Abstract
The solvated interaction energy (SIE) is an end-point, physics-based scoring function for predicting ligand-binding affinities. It supplements the force-field interaction energy with the desolvation cost of binding. Parameters such as the solute dielectric constant, Born radii, a cavity term and an overall scaling coefficient and additive constant have been previously calibrated against a training set of 99 protein–ligand complexes. We describe the application of the method to estimating binding free energies from molecular dynamics trajectories of protein–ligand binding complexes.
Key words
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ferrara, P., Gohlke, H., et al. (2004) Assessing Scoring Functions for Protein-Ligand Interactions, J. Med. Chem. 47, 3032–3047.
Wang, R., Lu, Y., et al. (2004) An Extensive Test of 14 Scoring Functions Using the PDBbind Refined Set of 800 Protein-Ligand Complexes, J. Chem. Inf. Comput. Sci. 44 2114–2125.
Warren, G. L., Andrews, C. W., et al. (2006) A Critical Assessment of Docking Programs and Scoring Functions, J. Med. Chem. 49, 5912–5931.
Gohlke, H., and Klebe, G. (2002) Approaches to the Description and Prediction of the Binding Affinity of Small-Molecule Ligands to Macromolecular Receptors, Angew. Chem. Int. Ed. 41, 2644–2676.
Böhm, H. J. (1994) The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure, J. Comput.-Aided Mol. Des. 8, 243–256.
Head, R. D., Smythe, M. L., et al. (1996) VALIDATE: A New Method for the Receptor-Based Prediction of Binding Affinities of Novel Ligands, J. Amer. Chem. Soc. 118, 3959–3969.
Tokarski, J. S., and Hopfinger, A. J. (1997) Prediction of Ligand-Receptor Binding Thermodynamics by Free Energy Force Field (FEFF) 3D-QSAR Analysis: Application to a Set of Peptidometic Renin Inhibitors, J. Chem. Inf. Comput. Sci. 37, 792–811.
Eldridge, M. D., Murray, C. W., et al. (1997) Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes, J. Comput.-Aided Mol. Des. 11, 425–445.
Wang, R., Lai, L., and Wang, S. (2002) Further development and validation of empirical scoring functions for structure-based binding affinity prediction, J. Comput.-Aided Mol. Des. 16, 11–26.
Hwang, J. K., and Warshel, A. (1987) Semiquantitative Calculations of Catalytic Free Energies in Genetically Modified Enzymes, Biochemistry 26, 2669–2673.
Gohlke, H., and Klebe, G. (2001) Statistical potentials and scoring functions applied to protein-ligand binding, Curr. Opin. Struct. Biol. 11, 231–235.
Huang, S.-Y., and Zou, X. (2010) Mean-force scoring functions for protein-ligand binding, Annu. Rep. Comput. Chem. 6, 281–296.
Muegge, I., and Martin, Y. C. (1999) A General and Fast Scoring Function for Protein-Ligand Interactions: A Simplified Potential Approach, J. Med. Chem. 42, 791–804.
Huang, S.-Y., and Zou, X. (2010) Inclusion of Solvation and Entropy in the Knowledge-Based Scoring Function for Protein−Ligand Interactions, J. Chem. Inf. Model. 50, 262–273.
Ishchenko, A. V., and Shakhnovich, E. I. (2002) SMall Molecule Growth 2001 (SMoG2001): An Improved Knowledge-Based Scoring Function for Protein−Ligand Interactions, J. Med. Chem. 45, 2770–2780.
Naïm, M., Bhat, S., et al. (2007) Solvated interaction energy (SIE) for scoring protein-ligand binding affinities. 1. Exploring the parameter space, J. Chem. Inf. Model. 47, 122–133.
Cui, Q., Sulea, T., et al. (2008) Molecular Dynamics - Solvated Interaction Energy Studies of Protein-Protein Interactions: the MP1-p14 Scaffolding Complex, J. Mol.Biol 379, 787–802.
Zou, X., Sun, Y., and Kuntz, I. D. (1999) Inclusion of Solvation in Ligand Binding Free Energy Calculations Using the Generalized-Born Model, J. Amer. Chem. Soc. 121, 8033–8043.
Kollman, P. A., Massova, I., et al. (2000) Calculating Structures and Free Energies of Complex Molecules: Combining Molecular Mechanics and Continuum Models, Acc. Chem. Res. 33, 889–897.
Kuhn, B., Gerber, P., et al. (2005) Validation and Use of the MM-PBSA Approach for Drug Discovery, J. Med. Chem. 48 4040–4048.
Gohlke, H., and Case, D. A. (2004) Converging free energy estimates: MM-PB(GB)SA studies on the protein-protein complex Ras-Raf, J. Comput. Chem. 25, 238–250.
Åqvist, J., Luzhkov, V. B., and Brandsdal, B. O. (2002) Ligand Binding Affinities from MD Simulations, Acc. Chem. Res. 35, 358–365.
Gilson, M. K., and Zhou, H. X. (2007) Calculation of Protein-Ligand Binding Affinities, Annu. Rev. Biophys. Biomol. Struct. 36, 21–42.
Chang, C. E., and Gilson, M. K. (2004) Free Energy, Entropy, and Induced Fit in Host-Guest Recognition: Calculations with the Second-Generation Mining Minima Algorithm, J. Amer. Chem. Soc. 126, 13156–13164.
Chen, W., Chang, C. E., and Gilson, M. K. (2004) Calculation of Cyclodextrin Binding Affinities: Energy, Entropy, and Implications for Drug Design, Biophys. J. 87, 3035–3049.
Jakalian, A., Jack, D. B., and Bayly, C. I. (2002) Fast, Efficient Generation of High-Quality Atomic Charges. AM1-BCC Model: II. Parameterization and validation, J. Comput. Chem. 23, 1623–1641.
Bayly, C. I., Cieplak, P., et al. (1993) A Well-Behaved Electrostatic Potential Based Method Using Charge Restraints for Deriving Atomic Charges: The RESP Model, J. Phys. Chem. 97, 10269–10280.
Hornak, V., Abel, R., et al. (2006) Comparison of multiple Amber force fields and development of improved protein backbone parameters, Proteins Struct. Funct. Bioinf. 65, 712–725.
Wang, J., Wolf, R. M., et al. (2004) Development and testing of a general amber force field, J. Comput. Chem. 25, 1157–1174.
Duan, Y., Wu, C., et al. (2003) A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations, J. Comput. Chem. 24, 1999–2012.
Genheden, S., and Ryde, U. (2010) How to obtain statistically converged MM/GBSA results, J. Comput. Chem. 31, 837–846.
Sadiq, S. K., Wright, D. W., et al. (2010) Accurate Ensemble Molecular Dynamics Binding Free Energy Ranking of Multidrug-Resistant HIV-1 Proteases, J. Chem. Inf. Model. 50, 890–905.
Wang, Y. T., Su, Z. Y., et al. (2009) Predictions of Binding for Dopamine D2 Receptor Antagonists by the SIE Method, J. Chem. Inf. Model. 49, 2369–2375.
Wimmerová, M., Mishra, N., et al. (2009) Importance of oligomerisation on Pseudomonas aeruginosa Lectin-II binding affinity. In silico and in vitro mutagenesis, J. Mol. Model. 15, 673–679.
Mishra, N. K., Kríz, Z., et al. (2010) Recognition of selected monosaccharides by Pseudomonas aeruginosa Lectin II analyzed by molecular dynamics and free energy calculations, Carbohydr. Res. 345, 1432–1441.
Rodriguez-Granillo, A., Sedlak, E., and Wittung-Stafshede, P. (2008) Stability and ATP Binding of the Nucleotide-binding Domain of the Wilson Disease Protein: Effect of the Common H1069Q Mutation, J. Mol. Biol. 383, 1097–1111.
Wei, C., Mei, Y., and Zhang, D. (2010) Theoretical study on the HIV-1 integrase-5CITEP complex based on polarized force fields, Chem. Phys. Lett. 495, 121–124.
Lecaille, F., Chowdhury, S., et al. (2007) The S2 subsites of cathepsins K and L and their contribution to collagen degradation, Protein Sci. 16, 662–670.
Nguyen, M., Marcellus, R. C., et al. (2007) Small molecule obatoclax (GX15-070) antagonizes MCL-1 and overcomes MCL-1-mediated resistance to apoptosis, Proc. Nat. Acad. Sci. U.S.A. 104, 19512–19517.
Okamoto, M., Takayama, K., et al. (2010) Structure-activity relationship of novel DAPK inhibitors identified by structure-based virtual screening, Bioorg. Med. Chem. 18, 2728–2734.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Sulea, T., Purisima, E.O. (2012). The Solvated Interaction Energy Method for Scoring Binding Affinities. In: Baron, R. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 819. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-465-0_19
Download citation
DOI: https://doi.org/10.1007/978-1-61779-465-0_19
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-61779-464-3
Online ISBN: 978-1-61779-465-0
eBook Packages: Springer Protocols