1
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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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2
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Chen L, Cruz A, Roe DR, Simmonett AC, Wickstrom L, Deng N, Kurtzman T. Thermodynamic Decomposition of Solvation Free Energies with Particle Mesh Ewald and Long-Range Lennard-Jones Interactions in Grid Inhomogeneous Solvation Theory. J Chem Theory Comput 2021; 17:2714-2724. [PMID: 33830762 DOI: 10.1021/acs.jctc.0c01185] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Grid Inhomogeneous Solvation Theory (GIST) maps out solvation thermodynamic properties on a fine meshed grid and provides a statistical mechanical formalism for thermodynamic end-state calculations. However, differences in how long-range nonbonded interactions are calculated in molecular dynamics engines and in the current implementation of GIST have prevented precise comparisons between free energies estimated using GIST and those from other free energy methods such as thermodynamic integration (TI). Here, we address this by presenting PME-GIST, a formalism by which particle mesh Ewald (PME)-based electrostatic energies and long-range Lennard-Jones (LJ) energies are decomposed and assigned to individual atoms and the corresponding voxels they occupy in a manner consistent with the GIST approach. PME-GIST yields potential energy calculations that are precisely consistent with modern simulation engines and performs these calculations at a dramatically faster speed than prior implementations. Here, we apply PME-GIST end-state analyses to 32 small molecules whose solvation free energies are close to evenly distributed from 2 kcal/mol to -17 kcal/mol and obtain solvation energies consistent with TI calculations (R2 = 0.99, mean unsigned difference 0.8 kcal/mol). We also estimate the entropy contribution from the second and higher order entropy terms that are truncated in GIST by the differences between entropies calculated in TI and GIST. With a simple correction for the high order entropy terms, PME-GIST obtains solvation free energies that are highly consistent with TI calculations (R2 = 0.99, mean unsigned difference = 0.4 kcal/mol) and experimental results (R2 = 0.88, mean unsigned difference = 1.4 kcal/mol). The precision of PME-GIST also enables us to show that the solvation free energy of small hydrophobic and hydrophilic molecules can be largely understood based on perturbations of the solvent in a region extending a few solvation shells from the solute. We have integrated PME-GIST into the open-source molecular dynamics analysis software CPPTRAJ.
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Affiliation(s)
- Lieyang Chen
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States
| | - Anthony Cruz
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Chemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States
| | - Daniel R Roe
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung and Blood Institute, Bethesda, Maryland 20892, United States
| | - Andrew C Simmonett
- Laboratory of Computational Biology, National Institutes of Health - National Heart, Lung and Blood Institute, Bethesda, Maryland 20892, United States
| | - Lauren Wickstrom
- Department of Science, Borough of Manhattan Community College, The City University of New York, New York, New York 10007, United States
| | - Nanjie Deng
- Department of Chemistry and Physical Sciences, Pace University, New York, New York 10038, United States
| | - Tom Kurtzman
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States.,Ph.D. Program in Chemistry, The Graduate Center of The City University of New York, New York, New York 10016, United States
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3
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Evans R, Hovan L, Tribello GA, Cossins BP, Estarellas C, Gervasio FL. Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies. J Chem Theory Comput 2020; 16:4641-4654. [PMID: 32427471 PMCID: PMC7467642 DOI: 10.1021/acs.jctc.0c00075] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on 18 chemically diverse ligands with a wide range of different binding affinities to a complex target; namely, human soluble epoxide hydrolase. The results suggest that metadynamics with a funnel-shaped restraint can be used to calculate, in a computationally affordable and relatively accurate way, the absolute binding free energy for small fragments. When used in combination with an optimal pathlike variable obtained using machine learning or with the Hamiltonian replica-exchange algorithm SWISH, this method can achieve reasonably accurate results for increasingly complex ligands, with a good balance of computational cost and speed. An additional benefit of using the combination of metadynamics and SWISH is that it also provides useful information about the role of water in the binding mechanism.
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Affiliation(s)
| | | | - Gareth A Tribello
- Atomistic Simulation Centre, Queen's University, Belfast BT7 1NN, United Kingdom
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4
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Mitusińska K, Raczyńska A, Bzówka M, Bagrowska W, Góra A. Applications of water molecules for analysis of macromolecule properties. Comput Struct Biotechnol J 2020; 18:355-365. [PMID: 32123557 PMCID: PMC7036622 DOI: 10.1016/j.csbj.2020.02.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 01/26/2020] [Accepted: 02/01/2020] [Indexed: 01/12/2023] Open
Abstract
Water molecules maintain proteins' structures, functions, stabilities and dynamics. They can occupy certain positions or pass quickly via a protein's interior. Regardless of their behaviour, water molecules can be used for the analysis of proteins' structural features and biochemical properties. Here, we present a list of several software programs that use the information provided by water molecules to: i) analyse protein structures and provide the optimal positions of water molecules for protein hydration, ii) identify high-occupancy water sites in order to analyse ligand binding modes, and iii) detect and describe tunnels and cavities. The analysis of water molecules' distribution and trajectories sheds a light on proteins' interactions with small molecules, on the dynamics of tunnels and cavities, on protein composition and also on the functionality, transportation network and location of functionally relevant residues. Finally, the correct placement of water molecules in protein crystal structures can significantly improve the reliability of molecular dynamics simulations.
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Affiliation(s)
| | | | | | | | - Artur Góra
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, Krzywoustego 8, Gliwice, Poland
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5
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Pérez-Conesa S, Piaggi PM, Parrinello M. A local fingerprint for hydrophobicity and hydrophilicity: From methane to peptides. J Chem Phys 2019; 150:204103. [PMID: 31153166 DOI: 10.1063/1.5088418] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
An important characteristic that determines the behavior of a solute in water is whether it is hydrophobic or hydrophilic. The traditional classification is based on chemical experience and heuristics. However, this does not reveal how the local environment modulates this important property. We present a local fingerprint for hydrophobicity and hydrophilicity inspired by the two body contribution to the entropy. This fingerprint is an inexpensive, quantitative, and physically meaningful way of studying hydrophilicity and hydrophobicity that only requires as input the water-solute radial distribution functions. We apply our fingerprint to octanol, benzene, and 20 proteinogenic amino acids. Our measure of hydrophilicity is coherent with chemical experience, and moreover, it also shows how the character of an atom can change as its environment is changed. Finally, we use the fingerprint as a collective variable in a funnel metadynamics simulation of a host-guest system. The fingerprint serves as a desolvation collective variable that enhances transitions between the bound and unbound states.
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Affiliation(s)
- S Pérez-Conesa
- Department of Physical Chemistry, University of Seville, 41012 Seville, Spain
| | - Pablo M Piaggi
- Theory and Simulation of Materials (THEOS), École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Michele Parrinello
- Facoltà di Informatica, Istituto di Scienze Computazionali, and National Center for Computational Design and Discovery of Novel Materials (MARVEL), Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900 Lugano, Switzerland
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6
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Irwin BWJ, Vukovic S, Payne MC, Huggins DJ. Large-Scale Study of Hydration Environments through Hydration Sites. J Phys Chem B 2019; 123:4220-4229. [PMID: 31025866 DOI: 10.1021/acs.jpcb.9b02490] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Hydration sites are locations of interest to water and they can be used to classify the behavior of water around chemical motifs commonly found on the surface of proteins. Inhomogeneous fluid solvation theory (IFST) is a method for calculating hydration free-energy changes from molecular dynamics (MD) trajectories. In this paper, hydration sites are identified from MD simulations of 380 diverse protein structures. The hydration free energies of the hydration sites are calculated using IFST and distributions of these free-energy changes are analyzed. The results show that for some hydration sites near features conventionally regarded as attractive to water, such as hydrogen bond donors, the water molecules are actually relatively weakly bound and are easily displaced. We also construct plots of the spatial density of hydration sites with high, medium, and low hydration free-energy changes which represent weakly and strongly bound hydration sites. It is found that these plots show consistent features around common polar amino acids for all of the proteins studied.
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Affiliation(s)
- Benedict W J Irwin
- Theory of Condensed Matter Group, Cavendish Laboratory , University of Cambridge , 19 J J Thomson Avenue , Cambridge CB3 0HE , U.K
| | - Sinisa Vukovic
- Theory of Condensed Matter Group, Cavendish Laboratory , University of Cambridge , 19 J J Thomson Avenue , Cambridge CB3 0HE , U.K
| | - Michael C Payne
- Theory of Condensed Matter Group, Cavendish Laboratory , University of Cambridge , 19 J J Thomson Avenue , Cambridge CB3 0HE , U.K
| | - David J Huggins
- Theory of Condensed Matter Group, Cavendish Laboratory , University of Cambridge , 19 J J Thomson Avenue , Cambridge CB3 0HE , U.K.,Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge CB2 1EW , U.K.,Department of Physiology and Biophysics , Weill Cornell Medical College , 1300 York Avenue , New York , New York 10065 , United States
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7
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Irwin BWJ, Huggins DJ. Estimating Atomic Contributions to Hydration and Binding Using Free Energy Perturbation. J Chem Theory Comput 2018; 14:3218-3227. [PMID: 29712434 DOI: 10.1021/acs.jctc.8b00027] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
We present a general method called atom-wise free energy perturbation (AFEP), which extends a conventional molecular dynamics free energy perturbation (FEP) simulation to give the contribution to a free energy change from each atom. AFEP is derived from an expansion of the Zwanzig equation used in the exponential averaging method by defining that the system total energy can be partitioned into contributions from each atom. A partitioning method is assumed and used to group terms in the expansion to correspond to individual atoms. AFEP is applied to six example free energy changes to demonstrate the method. Firstly, the hydration free energies of methane, methanol, methylamine, methanethiol, and caffeine in water. AFEP highlights the atoms in the molecules that interact favorably or unfavorably with water. Finally AFEP is applied to the binding free energy of human immunodeficiency virus type 1 protease to lopinavir, and AFEP reveals the contribution of each atom to the binding free energy, indicating candidate areas of the molecule to improve to produce a more strongly binding inhibitor. FEP gives a single value for the free energy change and is already a very useful method. AFEP gives a free energy change for each "part" of the system being simulated, where part can mean individual atoms, chemical groups, amino acids, or larger partitions depending on what the user is trying to measure. This method should have various applications in molecular dynamics studies of physical, chemical, or biochemical phenomena, specifically in the field of computational drug discovery.
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Affiliation(s)
- Benedict W J Irwin
- Theory of Condensed Matter Group, Cavendish Laboratory , University of Cambridge , 19 J J Thomson Avenue , Cambridge CB3 0HE , United Kingdom
| | - David J Huggins
- Theory of Condensed Matter Group, Cavendish Laboratory , University of Cambridge , 19 J J Thomson Avenue , Cambridge CB3 0HE , United Kingdom.,Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge CB2 1EW , United Kingdom
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8
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Bucher D, Stouten P, Triballeau N. Shedding Light on Important Waters for Drug Design: Simulations versus Grid-Based Methods. J Chem Inf Model 2018; 58:692-699. [DOI: 10.1021/acs.jcim.7b00642] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Denis Bucher
- Galapagos SASU, 102 Avenue Gaston Roussel, 93230 Romainville, France
| | - Pieter Stouten
- Galapagos NV, Generaal De Wittelaan L11 A3, 2800 Mechelen, Belgium
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9
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Cui D, Zhang BW, Matubayasi N, Levy RM. The Role of Interfacial Water in Protein-Ligand Binding: Insights from the Indirect Solvent Mediated Potential of Mean Force. J Chem Theory Comput 2018; 14:512-526. [PMID: 29262255 DOI: 10.1021/acs.jctc.7b01076] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Classical density functional theory (DFT) can be used to relate the thermodynamic properties of solutions to the indirect solvent mediated part of the solute-solvent potential of mean force (PMF). Standard, but powerful numerical methods can be used to estimate the solute-solvent PMF from which the indirect part can be extracted. In this work we show how knowledge of the direct and indirect parts of the solute-solvent PMF for water at the interface of a protein receptor can be used to gain insights about how to design tighter binding ligands. As we show, the indirect part of the solute-solvent PMF is equal to the sum of the 1-body (energy + entropy) terms in the inhomogeneous solvation theory (IST) expansion of the solvation free energy. To illustrate the effect of displacing interfacial water molecules with particular direct/indirect PMF signatures on the binding of ligands, we carry out simulations of protein binding with several pairs of congeneric ligands. We show that interfacial water locations that contribute favorably or unfavorably at the 1-body level (energy + entropy) to the solvation free energy of the solute can be targeted as part of the ligand design process. Water locations where the indirect PMF is larger in magnitude provide better targets for displacement when adding a functional group to a ligand core.
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Affiliation(s)
- Di Cui
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Bin W Zhang
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Nobuyuki Matubayasi
- Division of Chemical Engineering, Graduate School of Engineering Science, Osaka University , Toyonaka, Osaka 560-8531, Japan.,Elements Strategy Initiative for Catalysts and Batteries, Kyoto University , Katsura, Kyoto 615-8520, Japan
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States
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10
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Haider K, Cruz A, Ramsey S, Gilson MK, Kurtzman T. Solvation Structure and Thermodynamic Mapping (SSTMap): An Open-Source, Flexible Package for the Analysis of Water in Molecular Dynamics Trajectories. J Chem Theory Comput 2018; 14:418-425. [PMID: 29161510 PMCID: PMC5760325 DOI: 10.1021/acs.jctc.7b00592] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We have developed SSTMap, a software package for mapping structural and thermodynamic water properties in molecular dynamics trajectories. The package introduces automated analysis and mapping of local measures of frustration and enhancement of water structure. The thermodynamic calculations are based on Inhomogeneous Fluid Solvation Theory (IST), which is implemented using both site-based and grid-based approaches. The package also extends the applicability of solvation analysis calculations to multiple molecular dynamics (MD) simulation programs by using existing cross-platform tools for parsing MD parameter and trajectory files. SSTMap is implemented in Python and contains both command-line tools and a Python module to facilitate flexibility in setting up calculations and for automated generation of large data sets involving analysis of multiple solutes. Output is generated in formats compatible with popular Python data science packages. This tool will be used by the molecular modeling community for computational analysis of water in problems of biophysical interest such as ligand binding and protein function.
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Affiliation(s)
- Kamran Haider
- Department of Physics, City College of New York, The City University of New York, 160 Convent Ave, New York, NY 10031
| | - Anthony Cruz
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York, NY 10468
- Ph.D. Program in Chemistry, The Graduate Center of The City University of New York, 365 Fifth Avenue, New York, New York, 10016, United States
| | - Steven Ramsey
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York, NY 10468
- Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York, 365 Fifth Avenue, New York, New York, 10016, United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, California, CA, 92093-0736
| | - Tom Kurtzman
- Department of Chemistry, Lehman College, The City University of New York, 250 Bedford Park Boulevard West, Bronx, New York, NY 10468
- Ph.D. Program in Chemistry, The Graduate Center of The City University of New York, 365 Fifth Avenue, New York, New York, 10016, United States
- Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York, 365 Fifth Avenue, New York, New York, 10016, United States
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11
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Güssregen S, Matter H, Hessler G, Lionta E, Heil J, Kast SM. Thermodynamic Characterization of Hydration Sites from Integral Equation-Derived Free Energy Densities: Application to Protein Binding Sites and Ligand Series. J Chem Inf Model 2017; 57:1652-1666. [DOI: 10.1021/acs.jcim.6b00765] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Stefan Güssregen
- R&D, IDD, Structural Design and Informatics, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Building G877, 65926 Frankfurt am Main, Germany
| | - Hans Matter
- R&D, IDD, Structural Design and Informatics, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Building G877, 65926 Frankfurt am Main, Germany
| | - Gerhard Hessler
- R&D, IDD, Structural Design and Informatics, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Building G877, 65926 Frankfurt am Main, Germany
| | - Evanthia Lionta
- R&D, IDD, Structural Design and Informatics, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Building G877, 65926 Frankfurt am Main, Germany
| | - Jochen Heil
- Physikalische
Chemie III, Technische Universität Dortmund, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany
| | - Stefan M. Kast
- Physikalische
Chemie III, Technische Universität Dortmund, Otto-Hahn-Straße 4a, 44227 Dortmund, Germany
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12
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Abstract
Evaluating solvation entropies directly and combining with direct energy calculations is one way of calculating free energies of solvation and is used by Inhomogeneous Fluid Solvation Theory (IFST). The configurational entropy of a fluid is a function of the interatomic correlations and can thus be expressed in terms of correlation functions. The entropies in this work are directly calculated from a truncated series of integrals over these correlation functions. Many studies truncate all terms higher than the solvent-solute correlations. This study includes an additional solvent-solvent correlation term and assesses the associated free energy when IFST is applied to a fixed Lennard-Jones particle solvated in neon. The strength of the central potential is varied to imitate larger solutes. Average free energy estimates with both levels of IFST are able to reproduce the estimate made using the Free energy Perturbation (FEP) to within 0.16 kcal/mol. We find that the signal from the solvent-solvent correlations is very weak. Our conclusion is that for monatomic fluids simulated by pairwise classical potentials the correction term is relatively small in magnitude. This study shows it is possible to reproduce the free energy from a path based method like FEP, by only considering the endpoints of the path. This method can be directly applied to more complex solutes which break the spherical symmetry of this study.
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Affiliation(s)
- Benedict W J Irwin
- Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, 19 J J Thomson Avenue, Cambridge CB3 0HE, United Kingdom
| | - David J Huggins
- Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, 19 J J Thomson Avenue, Cambridge CB3 0HE, United Kingdom
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13
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Levy RM, Cui D, Zhang BW, Matubayasi N. Relationship between Solvation Thermodynamics from IST and DFT Perspectives. J Phys Chem B 2017; 121:3825-3841. [PMID: 28186751 DOI: 10.1021/acs.jpcb.6b12889] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Inhomogeneous solvation theory (IST) and classical density functional theory (DFT) each provide a framework for relating distribution functions of solutions to their thermodynamic properties. As reviewed in this work, both IST and DFT can be formulated in a way that use two "end point" simulations, one of the pure solvent and the other of the solution, to determine the solute chemical potential and other thermodynamic properties of the solution and of subvolumes in regions local to the solute containing hydrating waters. In contrast to IST, where expressions for the excess energy and entropy of solution are the object of analysis, in the DFT end point formulation of the problem, the solute-solvent potential of mean force (PMF) plays a central role. The indirect part of the PMF corresponds to the lowest order (1-body) truncation of the IST expression. Because the PMF is a free energy function, powerful numerical methods can be used to estimate it. We show that the DFT expressions for the solute excess chemical potential can be written in a form which is local, involving integrals only over regions proximate to the solute. The DFT end point route to estimating solvation free energies provides an alternative path to that of IST for analyzing solvation effects on molecular recognition and conformational changes in solution, which can lead to new insights. In order to illustrate the kind of information that is contained in the solute-solvent PMF, we have carried out simulations of β-cyclodextrin in water. This solute is a well studied "host" molecule to which "guest" molecules bind; host-guest systems serve as models for molecular recognition. We illustrate the range of values the direct and indirect parts of the solute-solvent PMF can have as a water molecule is brought to the interface of β-cyclodextrin from the bulk; we discuss the "competition" between these two terms, and the role it plays in molecular recognition.
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Affiliation(s)
- Ronald M Levy
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Di Cui
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Bin W Zhang
- Center for Biophysics and Computational Biology, Department of Chemistry, and Institute for Computational Molecular Science, Temple University , Philadelphia, Pennsylvania 19122, United States
| | - Nobuyuki Matubayasi
- Division of Chemical Engineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531, Japan and Elements Strategy Initiative for Catalysts and Batteries, Kyoto University , Katsura, Kyoto 615-8520, Japan
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14
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15
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Huggins DJ. Studying the role of cooperative hydration in stabilizing folded protein states. J Struct Biol 2016; 196:394-406. [PMID: 27633532 PMCID: PMC5131609 DOI: 10.1016/j.jsb.2016.09.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Revised: 09/03/2016] [Accepted: 09/07/2016] [Indexed: 01/19/2023]
Abstract
Understanding and modelling protein folding remains a key scientific and engineering challenge. Two key questions in protein folding are (1) why many proteins adopt a folded state and (2) how these proteins transition from the random coil ensemble to a folded state. In this paper we employ molecular dynamics simulations to address the first of these questions. Computational methods are well-placed to address this issue due to their ability to analyze systems at atomic-level resolution. Traditionally, the stability of folded proteins has been ascribed to the balance of two types of intermolecular interactions: hydrogen-bonding interactions and hydrophobic contacts. In this study, we explore a third type of intermolecular interaction: cooperative hydration of protein surface residues. To achieve this, we consider multiple independent simulations of the villin headpiece domain to quantify the contributions of different interactions to the energy of the native and fully extended states. In addition, we consider whether these findings are robust with respect to the protein forcefield, the water model, and the presence of salt. In all cases, we identify many cooperatively hydrated interactions that are transient but energetically favor the native state. Whilst further work on additional protein structures, forcefields, and water models is necessary, these results suggest a role for cooperative hydration in protein folding that should be explored further. Rational design of cooperative hydration on the protein surface could be a viable strategy for increasing protein stability.
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Affiliation(s)
- David J Huggins
- Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, 19 J J Thomson Avenue, Cambridge CB3 0HE, United Kingdom; Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom.
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16
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Vukovic S, Brennan PE, Huggins DJ. Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2016; 28:344007. [PMID: 27367338 DOI: 10.1088/0953-8984/28/34/344007] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.
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Affiliation(s)
- Sinisa Vukovic
- Department of Physics, Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge, CB3 0HE, UK
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17
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Schauperl M, Podewitz M, Waldner BJ, Liedl KR. Enthalpic and Entropic Contributions to Hydrophobicity. J Chem Theory Comput 2016; 12:4600-10. [PMID: 27442443 PMCID: PMC5024328 DOI: 10.1021/acs.jctc.6b00422] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Hydrophobic hydration plays a key role in a vast variety of biological processes, ranging from the formation of cells to protein folding and ligand binding. Hydrophobicity scales simplify the complex process of hydration by assigning a value describing the averaged hydrophobic character to each amino acid. Previously published scales were not able to calculate the enthalpic and entropic contributions to the hydrophobicity directly. We present a new method, based on Molecular Dynamics simulations and Grid Inhomogeneous Solvation Theory, that calculates hydrophobicity from enthalpic and entropic contributions. Instead of deriving these quantities from the temperature dependence of the free energy of hydration or as residual of the free energy and the enthalpy, we directly obtain these values from the phase space occupied by water molecules. Additionally, our method is able to identify regions with specific enthalpic and entropic properties, allowing to identify so-called "unhappy water" molecules, which are characterized by weak enthalpic interactions and unfavorable entropic constraints.
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Affiliation(s)
- Michael Schauperl
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck , Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Maren Podewitz
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck , Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Birgit J Waldner
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck , Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
| | - Klaus R Liedl
- Institute of General, Inorganic and Theoretical Chemistry, and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck , Innrain 80-82, A-6020 Innsbruck, Tyrol, Austria
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18
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Deng N, Zhang BW, Levy RM. Connecting free energy surfaces in implicit and explicit solvent: an efficient method to compute conformational and solvation free energies. J Chem Theory Comput 2016; 11:2868-78. [PMID: 26236174 DOI: 10.1021/acs.jctc.5b00264] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions, and protein–ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ∼3 kcal/mol at only ∼8% of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the implicit/explicit thermodynamic cycle.
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Affiliation(s)
- Nanjie Deng
- Center for Biophysics & Computational Biology and Institute for Computational Molecular Sciences Temple University, Philadelphia, Pennsylvania 19122, United States
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19
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Haider K, Wickstrom L, Ramsey S, Gilson MK, Kurtzman T. Enthalpic Breakdown of Water Structure on Protein Active-Site Surfaces. J Phys Chem B 2016; 120:8743-56. [PMID: 27169482 DOI: 10.1021/acs.jpcb.6b01094] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The principles underlying water reorganization around simple nonpolar solutes are well understood and provide the framework for the classical hydrophobic effect, whereby water molecules structure themselves around solutes so that they maintain favorable energetic contacts with both the solute and the other water molecules. However, for certain solute surface topographies, water molecules, due to their geometry and size, are unable to simultaneously maintain favorable energetic contacts with both the surface and neighboring water molecules. In this study, we analyze the solvation of ligand-binding sites for six structurally diverse proteins using hydration site analysis and measures of local water structure, in order to identify surfaces at which water molecules are unable to structure themselves in a way that maintains favorable enthalpy relative to bulk water. These surfaces are characterized by a high degree of enclosure, weak solute-water interactions, and surface constraints that induce unfavorable pair interactions between neighboring water molecules. Additionally, we find that the solvation of charged side chains in an active site generally results in favorable enthalpy but can also lead to pair interactions between neighboring water molecules that are significantly unfavorable relative to bulk water. We find that frustrated local structure can occur not only in apolar and weakly polar pockets, where overall enthalpy tends to be unfavorable, but also in charged pockets, where overall water enthalpy tends to be favorable. The characterization of local water structure in these terms may prove useful for evaluating the displacement of water from diverse protein active-site environments.
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Affiliation(s)
- Kamran Haider
- Department of Chemistry, Lehman College, The City University of New York , 250 Bedford Park Boulevard West, Bronx, New York 10468, United States
| | - Lauren Wickstrom
- Borough of Manhattan Community College, Department of Science, The City University of New York , 199 Chambers Street, New York, New York 10007, United States
| | - Steven Ramsey
- Department of Chemistry, Lehman College, The City University of New York , 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York , 365 Fifth Avenue, New York, New York 10016, United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093-0736, United States
| | - Tom Kurtzman
- Department of Chemistry, Lehman College, The City University of New York , 250 Bedford Park Boulevard West, Bronx, New York 10468, United States.,Ph.D. Program in Biochemistry, The Graduate Center of The City University of New York , 365 Fifth Avenue, New York, New York 10016, United States.,Ph.D. Program in Chemistry, The Graduate Center of The City University of New York , 365 Fifth Avenue, New York, New York 10016, United States
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20
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Hydration of proteins and nucleic acids: Advances in experiment and theory. A review. Biochim Biophys Acta Gen Subj 2016; 1860:1821-35. [PMID: 27241846 DOI: 10.1016/j.bbagen.2016.05.036] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 05/20/2016] [Accepted: 05/26/2016] [Indexed: 11/21/2022]
Abstract
BACKGROUND Most biological processes involve water, and the interactions of biomolecules with water affect their structure, function and dynamics. SCOPE OF REVIEW This review summarizes the current knowledge of protein and nucleic acid interactions with water, with a special focus on the biomolecular hydration layer. Recent developments in both experimental and computational methods that can be applied to the study of hydration structure and dynamics are reviewed, including software tools for the prediction and characterization of hydration layer properties. MAJOR CONCLUSIONS In the last decade, important advances have been made in our understanding of the factors that determine how biomolecules and their aqueous environment influence each other. Both experimental and computational methods contributed to the gradually emerging consensus picture of biomolecular hydration. GENERAL SIGNIFICANCE An improved knowledge of the structural and thermodynamic properties of the hydration layer will enable a detailed understanding of the various biological processes in which it is involved, with implications for a wide range of applications, including protein-structure prediction and structure-based drug design.
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21
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Huggins DJ. Estimating Translational and Orientational Entropies Using the k-Nearest Neighbors Algorithm. J Chem Theory Comput 2015; 10:3617-25. [PMID: 26588506 DOI: 10.1021/ct500415g] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Inhomogeneous fluid solvation theory (IFST) and free energy perturbation (FEP) calculations were performed for a set of 20 solutes to compute the hydration free energies. We identify the weakness of histogram methods in computing the IFST hydration entropy by showing that previously employed histogram methods overestimate the translational and orientational entropies and thus underestimate their contribution to the free energy by a significant amount. Conversely, we demonstrate the accuracy of the k-nearest neighbors (KNN) algorithm in computing these translational and orientational entropies. Implementing the KNN algorithm within the IFST framework produces a powerful method that can be used to calculate free-energy changes for large perturbations. We introduce a new KNN approach to compute the total solute-water entropy with six degrees of freedom, as well as the translational and orientational contributions. However, results suggest that both the solute-water and water-water entropy terms are significant and must be included. When they are combined, the IFST and FEP hydration free energies are highly correlated, with an R(2) of 0.999 and a mean unsigned difference of 0.9 kcal/mol. IFST predictions are also highly correlated with experimental hydration free energies, with an R(2) of 0.997 and a mean unsigned error of 1.2 kcal/mol. In summary, the KNN algorithm is shown to yield accurate estimates of the combined translational-orientational entropy and the novel approach of combining distance metrics that is developed here could be extended to provide a powerful method for entropy estimation in numerous contexts.
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Affiliation(s)
- David J Huggins
- Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge , 19 J J Thomson Avenue, Cambridge CB3 0HE, United Kingdom
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22
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Nguyen CN, Kurtzman T, Gilson MK. Spatial Decomposition of Translational Water-Water Correlation Entropy in Binding Pockets. J Chem Theory Comput 2015; 12:414-29. [PMID: 26636620 PMCID: PMC4819442 DOI: 10.1021/acs.jctc.5b00939] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
A number
of computational tools available today compute the thermodynamic properties
of water at surfaces and in binding pockets by using inhomogeneous
solvation theory (IST) to analyze explicit-solvent simulations. Such
methods enable qualitative spatial mappings of both energy and entropy
around a solute of interest and can also be applied quantitatively.
However, the entropy estimates of existing methods have, to date,
been almost entirely limited to the first-order terms in the IST’s
entropy expansion. These first-order terms account for localization
and orientation of water molecules in the field of the solute but
not for the modification of water–water correlations by the
solute. Here, we present an extension of the Grid Inhomogeneous Solvation
Theory (GIST) approach which accounts for water–water translational
correlations. The method involves rewriting the two-point density
of water in terms of a conditional density and utilizes the efficient
nearest-neighbor entropy estimation approach. Spatial maps of this
second order term, for water in and around the synthetic host cucurbit[7]uril
and in the binding pocket of the enzyme Factor Xa, reveal mainly negative
contributions, indicating solute-induced water–water correlations
relative to bulk water; particularly strong signals are obtained for
sites at the entrances of cavities or pockets. This second-order term
thus enters with the same, negative, sign as the first order translational
and orientational terms. Numerical and convergence properties of the
methodology are examined.
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Affiliation(s)
- Crystal N Nguyen
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093-0736, United States
| | - Tom Kurtzman
- Department of Chemistry, Lehman College, The City University of New York , 250 Bedford Park Blvd. West, Bronx, New York, New York 10468, United States.,Ph.D. Program in Chemistry, The Graduate Center of The City University of New York , New York 10016, United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093-0736, United States
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23
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Chung KC, Park H. Accuracy enhancement in the estimation of molecular hydration free energies by implementing the intramolecular hydrogen bond effects. J Cheminform 2015; 7:57. [PMID: 26613005 PMCID: PMC4660792 DOI: 10.1186/s13321-015-0106-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Accepted: 11/12/2015] [Indexed: 11/10/2022] Open
Abstract
Background The formation of intramolecular hydrogen bonds (IHBs) may induce the remarkable changes in molecular physicochemical properties. Within the framework of the extended solvent-contact model, we investigate the effect of implementing the IHB interactions on the accuracy in estimating the molecular hydration free energies. Results The performances of hydration free energy functions including and excluding the IHB parameters are compared using the molecules distributed for SAMPL4 blind prediction challenge and those in Free Solvation Database (FSD). The calculated hydration free energies with IHB effects are found to be in considerably better agreement with the experimental data than those without them. For example, the root mean square error of the estimation decreases from 2.56 to 1.66 and from 1.73 to 1.54 kcal/mol for SAMPL4 and FSD molecules, respectively, due to the extension of atomic parameter space to cope with IHBs. Conclusions These improvements are made possible by reducing the overestimation of attractive interactions between water and the solute molecules involving IHBs. The modified hydration free energy function is thus anticipated to be useful for estimating the desolvation cost for various organic molecules. Electronic supplementary material The online version of this article (doi:10.1186/s13321-015-0106-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Kee-Choo Chung
- Department of Bioscience and Biotechnology, Sejong University, 209 Neungdong-ro, Kwangjin-gu, Seoul, 143-747 Republic of Korea
| | - Hwangseo Park
- Department of Bioscience and Biotechnology, Sejong University, 209 Neungdong-ro, Kwangjin-gu, Seoul, 143-747 Republic of Korea
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24
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Quantifying the entropy of binding for water molecules in protein cavities by computing correlations. Biophys J 2015; 108:928-936. [PMID: 25692597 PMCID: PMC4336375 DOI: 10.1016/j.bpj.2014.12.035] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Revised: 12/16/2014] [Accepted: 12/17/2014] [Indexed: 11/20/2022] Open
Abstract
Protein structural analysis demonstrates that water molecules are commonly found in the internal cavities of proteins. Analysis of experimental data on the entropies of inorganic crystals suggests that the entropic cost of transferring such a water molecule to a protein cavity will not typically be greater than 7.0 cal/mol/K per water molecule, corresponding to a contribution of approximately +2.0 kcal/mol to the free energy. In this study, we employ the statistical mechanical method of inhomogeneous fluid solvation theory to quantify the enthalpic and entropic contributions of individual water molecules in 19 protein cavities across five different proteins. We utilize information theory to develop a rigorous estimate of the total two-particle entropy, yielding a complete framework to calculate hydration free energies. We show that predictions from inhomogeneous fluid solvation theory are in excellent agreement with predictions from free energy perturbation (FEP) and that these predictions are consistent with experimental estimates. However, the results suggest that water molecules in protein cavities containing charged residues may be subject to entropy changes that contribute more than +2.0 kcal/mol to the free energy. In all cases, these unfavorable entropy changes are predicted to be dominated by highly favorable enthalpy changes. These findings are relevant to the study of bridging water molecules at protein-protein interfaces as well as in complexes with cognate ligands and small-molecule inhibitors.
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25
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López ED, Arcon JP, Gauto DF, Petruk AA, Modenutti CP, Dumas VG, Marti MA, Turjanski AG. WATCLUST: a tool for improving the design of drugs based on protein-water interactions. Bioinformatics 2015. [PMID: 26198103 DOI: 10.1093/bioinformatics/btv411] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Water molecules are key players for protein folding and function. On the protein surface, water is not placed randomly, but display instead a particular structure evidenced by the presence of specific water sites (WS). These WS can be derived and characterized using explicit water Molecular Dynamics simulations, providing useful information for ligand binding prediction and design. Here we present WATCLUST, a WS determination and analysis tool running on the VMD platform. The tool also allows direct transfer of the WS information to Autodock program to perform biased docking. AVAILABILITY AND IMPLEMENTATION The WATCLUST plugin and documentation are freely available at http://sbg.qb.fcen.uba.ar/watclust/. CONTACT marcelo@qi.fcen.uba.ar, adrian@qi.fcen.uba.ar.
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Affiliation(s)
- Elias D López
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina and
| | - Juan Pablo Arcon
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina and INQUIMAE-CONICET, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Diego F Gauto
- INQUIMAE-CONICET, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Ariel A Petruk
- INQUIMAE-CONICET, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Carlos P Modenutti
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina and
| | - Victoria G Dumas
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina and
| | - Marcelo A Marti
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina and INQUIMAE-CONICET, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina
| | - Adrian G Turjanski
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina and INQUIMAE-CONICET, Ciudad Universitaria, Pabellón II, C1428EHA, Ciudad de Buenos Aires, Argentina
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26
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Laraia L, McKenzie G, Spring DR, Venkitaraman AR, Huggins DJ. Overcoming Chemical, Biological, and Computational Challenges in the Development of Inhibitors Targeting Protein-Protein Interactions. CHEMISTRY & BIOLOGY 2015; 22:689-703. [PMID: 26091166 PMCID: PMC4518475 DOI: 10.1016/j.chembiol.2015.04.019] [Citation(s) in RCA: 115] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Revised: 04/01/2015] [Accepted: 04/08/2015] [Indexed: 01/19/2023]
Abstract
Protein-protein interactions (PPIs) underlie the majority of biological processes, signaling, and disease. Approaches to modulate PPIs with small molecules have therefore attracted increasing interest over the past decade. However, there are a number of challenges inherent in developing small-molecule PPI inhibitors that have prevented these approaches from reaching their full potential. From target validation to small-molecule screening and lead optimization, identifying therapeutically relevant PPIs that can be successfully modulated by small molecules is not a simple task. Following the recent review by Arkin et al., which summarized the lessons learnt from prior successes, we focus in this article on the specific challenges of developing PPI inhibitors and detail the recent advances in chemistry, biology, and computation that facilitate overcoming them. We conclude by providing a perspective on the field and outlining four innovations that we see as key enabling steps for successful development of small-molecule inhibitors targeting PPIs.
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Affiliation(s)
- Luca Laraia
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; Medical Research Council Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Hills Road, Cambridge CB2 0XZ, UK
| | - Grahame McKenzie
- Medical Research Council Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Hills Road, Cambridge CB2 0XZ, UK
| | - David R Spring
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
| | - Ashok R Venkitaraman
- Medical Research Council Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Hills Road, Cambridge CB2 0XZ, UK
| | - David J Huggins
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; Medical Research Council Cancer Unit, University of Cambridge, Hutchison/MRC Research Centre, Hills Road, Cambridge CB2 0XZ, UK; Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0HE, UK.
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27
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Vincent MA, Hillier IH. Accurate Prediction of Adsorption Energies on Graphene, Using a Dispersion-Corrected Semiempirical Method Including Solvation. J Chem Inf Model 2014; 54:2255-60. [DOI: 10.1021/ci5003729] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Mark A. Vincent
- School of Chemistry, University of Manchester, Manchester M13 9PL, United Kingdom
| | - Ian H. Hillier
- School of Chemistry, University of Manchester, Manchester M13 9PL, United Kingdom
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28
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Sun H, Zhao L, Peng S, Huang N. Incorporating replacement free energy of binding-site waters in molecular docking. Proteins 2014; 82:1765-76. [DOI: 10.1002/prot.24530] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2013] [Revised: 01/17/2014] [Accepted: 01/28/2014] [Indexed: 12/24/2022]
Affiliation(s)
- Hanzi Sun
- College of Life Sciences; Beijing Normal University; Beijing 100875 China
- National Institute of Biological Sciences, Beijing, Zhongguancun Life Science Park; Beijing 102206 China
| | - Lifeng Zhao
- National Institute of Biological Sciences, Beijing, Zhongguancun Life Science Park; Beijing 102206 China
| | - Shiming Peng
- National Institute of Biological Sciences, Beijing, Zhongguancun Life Science Park; Beijing 102206 China
| | - Niu Huang
- College of Life Sciences; Beijing Normal University; Beijing 100875 China
- National Institute of Biological Sciences, Beijing, Zhongguancun Life Science Park; Beijing 102206 China
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29
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Huggins DJ. Comparing distance metrics for rotation using the k-nearest neighbors algorithm for entropy estimation. J Comput Chem 2014; 35:377-85. [PMID: 24311273 PMCID: PMC4238811 DOI: 10.1002/jcc.23504] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2013] [Revised: 11/08/2013] [Accepted: 11/14/2013] [Indexed: 01/17/2023]
Abstract
Distance metrics facilitate a number of methods for statistical analysis. For statistical mechanical applications, it is useful to be able to compute the distance between two different orientations of a molecule. However, a number of distance metrics for rotation have been employed, and in this study, we consider different distance metrics and their utility in entropy estimation using the k-nearest neighbors (KNN) algorithm. This approach shows a number of advantages over entropy estimation using a histogram method, and the different approaches are assessed using uniform randomly generated data, biased randomly generated data, and data from a molecular dynamics (MD) simulation of bulk water. The results identify quaternion metrics as superior to a metric based on the Euler angles. However, it is demonstrated that samples from MD simulation must be independent for effective use of the KNN algorithm and this finding impacts any application to time series data.
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Affiliation(s)
- David J Huggins
- Theory of Condensed Matter Group, University of Cambridge, Cavendish Laboratory19 J J Thomson Avenue, Cambridge, CB3 0HE, United Kingdom
- Cambridge Molecular Therapeutics Programme, University of Cambridge, Hutchison/MRC Research CentreHills Road, Cambridge, CB2 0XZ, United Kingdom
- Department of Chemistry, University of CambridgeLensfield Road, Cambridge, UK CB2 1EW, United Kingdom
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30
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Gerogiokas G, Calabro G, Henchman RH, Southey MWY, Law RJ, Michel J. Prediction of Small Molecule Hydration Thermodynamics with Grid Cell Theory. J Chem Theory Comput 2013; 10:35-48. [PMID: 26579889 DOI: 10.1021/ct400783h] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
An efficient methodology has been developed to quantify water energetics by analysis of explicit solvent molecular simulations of organic and biomolecular systems. The approach, grid cell theory (GCT), relies on a discretization of the cell theory methodology on a three-dimensional grid to spatially resolve the density, enthalpy, and entropy of water molecules in the vicinity of solute(s) of interest. Entropies of hydration are found to converge more efficiently than enthalpies of hydration. GCT predictions of free energies of hydration on a data set of small molecules are strongly correlated with thermodynamic integration predictions. Agreement with the experiment is comparable for both approaches. A key advantage of GCT is its ability to provide from a single simulation insightful graphical analyses of spatially resolved components of the enthalpies and entropies of hydration.
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Affiliation(s)
- Georgios Gerogiokas
- EaStCHEM School of Chemistry , Joseph Black Building, The King's Buildings, Edinburgh EH9 3JJ, United Kingdom
| | - Gaetano Calabro
- EaStCHEM School of Chemistry , Joseph Black Building, The King's Buildings, Edinburgh EH9 3JJ, United Kingdom
| | - Richard H Henchman
- Manchester Institute of Biotechnology, The University of Manchester , 131 Princess Street, Manchester M1 7DN, United Kingdom and School of Chemistry, The University of Manchester , Oxford Road, Manchester M13 9PL, United Kingdom
| | - Michelle W Y Southey
- Evotec (U.K.) Ltd. , 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
| | - Richard J Law
- Evotec (U.K.) Ltd. , 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
| | - Julien Michel
- EaStCHEM School of Chemistry , Joseph Black Building, The King's Buildings, Edinburgh EH9 3JJ, United Kingdom
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Haider K, Huggins DJ. Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules. J Chem Inf Model 2013; 53:2571-86. [PMID: 24070451 PMCID: PMC3840717 DOI: 10.1021/ci4003409] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Intermolecular interactions in the aqueous phase must compete with the interactions between the two binding partners and their solvating water molecules. In biological systems, water molecules in protein binding sites cluster at well-defined hydration sites and can form strong hydrogen-bonding interactions with backbone and side-chain atoms. Displacement of such water molecules is only favorable when the ligand can form strong compensating hydrogen bonds. Conversely, water molecules in hydrophobic regions of protein binding sites make only weak interactions, and the requirements for favorable displacement are less stringent. The propensity of water molecules for displacement can be identified using inhomogeneous fluid solvation theory (IFST), a statistical mechanical method that decomposes the solvation free energy of a solute into the contributions from different spatial regions and identifies potential binding hotspots. In this study, we employed IFST to study the displacement of water molecules from the ATP binding site of Hsp90, using a test set of 103 ligands. The predicted contribution of a hydration site to the hydration free energy was found to correlate well with the observed displacement. Additionally, we investigated if this correlation could be improved by using the energetic scores of favorable probe groups binding at the location of hydration sites, derived from a multiple copy simultaneous search (MCSS) method. The probe binding scores were not highly predictive of the observed displacement and did not improve the predictivity when used in combination with IFST-based hydration free energies. The results show that IFST alone can be used to reliably predict the observed displacement of water molecules in Hsp90. However, MCSS can augment IFST calculations by suggesting which functional groups should be used to replace highly displaceable water molecules. Such an approach could be very useful in improving the hit-to-lead process for new drug targets.
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Affiliation(s)
- Kamran Haider
- Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences , Lahore, 54792, Pakistan
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