
    David L. Mobley, Shaui Liu, David S. Cerutti, William C. Swope, Julia E. Rice
    Journal of Computer-Aided Molecular Design (2011-12-24) https://doi.org/fxnqwp
    DOI: 10.1007/s10822-011-9528-8 · PMID: 22198475 · PMCID: PMC3583515

  131. Prediction of trypsin/molecular fragment binding affinities by free energy decomposition and empirical scores
    Mark L. Benson, John C. Faver, Melek N. Ucisik, Danial S. Dashti, Zheng Zheng, Kenneth M. Merz Jr.
    Journal of Computer-Aided Molecular Design (2012-04-04) https://doi.org/f329j4
    DOI: 10.1007/s10822-012-9567-9 · PMID: 22476578

  132. Testing the semi-explicit assembly solvation model in the SAMPL3 community blind test
    Charles W. Kehoe, Christopher J. Fennell, Ken A. Dill
    Journal of Computer-Aided Molecular Design (2011-12-29) https://doi.org/fxh8dn
    DOI: 10.1007/s10822-011-9536-8 · PMID: 22205387

  133. Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction
    Traian Sulea, Hervé Hogues, Enrico O. Purisima
    Journal of Computer-Aided Molecular Design (2011-12-25) https://doi.org/fzx3v3
    DOI: 10.1007/s10822-011-9529-7 · PMID: 22198519

  134. Binding affinities in the SAMPL3 trypsin and host–guest blind tests estimated with the MM/PBSA and LIE methods
    Paulius Mikulskis, Samuel Genheden, Patrik Rydberg, Lars Sandberg, Lars Olsen, Ulf Ryde
    Journal of Computer-Aided Molecular Design (2011-12-25) https://doi.org/fzbbcv
    DOI: 10.1007/s10822-011-9524-z · PMID: 22198518

  135. Predicting binding affinities of host-guest systems in the SAMPL3 blind challenge: the performance of relative free energy calculations
    Gerhard König, Bernard R. Brooks
    Journal of Computer-Aided Molecular Design (2011-12-24) https://doi.org/fx5jxq
    DOI: 10.1007/s10822-011-9525-y · PMID: 22198474 · PMCID: PMC3584352

  136. Predicting hydration free energies of polychlorinated aromatic compounds from the SAMPL-3 data set with FiSH and LIE models
    Traian Sulea, Enrico O. Purisima
    Journal of Computer-Aided Molecular Design (2011-12-22) https://doi.org/fztfjb
    DOI: 10.1007/s10822-011-9522-1 · PMID: 22190141

  137. Prediction of hydration free energies for aliphatic and aromatic chloro derivatives using molecular dynamics simulations with the OPLS-AA force field
    Oliver Beckstein, Bogdan I. Iorga
    Journal of Computer-Aided Molecular Design (2011-12-21) https://doi.org/fx74fm
    DOI: 10.1007/s10822-011-9527-9 · PMID: 22187140

  138. The DINGO dataset: a comprehensive set of data for the SAMPL challenge
    Janet Newman, Olan Dolezal, Vincent Fazio, Tom Caradoc-Davies, Thomas S. Peat
    Journal of Computer-Aided Molecular Design (2011-12-21) https://doi.org/fx2gqh
    DOI: 10.1007/s10822-011-9521-2 · PMID: 22187139 · PMCID: PMC3382646

  139. Evaluation of docking performance in a blinded virtual screening of fragment-like trypsin inhibitors
    Georgiana Surpateanu, Bogdan I. Iorga
    Journal of Computer-Aided Molecular Design (2011-12-17) https://doi.org/c537mw
    DOI: 10.1007/s10822-011-9526-x · PMID: 22180049

  140. Modeling aqueous solvation with semi-explicit assembly
    Christopher J. Fennell, Charles W. Kehoe, Ken A. Dill
    Proceedings of the National Academy of Sciences (2011-02-07) https://doi.org/dmrx94
    DOI: 10.1073/pnas.1017130108 · PMID: 21300905 · PMCID: PMC3044389

  141. The SAMPL2 blind prediction challenge: introduction and overview
    Matthew T. Geballe, A. Geoffrey Skillman, Anthony Nicholls, J. Peter Guthrie, Peter J. Taylor
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/bcz2nw
    DOI: 10.1007/s10822-010-9350-8 · PMID: 20455007

  142. Analysis of SM8 and Zap TK calculations and their geometric sensitivity
    Benjamin A. Ellingson, A. Geoffrey Skillman, Anthony Nicholls
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/fr3cjc
    DOI: 10.1007/s10822-010-9355-3 · PMID: 20432055

  143. SAMPL2 challenge: prediction of solvation energies and tautomer ratios
    A. Geoffrey Skillman, Matthew T. Geballe, Anthony Nicholls
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/cqz8cr
    DOI: 10.1007/s10822-010-9358-0 · PMID: 20425136

  144. Blind prediction test of free energies of hydration with COSMO-RS
    Andreas Klamt, Michael Diedenhofen
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/dhzfjn
    DOI: 10.1007/s10822-010-9354-4 · PMID: 20383653

  145. Some conclusions regarding the predictions of tautomeric equilibria in solution based on the SAMPL2 challenge
    Andreas Klamt, Michael Diedenhofen
    Journal of Computer-Aided Molecular Design (2010-04-08) https://doi.org/fcs9zg
    DOI: 10.1007/s10822-010-9332-x · PMID: 20376531

  146. SAMPL2 and continuum modeling
    Anthony Nicholls, Stanislaw Wlodek, J. Andrew Grant
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/b7nksr
    DOI: 10.1007/s10822-010-9334-8 · PMID: 20372975

  147. Rapid prediction of solvation free energy. 3. Application to the SAMPL2 challenge
    Enrico O. Purisima, Christopher R. Corbeil, Traian Sulea
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/cr6vd2
    DOI: 10.1007/s10822-010-9341-9 · PMID: 20414699

  148. Prediction of SAMPL2 aqueous solvation free energies and tautomeric ratios using the SM8, SM8AD, and SMD solvation models
    Raphael F. Ribeiro, Aleksandr V. Marenich, Christopher J. Cramer, Donald G. Truhlar
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/dbwmnj
    DOI: 10.1007/s10822-010-9333-9 · PMID: 20358259

  149. Predicting hydration free energies using all-atom molecular dynamics simulations and multiple starting conformations
    Pavel V. Klimovich, David L. Mobley
    Journal of Computer-Aided Molecular Design (2010-04) https://doi.org/fmjpp9
    DOI: 10.1007/s10822-010-9343-7 · PMID: 20372973

  150. Predictions of hydration free energies from continuum solvent with solute polarizable models: the SAMPL2 blind challenge
    Alexandre Meunier, Jean-François Truchon
    Journal of Computer-Aided Molecular Design (2010-03-31) https://doi.org/cq66bv
    DOI: 10.1007/s10822-010-9339-3 · PMID: 20354893

  151. Prediction of tautomer ratios by embedded-cluster integral equation theory
    Stefan M. Kast, Jochen Heil, Stefan Güssregen, K. Friedemann Schmidt
    Journal of Computer-Aided Molecular Design (2010-03-30) https://doi.org/cc458z
    DOI: 10.1007/s10822-010-9340-x · PMID: 20352296

  152. Performance of the IEF-MST solvation continuum model in the SAMPL2 blind test prediction of hydration and tautomerization free energies
    Ignacio Soteras, Modesto Orozco, F. Javier Luque
    Journal of Computer-Aided Molecular Design (2010-03-19) https://doi.org/cc8mgk
    DOI: 10.1007/s10822-010-9331-y · PMID: 20300801

  153. The SAMP1 Solvation Challenge: Further Lessons Regarding the Pitfalls of Parametrization
    Anthony Nicholls, Stanislaw Wlodek, J. Andrew Grant
    The Journal of Physical Chemistry B (2009-03-12) https://doi.org/bhrps8
    DOI: 10.1021/jp806855q · PMID: 19281198

  154. Prediction of SAMPL-1 Hydration Free Energies Using a Continuum Electrostatics-Dispersion Model
    Traian Sulea, Duangporn Wanapun, Sheldon Dennis, Enrico O. Purisima
    The Journal of Physical Chemistry B (2009-03-06) https://doi.org/bwp566
    DOI: 10.1021/jp8061477 · PMID: 19267492

  155. Performance of SM6, SM8, and SMD on the SAMPL1 Test Set for the Prediction of Small-Molecule Solvation Free Energies
    Aleksandr V. Marenich, Christopher J. Cramer, Donald G. Truhlar
    The Journal of Physical Chemistry B (2009-03-02) https://doi.org/cvcp2g
    DOI: 10.1021/jp809094y · PMID: 19253989

  156. A Blind Challenge for Computational Solvation Free Energies: Introduction and Overview
    J. Peter Guthrie
    ACS Publications (2009-04-02) https://pubs.acs.org/doi/abs/10.1021/jp806724u

  157. Prediction of the Free Energy of Hydration of a Challenging Set of Pesticide-Like Compounds†
    Andreas Klamt, Frank Eckert, Michael Diedenhofen
    ACS Publications (2009-03-10) https://pubs.acs.org/doi/abs/10.1021/jp805853y

  158. Practical Aspects of the SAMPL Challenge: Providing an Extensive Experimental Data Set for the Modeling Community
    Janet Newman, Vincent J. Fazio, Tom T. Caradoc-Davies, Kim Branson, Thomas S. Peat
    Journal of Biomolecular Screening (2009-10-12) https://doi.org/b23t6k
    DOI: 10.1177/1087057109348220 · PMID: 19822883

  159. Predictions of Hydration Free Energies from All-Atom Molecular Dynamics Simulations
    David L. Mobley, Christopher I. Bayly, Matthew D. Cooper, Ken A. Dill
    The Journal of Physical Chemistry B (2009-04-09) https://pubs.acs.org/doi/10.1021/jp806838b
    DOI: 10.1021/jp806838b

  160. Performance of SM8 on a Test To Predict Small-Molecule Solvation Free Energies
    Adam C. Chamberlin, Christopher J. Cramer, Donald G. Truhlar
    The Journal of Physical Chemistry B (2008-06-26) https://doi.org/cn88b6
    DOI: 10.1021/jp8028038 · PMID: 18582013 · PMCID: PMC2652251

  161. Predicting Small-Molecule Solvation Free Energies: An Informal Blind Test for Computational Chemistry
    Anthony Nicholls, David L. Mobley, J. Peter Guthrie, John D. Chodera, Christopher I. Bayly, Matthew D. Cooper, Vijay S. Pande
    Journal of Medicinal Chemistry (2008-01-24) https://doi.org/dpkkf9
    DOI: 10.1021/jm070549+ · PMID: 18215013

Updated: