Computational scheme for pH‐dependent binding free energy calculation with explicit solvent

We present a computational scheme to compute the pH‐dependence of binding free energy with explicit solvent. Despite the importance of pH, the effect of pH has been generally neglected in binding free energy calculations because of a lack of accurate methods to model it. To address this limitation, we use a constant‐pH methodology to obtain a true ensemble of multiple protonation states of a titratable system at a given pH and analyze the ensemble using the Bennett acceptance ratio (BAR) method. The constant pH method is based on the combination of enveloping distribution sampling (EDS) with the Hamiltonian replica exchange method (HREM), which yields an accurate semi‐grand canonical ensemble of a titratable system. By considering the free energy change of constraining multiple protonation states to a single state or releasing a single protonation state to multiple states, the pH dependent binding free energy profile can be obtained. We perform benchmark simulations of a host‐guest system: cucurbit[7]uril (CB[7]) and benzimidazole (BZ). BZ experiences a large pKa shift upon complex formation. The pH‐dependent binding free energy profiles of the benchmark system are obtained with three different long‐range interaction calculation schemes: a cutoff, the particle mesh Ewald (PME), and the isotropic periodic sum (IPS) method. Our scheme captures the pH‐dependent behavior of binding free energy successfully. Absolute binding free energy values obtained with the PME and IPS methods are consistent, while cutoff method results are off by 2 kcal mol−1. We also discuss the characteristics of three long‐range interaction calculation methods for constant‐pH simulations.

[1]  Michael K. Gilson,et al.  Blind prediction of host–guest binding affinities: a new SAMPL3 challenge , 2012, Journal of Computer-Aided Molecular Design.

[2]  B Honig,et al.  On the pH dependence of protein stability. , 1993, Journal of molecular biology.

[3]  Jan H. Jensen,et al.  Protein–protein binding is often associated with changes in protonation state , 2008, Proteins.

[4]  H. Grubmüller,et al.  Constant pH Molecular Dynamics in Explicit Solvent with λ-Dynamics , 2011, Journal of chemical theory and computation.

[5]  Asim Okur,et al.  MSCALE: A General Utility for Multiscale Modeling. , 2011, Journal of chemical theory and computation.

[6]  D. Case,et al.  Exploring protein native states and large‐scale conformational changes with a modified generalized born model , 2004, Proteins.

[7]  A. Baptista,et al.  Is the prediction of pKa values by constant‐pH molecular dynamics being hindered by inherited problems? , 2011, Proteins.

[8]  Ye Mei,et al.  Predicting hydration free energies with a hybrid QM/MM approach: an evaluation of implicit and explicit solvation models in SAMPL4 , 2014, Journal of Computer-Aided Molecular Design.

[9]  Alexander D. MacKerell,et al.  Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges , 2012, J. Chem. Inf. Model..

[10]  Bernard R Brooks,et al.  Enhanced Sampling in Free Energy Calculations: Combining SGLD with the Bennett's Acceptance Ratio and Enveloping Distribution Sampling Methods. , 2012, Journal of chemical theory and computation.

[11]  Eric Masson,et al.  Cucurbituril chemistry: a tale of supramolecular success , 2012 .

[12]  C. Brooks,et al.  Constant‐pH molecular dynamics using continuous titration coordinates , 2004, Proteins.

[13]  Jae Wook Lee,et al.  Cucurbituril homologues and derivatives: new opportunities in supramolecular chemistry. , 2003, Accounts of chemical research.

[14]  Boris Aguilar,et al.  Statistics and physical origins of pK and ionization state changes upon protein-ligand binding. , 2010, Biophysical journal.

[15]  D. Lauffenburger,et al.  pH Sensitivity of epidermal growth factor receptor complexes , 1993, Journal of cellular biochemistry.

[16]  Patrick G. Blachly,et al.  Protocols Utilizing Constant pH Molecular Dynamics to Compute pH-Dependent Binding Free Energies , 2014, The journal of physical chemistry. B.

[17]  Charles H. Bennett,et al.  Efficient estimation of free energy differences from Monte Carlo data , 1976 .

[18]  B. Brooks,et al.  A super-linear minimization scheme for the nudged elastic band method , 2003 .

[19]  P. Kollman,et al.  Simulating proteins at constant pH: An approach combining molecular dynamics and Monte Carlo simulation , 2002, Proteins.

[20]  Eunsung Lee,et al.  New Cucurbituril Homologues: Syntheses, Isolation, Characterization, and X-ray Crystal Structures of Cucurbit[n]uril (n = 5, 7, and 8) , 2000 .

[21]  J. Antosiewicz,et al.  Constant-pH molecular dynamics simulations: a test case of succinic acid , 2004 .

[22]  Y. Ko,et al.  Inclusion of methylviologen in cucurbit[7]uril , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Bernard R Brooks,et al.  pH replica‐exchange method based on discrete protonation states , 2011, Proteins.

[24]  John Mongan,et al.  Biomolecular simulations at constant pH. , 2005, Current opinion in structural biology.

[25]  P. Kollman,et al.  A well-behaved electrostatic potential-based method using charge restraints for deriving atomic char , 1993 .

[26]  Andrew T. Fenley,et al.  Bridging Calorimetry and Simulation through Precise Calculations of Cucurbituril–Guest Binding Enthalpies , 2014, Journal of chemical theory and computation.

[27]  Bernard R Brooks,et al.  Isotropic periodic sum: a method for the calculation of long-range interactions. , 2005, The Journal of chemical physics.

[28]  Bernard R Brooks,et al.  Isotropic periodic sum of electrostatic interactions for polar systems. , 2009, The Journal of chemical physics.

[29]  T. Darden,et al.  Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems , 1993 .

[30]  J. Wyman,et al.  Binding and Linkage: Functional Chemistry of Biological Macromolecules , 1990 .

[31]  Gerhard König,et al.  Multiscale Free Energy Simulations: An Efficient Method for Connecting Classical MD Simulations to QM or QM/MM Free Energies Using Non-Boltzmann Bennett Reweighting Schemes , 2014, Journal of chemical theory and computation.

[32]  H. Stern Molecular simulation with variable protonation states at constant pH. , 2007, The Journal of chemical physics.

[33]  Bernard R Brooks,et al.  Enhancing constant-pH simulation in explicit solvent with a two-dimensional replica exchange method. , 2015, Journal of chemical theory and computation.

[34]  B. Brooks,et al.  Constant pressure molecular dynamics simulation: The Langevin piston method , 1995 .

[35]  Y. Ko,et al.  Cucurbit[7]uril: a high-affinity host for encapsulation of amino saccharides and supramolecular stabilization of their α-anomers in water. , 2014, Angewandte Chemie.

[36]  S. Takada,et al.  On the Hamiltonian replica exchange method for efficient sampling of biomolecular systems: Application to protein structure prediction , 2002 .

[37]  S. Nosé A unified formulation of the constant temperature molecular dynamics methods , 1984 .

[38]  Benjamin T. Miller,et al.  Constant pH Molecular Dynamics in Explicit Solvent with Enveloping Distribution Sampling and Hamiltonian Exchange , 2014, Journal of chemical theory and computation.

[39]  Bernard R. Brooks,et al.  CHARMMing: A New, Flexible Web Portal for CHARMM , 2008, J. Chem. Inf. Model..

[40]  Jennifer L. Knight,et al.  Constant pH Molecular Dynamics Simulations of Nucleic Acids in Explicit Solvent. , 2012, Journal of chemical theory and computation.

[41]  Jennifer L. Lahti,et al.  Engineered epidermal growth factor mutants with faster binding on‐rates correlate with enhanced receptor activation , 2011, FEBS letters.

[42]  C. Tanford Protein denaturation. , 1968, Advances in protein chemistry.

[43]  Wilfred F van Gunsteren,et al.  Enveloping distribution sampling: a method to calculate free energy differences from a single simulation. , 2007, The Journal of chemical physics.

[44]  J. Antosiewicz,et al.  Constant-pH molecular dynamics study of protonation-structure relationship in a heptapeptide derived from ovomucoid third domain. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[45]  S. Petersen,et al.  Simulation of protein conformational freedom as a function of pH: constant‐pH molecular dynamics using implicit titration , 1997, Proteins.

[46]  O. Steinhauser,et al.  Towards a better description and understanding of biomolecular solvation. , 1999, Biophysical chemistry.

[47]  Alexander D. MacKerell,et al.  Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing , 2012, J. Chem. Inf. Model..

[48]  Ronald M. Levy,et al.  On Finite-Size Corrections to the Free Energy of Ionic Hydration , 1997 .

[49]  W. T. Chen,et al.  pH-dependent function, purification, and intracellular location of a major collagen-binding glycoprotein , 1987, The Journal of cell biology.

[50]  Alexander D. MacKerell,et al.  Simulating Monovalent and Divalent Ions in Aqueous Solution Using a Drude Polarizable Force Field. , 2010, Journal of chemical theory and computation.

[51]  Stefan Boresch,et al.  Absolute Binding Free Energies: A Quantitative Approach for Their Calculation , 2003 .

[52]  Gerhard Hummer,et al.  Free Energy of Ionic Hydration , 1996 .

[53]  Stefan Bruckner,et al.  Unorthodox uses of Bennett's acceptance ratio method , 2009, J. Comput. Chem..

[54]  Y. Bansal,et al.  The therapeutic journey of benzimidazoles: a review. , 2012, Bioorganic & medicinal chemistry.

[55]  Y. Sugita,et al.  Multidimensional replica-exchange method for free-energy calculations , 2000, cond-mat/0009120.

[56]  Thomas Simonson,et al.  An Overview of Electrostatic Free Energy Computations for Solutions and Proteins. , 2014, Journal of chemical theory and computation.

[57]  Bernard R. Brooks,et al.  Predicting binding affinities of host-guest systems in the SAMPL3 blind challenge: the performance of relative free energy calculations , 2011, Journal of Computer-Aided Molecular Design.

[58]  Bernard R Brooks,et al.  Using the isotropic periodic sum method to calculate long-range interactions of heterogeneous systems. , 2008, The Journal of chemical physics.

[59]  Gerhard König,et al.  Non‐Boltzmann sampling and Bennett's acceptance ratio method: How to profit from bending the rules , 2011, J. Comput. Chem..

[60]  W. Nau,et al.  Supramolecular encapsulation of benzimidazole-derived drugs by cucurbit[7]uril , 2011 .

[61]  C. Soares,et al.  Constant-pH molecular dynamics using stochastic titration , 2002 .

[62]  H. Ashbaugh,et al.  Continuum Corrections to the Polarization and Thermodynamic Properties of Ewald Sum Simulations for Ions and Ion Pairs at Infinite Dilution , 1998 .

[63]  Tetsu Narumi,et al.  Cutoff radius effect of the isotropic periodic sum and Wolf method in liquid-vapor interfaces of water. , 2011, The Journal of chemical physics.

[64]  Jianpeng Ma,et al.  CHARMM: The biomolecular simulation program , 2009, J. Comput. Chem..

[65]  Sarah L. Williams,et al.  Progress in the prediction of pKa values in proteins , 2011, Proteins.

[66]  Jingzhi Pu,et al.  Isotropic Periodic Sum Treatment of Long-Range Electrostatic Interactions in Combined Quantum Mechanical and Molecular Mechanical Calculations. , 2014, Journal of chemical theory and computation.

[67]  Bernard R. Brooks,et al.  Removal of pressure and free energy artifacts in charged periodic systems via net charge corrections to the Ewald potential , 1998 .

[68]  D. Case,et al.  Constant pH molecular dynamics in generalized Born implicit solvent , 2004, J. Comput. Chem..

[69]  Andrew C Simmonett,et al.  An efficient algorithm for multipole energies and derivatives based on spherical harmonics and extensions to particle mesh Ewald. , 2014, The Journal of chemical physics.

[70]  Wilfred F van Gunsteren,et al.  Multiple free energies from a single simulation: extending enveloping distribution sampling to nonoverlapping phase-space distributions. , 2008, The Journal of chemical physics.