The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction
Abstract
:1. Introduction
2. Results and Discussion
2.1. Two-Atom System (H–O System)
2.2. Two Amino Acid System (Arg–Glu System)
2.3. Two-Protein System (Bn-Bs System)
3. Methods
3.1. Intrinsic Radius in GB Model
3.2. Energy Analysis
4. Concluding Remarks
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Sheinerman, F.B.; Norel, R.; Honig, B. Electrostatic Aspects of Protein-Protein Interactions. Curr. Opin. Struct. Biol. 2000, 10, 153–159. [Google Scholar] [CrossRef] [PubMed]
- Schreiber, G.; Haran, G.; Zhou, H.-X. Fundamental Aspects of Protein-Protein Association Kinetics. Chem. Rev. 2009, 109, 839–860. [Google Scholar] [CrossRef] [Green Version]
- Born, M. Volumen und hydratationswärme der Ionen. Z. Phys. 1920, 1, 45–48. [Google Scholar] [CrossRef] [Green Version]
- Still, W.C.; Tempczyk, A.; Hawley, R.C.; Hendrickson, T. Semianalytical Treatment of Solvation for Molecular Mechanics and Dynamics. J. Am. Chem. Soc. 1990, 112, 6127–6129. [Google Scholar] [CrossRef]
- Hawkins, G.D.; Cramer, C.J.; Truhlar, D.G. Pairwise Solute Descreening of Solute Charges from a Dielectric Medium. Chem. Phys. Lett. 1995, 246, 122–129. [Google Scholar] [CrossRef]
- Hawkins, G.D.; Cramer, C.J.; Truhlar, D.G. Parametrized Models of Aqueous Free Energies of Solvation Based on Pairwise Descreening of Solute Atomic Charges from a Dielectric Medium. J. Phys. Chem. 1996, 100, 19824–19839. [Google Scholar] [CrossRef]
- Qiu, D.; Shenkin, P.S.; Hollinger, F.P.; Still, W.C. The GB/SA Continuum Model for Solvation. A Fast Analytical Method for the Calculation of Approximate Born Radii. J. Phys. Chem. A 1997, 101, 3005–3014. [Google Scholar] [CrossRef]
- Schaefer, M.; Karplus, M. A Comprehensive Analytical Treatment of Continuum Electrostatics. J. Phys. Chem. 1996, 100, 1578–1599. [Google Scholar] [CrossRef]
- Dominy, B.N.; Brooks, C.L., III. Development of a Generalized Born Model Parametrization for Proteins and Nucleic Acids. J. Phys. Chem. B 1999, 103, 3765–3773. [Google Scholar] [CrossRef]
- Bashford, D.; Case, D.A. Generalized Born Models of Macromolecular Solvation Effects. Annu. Rev. Phys. Chem. 2000, 51, 129–152. [Google Scholar] [CrossRef]
- Tsui, V.; Case, D.A. Molecular Dynamics Simulations of Nucleic Acids with a Generalized Born Solvation Model. J. Am. Chem. Soc. 2000, 122, 2489–2498. [Google Scholar] [CrossRef]
- Tsui, V.; Case, D.A. Theory and Applications of The Generalized Born Solvation Model in Macromolecular Simulations. Biopolymers 2001, 56, 275–291. [Google Scholar] [CrossRef]
- Lee, M.S.; Salsbury, F.R.H.; Brooks, C.L., III. Novel Generalized Born Methods. J. Chem. Phys. 2002, 116, 10606–10614. [Google Scholar] [CrossRef]
- Lee, M.S.; Feig, M.; Salsbury, F.R., Jr.; Brooks, C.L., III. New Analytic Approximation to the Standard Molecular Volume Definition and Its Application to Generalized Born Calculations. J. Comput. Chem. 2003, 24, 1348–1356. [Google Scholar] [CrossRef]
- Im, W.; Lee, M.S.; Brooks, C.L., III. Generalized Born Model with a Simple Smoothing Function. J. Comput. Chem. 2003, 24, 1691–1702. [Google Scholar] [CrossRef]
- Onufriev, A.; Bashford, D.; Case, D.A. Exploring Protein Native States and Large-scale Conformational Changes with a Modified Generalized Born Model. Proteins Struct. Funct. Bioinf. 2004, 55, 383–394. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Feig, M.; Onufriev, A.; Lee, M.S.; Im, W.; Case, D.A.; Brooks, C.L., III. Performance Comparison of Generalized Born and Poisson Methods in the Calculation of Electrostatic Solvation Energies for Protein Structures. J. Comput. Chem. 2004, 25, 265–284. [Google Scholar] [CrossRef]
- Gallicchio, E.; Levy, R.M. AGBNP: An Analytic Implicit Solvent Model Suitable for Molecular Dynamics Simulations and High-Resolution Modeling. J. Comput. Chem. 2004, 25, 479–499. [Google Scholar] [CrossRef]
- Im, W.; Chen, J.; Brooks, C.L. Peptide and Protein Folding and Conformational Equilibria: Theoretical Treatment of Electrostatics and Hydrogen Bonding with Implicit Solvent Models. Adv. Protein Chem. 2005, 72, 173–198. [Google Scholar]
- Chen, J.; Im, W.; Brooks, C.L. Balancing Solvation and Intramolecular Interactions: Toward a Consistent Generalized Born Force Field. J. Am. Chem. Soc. 2006, 128, 3728–3736. [Google Scholar] [CrossRef] [Green Version]
- Mongan, J.; Simmerling, C.; McCammon, J.A.; Case, D.A.; Onufriev, A. Generalized Born Model with a Simple, Robust Molecular Volume Correction. J. Chem. Theory Comput. 2007, 3, 156–169. [Google Scholar] [CrossRef]
- Aguilar, B.; Shadrach, R.; Onufriev, A.V. Reducing the Secondary Structure Bias in the Generalized Born Model via R6 Effective Radii. J. Chem. Theory Comput. 2010, 6, 3613–3630. [Google Scholar] [CrossRef]
- Nguyen, H.; Roe, D.R.; Simmerling, C. Improved Generalized Born Solvent Model Parameters for Protein Simulations. J. Chem. Theory Comput. 2013, 9, 2020–2034. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mizuhara, Y.; Parkin, D.; Umezawa, K.; Ohnuki, J.; Takano, M. Over-Destabilization of Protein-Protein Interaction in Generalized Born Model and Utility of Energy Density Integration Cutoff. J. Phys. Chem. B 2017, 121, 4669–4677. [Google Scholar] [CrossRef] [PubMed]
- Bondi, A. van der Waals volumes and radii. J. Phys. Chem. 1964, 68, 441–451. [Google Scholar] [CrossRef]
- Felts, A.K.; Gallicchio, E.; Chekmarev, D.; Paris, K.A.; Friesner, R.A.; Levy, R.M. Prediction of protein loop conformations using the AGBNP implicit solvent model and torsion angle sampling. J. Chem. Theory Comput. 2008, 4, 855–868. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Geney, R.; Layten, M.; Gomperts, R.; Hornak, V.; Simmerling, C. Investigation of Salt Bridge Stability in a Generalized Born Solvent Model. J. Chem. Theory Comput. 2006, 2, 115–127. [Google Scholar] [CrossRef] [PubMed]
- Parkin, D.; Takano, M. Coulombic Organization in Membrane-Embedded Rotary Motor of ATP synthase. J. Phys. Chem. B 2023, 127, 1552–1562. [Google Scholar] [CrossRef]
- Kamiyama, Y.; Parkin, D.; Takano, M. Torque Generation Mechanism in Fo Motor of ATP Synthase Elucidated by Free-energy and Coulomb-energy Landscapes along the c-ring Rotation. Biochem. Biophys. Res. Commun. 2023, 651, 56–61. [Google Scholar] [CrossRef]
- Buckle, A.M.; Schreiber, G.; Fersht, A.R. Protein-Protein Recognition: Crystal Structural Analysis of Barnase-Barstar Complex at 2.0-Å Resolution. Biochemistry 1994, 33, 8878–8889. [Google Scholar] [CrossRef]
- Dong, F.; Vijayakumar, M.; Zhou, H.-X. Comparison of Calculation and Experiment Implicates Significant Electrostatic Contributions to the Binding Stability of Barnase and Barstar. Biophys. J. 2003, 85, 49–60. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, T.; Tomic, S.; Gabdoulline, R.R.; Wade, R.C. How Optimal are the Binding Energetics of Barnase and Barstar? Biophys. J. 2004, 87, 1618–1630. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gumbart, J.C.; Roux, B.; Chipot, C. Efficient Determination of Protein-Protein Standard Binding Free Energies from First Principles. J. Chem. Theory Comput. 2013, 9, 3789–3798. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baker, N.A.; Sept, D.; Joseph, S.; Holst, M.J.; McCammon, J.A. Electrostatics of Nanosystems: Application to Microtubules and the Ribosome. Proc. Natl. Acad. Sci. USA 2001, 98, 10037–10041. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Constanciel, R.; Contreras, R. Self Consistent Field Theory of Solvent Effects Representation by Continuum Models: Introduction of Desolvation Contribution. Theor. Chim. Acta 1984, 65, 1–11. [Google Scholar] [CrossRef]
- Cornell, W.D.; Cieplak, P.; Bayly, C.I.; Gould, I.R.; Merz, K.M.; Ferguson, D.M.; Spellmeyer, D.C.; Fox, T.; Caldwell, J.W.; Kollman, P.A. A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules. J. Am. Chem. Soc. 1995, 117, 5179–5197. [Google Scholar] [CrossRef] [Green Version]
- Hornak, V.; Abel, R.; Okur, A.; Strockbine, B.; Roitberg, A.; Simmerling, C. Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins: Struct. Funct. Bioinform. 2006, 65, 712–725. [Google Scholar] [CrossRef] [Green Version]
- Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys. 1983, 79, 926–935. [Google Scholar] [CrossRef]
- Essmann, U.; Perera, L.; Berkowitz, M.L.; Darden, T.; Lee, H.; Pedersen, L.G. A Smooth Particle Mesh Ewald Method. J. Chem. Phys. 1995, 103, 8577–8593. [Google Scholar] [CrossRef] [Green Version]
- Berendsen, H.J.C.; Postma, J.P.M.; van Gunsteren, W.F.; DiNola, A.; Haak, J.R. Molecular Dynamics with Coupling to an External Bath. J. Chem. Phys. 1984, 81, 3684–3690. [Google Scholar] [CrossRef] [Green Version]
- Case, D.A.; Darden, T.A.; Cheatham, T.E., III; Simmerling, C.L.; Wang, J.; Duke, R.E.; Luo, R.; Walker, R.C.; Zhang, W.; Merz, K.M.; et al. AMBER12; University of California: San Francisco, CA, USA, 2012. [Google Scholar]
- Joung, I.S.; Cheatham, T.E., III. Determination of Alkali and Halide Monovalent Ion Parameters for Use in Explicitly Solvated Biomolecular Simulations. J. Phys. Chem. B 2008, 112, 9020–9041. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M.C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; et al. A Point-Charge Force Field for Molecular Mechanics Simulations of Proteins Based on Condensed-Phase Quantum Mechanical Calculations. J. Comput. Chem. 2003, 24, 1999–2012. [Google Scholar] [CrossRef] [PubMed]
- Eswar, N.; Webb, B.; Marti-Renom, M.A.; Madhusudhan, M.S.; Eramian, D.; Shen, M.Y.; Pieper, U.; Šali, A. Comparative Protein Structure Modeling Using MODELLER. Curr. Protoc. Protein Sci. 2007. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kumar, S.; Bouzida, D.; Swendsen, R.H.; Kollman, P.A.; Rosenberg, J.M. The Weighted Histogram Analysis Method for Free-energy Calculations on Biomolecules. I. The Method. J. Comput. Chem. 1992, 13, 1011–1021. [Google Scholar] [CrossRef]
- Wong, S.; Amaro, R.E.; McCammon, J.A. MM-PBSA Captures Key Role of Intercalating Water Molecules at a Protein-Protein Interface. J. Chem. Theory Comput. 2009, 5, 422–429. [Google Scholar] [CrossRef] [Green Version]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Parkin, D.; Takano, M. The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction. Int. J. Mol. Sci. 2023, 24, 4700. https://doi.org/10.3390/ijms24054700
Parkin D, Takano M. The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction. International Journal of Molecular Sciences. 2023; 24(5):4700. https://doi.org/10.3390/ijms24054700
Chicago/Turabian StyleParkin, Dan, and Mitsunori Takano. 2023. "The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction" International Journal of Molecular Sciences 24, no. 5: 4700. https://doi.org/10.3390/ijms24054700
APA StyleParkin, D., & Takano, M. (2023). The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction. International Journal of Molecular Sciences, 24(5), 4700. https://doi.org/10.3390/ijms24054700