1
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Fischer AL, Tichy A, Kokot J, Hoerschinger VJ, Wild RF, Riccabona JR, Loeffler JR, Waibl F, Quoika PK, Gschwandtner P, Forli S, Ward AB, Liedl KR, Zacharias M, Fernández-Quintero ML. The Role of Force Fields and Water Models in Protein Folding and Unfolding Dynamics. J Chem Theory Comput 2024; 20:2321-2333. [PMID: 38373307 PMCID: PMC10938642 DOI: 10.1021/acs.jctc.3c01106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/29/2024] [Accepted: 01/29/2024] [Indexed: 02/21/2024]
Abstract
Protein folding is a fascinating, not fully understood phenomenon in biology. Molecular dynamics (MD) simulations are an invaluable tool to study conformational changes in atomistic detail, including folding and unfolding processes of proteins. However, the accuracy of the conformational ensembles derived from MD simulations inevitably relies on the quality of the underlying force field in combination with the respective water model. Here, we investigate protein folding, unfolding, and misfolding of fast-folding proteins by examining different force fields with their recommended water models, i.e., ff14SB with the TIP3P model and ff19SB with the OPC model. To this end, we generated long conventional MD simulations highlighting the perks and pitfalls of these setups. Using Markov state models, we defined kinetically independent conformational substates and emphasized their distinct characteristics, as well as their corresponding state probabilities. Surprisingly, we found substantial differences in thermodynamics and kinetics of protein folding, depending on the combination of the protein force field and water model, originating primarily from the different water models. These results emphasize the importance of carefully choosing the force field and the respective water model as they determine the accuracy of the observed dynamics of folding events. Thus, the findings support the hypothesis that the water model is at least equally important as the force field and hence needs to be considered in future studies investigating protein dynamics and folding in all areas of biophysics.
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Affiliation(s)
- Anna-Lena
M. Fischer
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Anna Tichy
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Janik Kokot
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Valentin J. Hoerschinger
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Robert F. Wild
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Jakob R. Riccabona
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Johannes R. Loeffler
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Franz Waibl
- Department
of Chemistry and Applied Biosciences, ETH
Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Patrick K. Quoika
- Center
for Protein Assemblies (CPA), Physics Department, Chair of Theoretical
Biophysics, Technical University of Munich, D-80333 Munich, Germany
| | | | - Stefano Forli
- Department
of Integrative Structural and Computational Biology, Scripps Research Institute, La
Jolla, California 92037, United States
| | - Andrew B. Ward
- Department
of Integrative Structural and Computational Biology, Scripps Research Institute, La
Jolla, California 92037, United States
| | - Klaus R. Liedl
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
| | - Martin Zacharias
- Center
for Protein Assemblies (CPA), Physics Department, Chair of Theoretical
Biophysics, Technical University of Munich, D-80333 Munich, Germany
| | - Monica L. Fernández-Quintero
- Institute
for General, Inorganic and Theoretical Chemistry, Center for Molecular
Biosciences Innsbruck (CMBI), University
of Innsbruck, A-6020 Innsbruck, Austria
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2
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Kim Y, Jung H, Kumar S, Paton RS, Kim S. Designing solvent systems using self-evolving solubility databases and graph neural networks. Chem Sci 2024; 15:923-939. [PMID: 38239675 PMCID: PMC10793204 DOI: 10.1039/d3sc03468b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 12/04/2023] [Indexed: 01/22/2024] Open
Abstract
Designing solvent systems is key to achieving the facile synthesis and separation of desired products from chemical processes, so many machine learning models have been developed to predict solubilities. However, breakthroughs are needed to address deficiencies in the model's predictive accuracy and generalizability; this can be addressed by expanding and integrating experimental and computational solubility databases. To maximize predictive accuracy, these two databases should not be trained separately, and they should not be simply combined without reconciling the discrepancies from different magnitudes of errors and uncertainties. Here, we introduce self-evolving solubility databases and graph neural networks developed through semi-supervised self-training approaches. Solubilities from quantum-mechanical calculations are referred to during semi-supervised learning, but they are not directly added to the experimental database. Dataset augmentation is performed from 11 637 experimental solubilities to >900 000 data points in the integrated database, while correcting for the discrepancies between experiment and computation. Our model was successfully applied to study solvent selection in organic reactions and separation processes. The accuracy (mean absolute error around 0.2 kcal mol-1 for the test set) is quantitatively useful in exploring Linear Free Energy Relationships between reaction rates and solvation free energies for 11 organic reactions. Our model also accurately predicted the partition coefficients of lignin-derived monomers and drug-like molecules. While there is room for expanding solubility predictions to transition states, radicals, charged species, and organometallic complexes, this approach will be attractive to predictive chemistry areas where experimental, computational, and other heterogeneous data should be combined.
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Affiliation(s)
- Yeonjoon Kim
- Department of Chemistry, Colorado State University Fort Collins CO 80523 USA
- Department of Chemistry, Pukyong National University Busan 48513 Republic of Korea
| | - Hojin Jung
- Department of Chemistry, Colorado State University Fort Collins CO 80523 USA
| | - Sabari Kumar
- Department of Chemistry, Colorado State University Fort Collins CO 80523 USA
| | - Robert S Paton
- Department of Chemistry, Colorado State University Fort Collins CO 80523 USA
| | - Seonah Kim
- Department of Chemistry, Colorado State University Fort Collins CO 80523 USA
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3
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Ali HS, Henchman RH. Energy-entropy multiscale cell correlation method to predict toluene-water log P in the SAMPL9 challenge. Phys Chem Chem Phys 2023; 25:27524-27531. [PMID: 37800345 PMCID: PMC11411597 DOI: 10.1039/d3cp03076h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
The energy-entropy multiscale cell correlation (EE-MCC) method is used to calculate toluene-water log P values of 16 drug molecules in the SAMPL9 physical properties challenge. EE-MCC calculates the free energy, energy and entropy from molecular dynamics (MD) simulations of the water and toluene solutions. Specifically, MCC evaluates entropy by partitioning the system into cells of correlated atoms at multiple length scales and further partitioning the local coordinates into energy wells, yielding vibrational and topographical terms from the energy-well sizes and probabilities. The log P values calculated by EE-MCC using three 200 ns MD simulations have a mean average error of 0.82 and standard error of the mean of 0.97 versus experiment, which is comparable with the best methods entered in SAMPL9. The main contribution to log P is from energy. Less polar drugs have more favourable energies of transfer. The entropy of transfer consists of increased solute vibrational and conformational terms in toluene due to weaker interactions, fewer solute positions in the larger-molecule solvent, reduced water vibrational entropy, negligible change in toluene vibrational entropy, and gains in solvent orientational entropy. The solvent entropy contributions here may be slightly underestimated because software limitations and statistical fluctuations meant that only the first shell could be included while averaged over the whole solution. Nonetheless, such issues will be addressed in future software to offer a general method to calculate entropy directly from MD simulation and to provide molecular understanding or guide system design.
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Affiliation(s)
- Hafiz Saqib Ali
- Chemistry Research Laboratory, Department of Chemistry and the INEOS Oxford Institute for Antimicrobial Research, University of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK.
| | - Richard H Henchman
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
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4
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Wu R, Metternich JB, Kamenik AS, Tiwari P, Harrison JA, Kessen D, Akay H, Benzenberg LR, Chan TWD, Riniker S, Zenobi R. Determining the gas-phase structures of α-helical peptides from shape, microsolvation, and intramolecular distance data. Nat Commun 2023; 14:2913. [PMID: 37217470 PMCID: PMC10203302 DOI: 10.1038/s41467-023-38463-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 04/19/2023] [Indexed: 05/24/2023] Open
Abstract
Mass spectrometry is a powerful technique for the structural and functional characterization of biomolecules. However, it remains challenging to accurately gauge the gas-phase structure of biomolecular ions and assess to what extent native-like structures are maintained. Here we propose a synergistic approach which utilizes Förster resonance energy transfer and two types of ion mobility spectrometry (i.e., traveling wave and differential) to provide multiple constraints (i.e., shape and intramolecular distance) for structure-refinement of gas-phase ions. We add microsolvation calculations to assess the interaction sites and energies between the biomolecular ions and gaseous additives. This combined strategy is employed to distinguish conformers and understand the gas-phase structures of two isomeric α-helical peptides that might differ in helicity. Our work allows more stringent structural characterization of biologically relevant molecules (e.g., peptide drugs) and large biomolecular ions than using only a single structural methodology in the gas phase.
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Affiliation(s)
- Ri Wu
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
| | - Jonas B Metternich
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
| | - Anna S Kamenik
- Laboratorium für Physikalische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
| | - Prince Tiwari
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Forschungsstrasse 111, 5232, Villigen PSI, Switzerland
| | - Julian A Harrison
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
| | - Dennis Kessen
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
- University of Münster, MEET Battery Research Center, Corrensstrasse 46, 48149, Münster, Germany
| | - Hasan Akay
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
| | - Lukas R Benzenberg
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland
| | - T-W Dominic Chan
- Department of Chemistry, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Sereina Riniker
- Laboratorium für Physikalische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland.
| | - Renato Zenobi
- Laboratorium für Organische Chemie, D-CHAB, ETH Zürich, 8093, Zurich, Switzerland.
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5
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Sgouros AP, Revelas CJ, Lakkas AT, Theodorou DN. Solvation Free Energy of Dilute Grafted (Nano)Particles in Polymer Melts via the Self-Consistent Field Theory. J Phys Chem B 2022; 126:7454-7474. [DOI: 10.1021/acs.jpcb.2c05306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Aristotelis P. Sgouros
- School of Chemical Engineering, National Technical University of Athens (NTUA), GR-15780 Athens, Greece
| | - Constantinos J. Revelas
- School of Chemical Engineering, National Technical University of Athens (NTUA), GR-15780 Athens, Greece
| | - Apostolos T. Lakkas
- School of Chemical Engineering, National Technical University of Athens (NTUA), GR-15780 Athens, Greece
| | - Doros N. Theodorou
- School of Chemical Engineering, National Technical University of Athens (NTUA), GR-15780 Athens, Greece
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6
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Waibl F, Kraml J, Hoerschinger VJ, Hofer F, Kamenik AS, Fernández-Quintero ML, Liedl KR. Grid inhomogeneous solvation theory for cross-solvation in rigid solvents. J Chem Phys 2022; 156:204101. [PMID: 35649837 DOI: 10.1063/5.0087549] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Grid Inhomogeneous Solvation Theory (GIST) has proven useful to calculate localized thermodynamic properties of water around a solute. Numerous studies have leveraged this information to enhance structure-based binding predictions. We have recently extended GIST toward chloroform as a solvent to allow the prediction of passive membrane permeability. Here, we further generalize the GIST algorithm toward all solvents that can be modeled as rigid molecules. This restriction is inherent to the method and is already present in the inhomogeneous solvation theory. Here, we show that our approach can be applied to various solvent molecules by comparing the results of GIST simulations with thermodynamic integration (TI) calculations and experimental results. Additionally, we analyze and compare a matrix consisting of 100 entries of ten different solvent molecules solvated within each other. We find that the GIST results are highly correlated with TI calculations as well as experiments. For some solvents, we find Pearson correlations of up to 0.99 to the true entropy, while others are affected by the first-order approximation more strongly. The enthalpy-entropy splitting provided by GIST allows us to extend a recently published approach, which estimates higher order entropies by a linear scaling of the first-order entropy, to solvents other than water. Furthermore, we investigate the convergence of GIST in different solvents. We conclude that our extension to GIST reliably calculates localized thermodynamic properties for different solvents and thereby significantly extends the applicability of this widely used method.
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Affiliation(s)
- Franz Waibl
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
| | - Johannes Kraml
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
| | - Valentin J Hoerschinger
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
| | - Florian Hofer
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
| | - Anna S Kamenik
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
| | - Monica L Fernández-Quintero
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
| | - Klaus R Liedl
- Center for Molecular Biosciences Innsbruck, Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, Innsbruck, Austria
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7
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Waibl F, Kraml J, Fernández-Quintero ML, Loeffler JR, Liedl KR. Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt-water mixtures. J Comput Aided Mol Des 2022; 36:101-116. [PMID: 35031880 PMCID: PMC8907097 DOI: 10.1007/s10822-021-00429-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/28/2021] [Indexed: 12/03/2022]
Abstract
Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt-water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water-water and water-ion entropies contribute strongly. We show that the water-ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water-water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.
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Affiliation(s)
- Franz Waibl
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Johannes Kraml
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Monica L Fernández-Quintero
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Johannes R Loeffler
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Klaus R Liedl
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria.
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8
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Falcioni F, Kalayan J, Henchman RH. Energy-entropy prediction of octanol-water logP of SAMPL7 N-acyl sulfonamide bioisosters. J Comput Aided Mol Des 2021; 35:831-840. [PMID: 34244906 PMCID: PMC8295089 DOI: 10.1007/s10822-021-00401-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/17/2021] [Indexed: 12/23/2022]
Abstract
Partition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute.
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Affiliation(s)
- Fabio Falcioni
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
- School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
| | - Jas Kalayan
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK
- School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
| | - Richard H Henchman
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
- School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
- Sydney Medical School, The University of Sydney, Sydney, NSW, 2006, Australia.
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9
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Kamenik AS, Kraml J, Hofer F, Waibl F, Quoika PK, Kahler U, Schauperl M, Liedl KR. Macrocycle Cell Permeability Measured by Solvation Free Energies in Polar and Apolar Environments. J Chem Inf Model 2020; 60:3508-3517. [PMID: 32551643 PMCID: PMC7388155 DOI: 10.1021/acs.jcim.0c00280] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The relation of surface polarity and conformational preferences is decisive for cell permeability and thus bioavailability of macrocyclic drugs. Here, we employ grid inhomogeneous solvation theory (GIST) to calculate solvation free energies for a series of six macrocycles in water and chloroform as a measure of passive membrane permeability. We perform accelerated molecular dynamics simulations to capture a diverse structural ensemble in water and chloroform, allowing for a direct profiling of solvent-dependent conformational preferences. Subsequent GIST calculations facilitate a quantitative measure of solvent preference in the form of a transfer free energy, calculated from the ensemble-averaged solvation free energies in water and chloroform. Hence, the proposed method considers how the conformational diversity of macrocycles in polar and apolar solvents translates into transfer free energies. Following this strategy, we find a striking correlation of 0.92 between experimentally determined cell permeabilities and calculated transfer free energies. For the studied model systems, we find that the transfer free energy exceeds the purely water-based solvation free energies as a reliable estimate of cell permeability and that conformational sampling is imperative for a physically meaningful model. We thus recommend this purely physics-based approach as a computational tool to assess cell permeabilities of macrocyclic drug candidates.
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Affiliation(s)
- Anna S Kamenik
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Johannes Kraml
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Florian Hofer
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Franz Waibl
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Patrick K Quoika
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Ursula Kahler
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Michael Schauperl
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
| | - Klaus R Liedl
- Institute of General, Inorganic and Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80-82, Innsbruck A-6020 Austria
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