Artículo

Arcon, J.P.; Defelipe, L.A.; Modenutti, C.P.; López, E.D.; Alvarez-Garcia, D.; Barril, X.; Turjanski, A.G.; Martí, M.A. "Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions" (2017) Journal of Chemical Information and Modeling. 57(4):846-863
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Abstract:

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed. © 2017 American Chemical Society.

Registro:

Documento: Artículo
Título:Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions
Autor:Arcon, J.P.; Defelipe, L.A.; Modenutti, C.P.; López, E.D.; Alvarez-Garcia, D.; Barril, X.; Turjanski, A.G.; Martí, M.A.
Filiación:Departamento de Química Biológica e IQUIBICEN-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Ciudad de Buenos Aires, C1428EHA, Argentina
Discngine, 33 rue du Fauburg Saint-Antoine, Paris, 75011, France
Institut de Biomedicina de la Universitat de Barcelona (IBUB), Facultat de Farmàcia, Universitat de Barcelona, Av. Joan XXIII s/n, Barcelona, 08028, Spain
Catalan Institution for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, Barcelona, 08010, Spain
Palabras clave:Binding sites; Complexation; Ethanol; Free energy; Ligands; Molecular dynamics; Probes; Proteins; Solvents; Accuracy and precision; Accurate prediction; Binding free energy; Biological process; Molecular dynamics simulations; Protein-binding sites; Protein-ligand complexes; Protein-ligand interactions; Binding energy; ligand; protein; protein binding; solvent; water; chemical phenomena; chemistry; metabolism; molecular docking; molecular dynamics; protein conformation; thermodynamics; Hydrophobic and Hydrophilic Interactions; Ligands; Molecular Docking Simulation; Molecular Dynamics Simulation; Protein Binding; Protein Conformation; Proteins; Solvents; Thermodynamics; Water
Año:2017
Volumen:57
Número:4
Página de inicio:846
Página de fin:863
DOI: http://dx.doi.org/10.1021/acs.jcim.6b00678
Título revista:Journal of Chemical Information and Modeling
Título revista abreviado:J. Chem. Inf. Model.
ISSN:15499596
CODEN:JCISD
CAS:protein, 67254-75-5; water, 7732-18-5; Ligands; Proteins; Solvents; Water
Registro:http://digital.bl.fcen.uba.ar/collection/paper/document/paper_15499596_v57_n4_p846_Arcon

Referencias:

  • Bissantz, C., Kuhn, B., Stahl, M., A Medicinal Chemist's Guide to Molecular Interactions (2010) J. Med. Chem., 53, pp. 5061-5084
  • Medina-Franco, J.L., Mendez-Lucio, O., Martinez-Mayorga, K., The Interplay between Molecular Modeling and Chemoinformatics to Characterize Protein-Ligand and Protein-Protein Interactions Landscapes for Drug Discovery (2014) Advances in Protein Chemistry and Structural Biology, 16, pp. 1-37. , first ed. Karabencheva-Chistova, T. Academic Press: London, United Kingdom
  • Drews, J., Drug Discovery: A Historical Perspective (2000) Science, 287, pp. 1960-1964
  • Loging, W., Rodriguez-Esteban, R., Hill, J., Freeman, T., Miglietta, J., Cheminformatic/bioinformatic Analysis of Large Corporate Databases: Application to Drug Repurposing (2011) Drug Discovery Today: Ther. Strategies, 8, pp. 109-116
  • Fadda, E., Woods, R.J., Molecular Simulations of Carbohydrates and Protein-Carbohydrate Interactions: Motivation, Issues and Prospects (2010) Drug Discovery Today, 15, pp. 596-609
  • Powlesland, A.S., Quintero-Martinez, A., Lim, P.G., Pipirou, Z., Taylor, M.E., Drickamer, K., Engineered Carbohydrate-Recognition Domains for Glycoproteomic Analysis of Cell Surface Glycosylation and Ligands for Glycan-Binding Receptors (2010) Methods Enzymol., 480, pp. 165-179
  • Du, X., Li, Y., Xia, Y., Ai, S., Liang, J., Sang, P., Ji, X., Liu, S.-Q., Insights into Protein-Ligand Interactions: Mechanisms, Models, and Methods (2016) Int. J. Mol. Sci., 17, p. 144
  • Konc, J., Lesnik, S., Janezic, D., Modeling Enzyme-Ligand Binding in Drug Discovery (2015) J. Cheminf., 7, pp. 1-8
  • Mattos, C., Bellamacina, C.R., Peisach, E., Pereira, A., Vitkup, D., Petsko, G.A., Ringe, D., Multiple Solvent Crystal Structures: Probing Binding Sites, Plasticity and Hydration (2006) J. Mol. Biol., 357, pp. 1471-1482
  • English, A.C., Groom, C.R., Hubbard, R.E., Experimental and Computational Mapping of the Binding Surface of a Crystalline Protein (2001) Protein Eng., Des. Sel., 14, pp. 47-59
  • Liepinsh, E., Otting, G., Organic Solvents Identify Specific Ligand Binding Sites on Protein Surfaces (1997) Nat. Biotechnol., 15, pp. 264-268
  • Shuker, S.B., Hajduk, P.J., Meadows, R.P., Fesik, S.W., Discovering High-Affinity Ligands for Proteins: SAR by NMR (1996) Science, 274, pp. 1531-1534
  • Dechene, M., Wink, G., Smith, M., Swartz, P., Mattos, C., Multiple Solvent Crystal Structures of Ribonuclease A: An Assessment of the Method (2009) Proteins: Struct., Funct., Genet., 76, pp. 861-881
  • Davies, D.R., Begley, D.W., Hartley, R.C., Staker, B.L., Stewart, L.J., Predicting the Success of Fragment Screening by X-Ray Crystallography (2011) Methods Enzymol., 493, pp. 91-114
  • Seco, J., Luque, F.J., Barril, X., Binding Site Detection and Druggability Index from First Principles (2009) J. Med. Chem., 52, pp. 2363-2371
  • Guvench, O., MacKerell, A.D.J., Computational Fragment-Based Binding Site Identification by Ligand Competitive Saturation (2009) PLoS Comput. Biol., 5, p. e1000435
  • Bakan, A., Nevins, N., Lakdawala, A.S., Bahar, I., Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules (2012) J. Chem. Theory Comput., 8, pp. 2435-2447
  • Lexa, K.W., Carlson, H.A., Full Protein Flexibility Is Essential for Proper Hot-Spot Mapping (2011) J. Am. Chem. Soc., 133, pp. 200-202
  • Lopez, E.D., Arcon, J.P., Gauto, D.F., Petruk, A.A., Modenutti, C.P., Dumas, V.G., Marti, M.A., Turjanski, A.G., WATCLUST: A Tool for Improving the Design of Drugs Based on Protein-Water Interactions (2015) Bioinformatics, 31, pp. 3697-3699
  • Abel, R., Young, T., Farid, R., Berne, B.J., Friesner, R.A., Role of the Active-Site Solvent in the Thermodynamics of Factor Xa Ligand Binding (2008) J. Am. Chem. Soc., 130, pp. 2817-2831
  • Hu, B., Lill, M.A., Protein Pharmacophore Selection Using Hydration-Site Analysis (2012) J. Chem. Inf. Model., 52, pp. 1046-1060
  • Nguyen, C.N., Cruz, A., Gilson, M.K., Kurtzman, T., Thermodynamics of Water in an Enzyme Active Site: Grid-Based Hydration Analysis of Coagulation Factor Xa (2014) J. Chem. Theory Comput., 10, pp. 2769-2780
  • Wong, S.E., Lightstone, F.C., Accounting for Water Molecules in Drug Design (2011) Expert Opin. Drug Discovery, 6, pp. 65-74
  • Ladbury, J.E., Just Add Water! the Effect of Water on the Specificity of Protein-Ligand Binding Sites and Its Potential Application to Drug Design (1996) Chem. Biol., 3, pp. 973-980
  • Li, Z., Lazaridis, T., Water at Biomolecular Binding Interfaces (2007) Phys. Chem. Chem. Phys., 9, pp. 573-581
  • Modenutti, C., Gauto, D., Radusky, L., Blanco, J., Turjanski, A., Hajos, S., Marti, M.A., Using Crystallographic Water Properties for the Analysis and Prediction of Lectin-Carbohydrate Complex Structures (2015) Glycobiology, 25, pp. 181-196
  • Li, Z., Lazaridis, T., Computing the Thermodynamic Contributions of Interfacial Water (2012) Computational Drug Discovery and Design, 819, pp. 393-404. , Baron, R. Springer New York: New York, NY
  • Ichihara, O., Shimada, Y., Yoshidome, D., The Importance of Hydration Thermodynamics in Fragment-to-Lead Optimization (2014) ChemMedChem, 9, pp. 2708-2717
  • Alvarez-Garcia, D., Barril, X., Molecular Simulations with Solvent Competition Quantify Water Displaceability and Provide Accurate Interaction Maps of Protein Binding Sites (2014) J. Med. Chem., 57, pp. 8530-8539
  • Raman, E.P., Yu, W., Lakkaraju, S.K., MacKerell, A.D., Inclusion of Multiple Fragment Types in the Site Identification by Ligand Competitive Saturation (SILCS) Approach (2013) J. Chem. Inf. Model., 53, pp. 3384-3398
  • Yang, C.Y., Wang, S., Computational Analysis of Protein Hotspots (2010) ACS Med. Chem. Lett., 1, pp. 125-129
  • Lakkaraju, S.K., Raman, E.P., Yu, W., MacKerell, A.D., Sampling of Organic Solutes in Aqueous and Heterogeneous Environments Using Oscillating Excess Chemical Potentials in Grand Canonical-like Monte Carlo-Molecular Dynamics Simulations (2014) J. Chem. Theory Comput., 10, pp. 2281-2290
  • Mysinger, M.M., Carchia, M., Irwin, J.J., Shoichet, B.K., Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking (2012) J. Med. Chem., 55, pp. 6582-6594
  • Le Guilloux, V., Schmidtke, P., Tuffery, P., Fpocket: An Open Source Platform for Ligand Pocket Detection (2009) BMC Bioinf., 10, p. 168
  • Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E., The Protein Data Bank (2000) Nucleic Acids Res., 28, pp. 235-242
  • Case, D.A., Darden, T.A., Cheatham, T.E., Simmerling, C.L., Wang, J., Duke, R.E., Luo, R., Kollman, P.A., (2012) Amber 12, , University of California: San Francisco, CA
  • 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 (2006) Proteins: Struct., Funct., Genet., 65, pp. 712-725
  • Goetz, A.W., Williamson, M.J., Xu, D., Poole, D., Le Grand, S., Walker, R.C., Routine Microsecond Molecular Dynamics Simulations with AMBER - Part 1: Generalized Born (2012) J. Chem. Theory Comput., 8, pp. 1542-1555
  • Salomon-Ferrer, R., Goetz, A.W., Poole, D., Le Grand, S., Walker, R.C., Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs - Part 2: Explicit Solvent Particle Mesh Ewald (2013) J. Chem. Theory Comput., 9, pp. 3878-3888
  • Gauto, D.F., Di Lella, S., Guardia, C.M.A., Estrin, D.A., Marti, M.A., Carbohydrate-Binding Proteins: Dissecting Ligand Structures through Solvent Environment Occupancy (2009) J. Phys. Chem. B, 113, pp. 8717-8724
  • Young, T., Abel, R., Kim, B., Berne, B.J., Friesner, R.A., Motifs for Molecular Recognition Exploiting Hydrophobic Enclosure in Protein-Ligand Binding (2007) Proc. Natl. Acad. Sci. U. S. A., 104, pp. 808-813
  • Gauto, D.F., Petruk, A.A., Modenutti, C.P., Blanco, J.I., Di Lella, S., Marti, M.A., Solvent Structure Improves Docking Prediction in Lectin-Carbohydrate Complexes (2013) Glycobiology, 23, pp. 241-258
  • Morris, G.M., Huey, R., Lindstrom, W., Sanner, M.F., Belew, R.K., Goodsell, D.S., Olson, A.J., AutoDock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility (2009) J. Comput. Chem., 30, pp. 2785-2791
  • Kozakov, D., Grove, L.E., Hall, D.R., Bohnuud, T., Mottarella, S.E., Luo, L., Xia, B., Vajda, S., The FTMap Family of Web Servers for Determining and Characterizing Ligand-Binding Hot Spots of Proteins (2015) Nat. Protoc., 10, pp. 733-755
  • Hou, T., Wang, J., Li, Y., Wang, W., Assessing the Performance of the MM/PBSA and MM/GBSA Methods. I. the Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations (2011) J. Chem. Inf. Model., 51, pp. 69-82
  • Ghanakota, P., Carlson, H.A., Moving beyond Active-Site Detection: MixMD Applied to Allosteric Systems (2016) J. Phys. Chem. B, 120, pp. 8685-8695
  • Yu, W., Lakkaraju, S.K., Raman, E.P., Fang, L., MacKerell, A.D., Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules (2015) J. Chem. Inf. Model., 55, pp. 407-420
  • Foster, T.J., MacKerell, A.D., Guvench, O., Balancing Target Flexibility and Target Denaturation in Computational Fragment-Based Inhibitor Discovery (2012) J. Comput. Chem., 33, pp. 1880-1891
  • Limongelli, V., Bonomi, M., Parrinello, M., Funnel Metadynamics as Accurate Binding Free-Energy Method (2013) Proc. Natl. Acad. Sci. U. S. A., 110, pp. 6358-6363
  • Wang, L., Wu, Y., Deng, Y., Kim, B., Pierce, L., Krilov, G., Lupyan, D., Abel, R., Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field (2015) J. Am. Chem. Soc., 137, pp. 2695-2703

Citas:

---------- APA ----------
Arcon, J.P., Defelipe, L.A., Modenutti, C.P., López, E.D., Alvarez-Garcia, D., Barril, X., Turjanski, A.G.,..., Martí, M.A. (2017) . Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions. Journal of Chemical Information and Modeling, 57(4), 846-863.
http://dx.doi.org/10.1021/acs.jcim.6b00678
---------- CHICAGO ----------
Arcon, J.P., Defelipe, L.A., Modenutti, C.P., López, E.D., Alvarez-Garcia, D., Barril, X., et al. "Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions" . Journal of Chemical Information and Modeling 57, no. 4 (2017) : 846-863.
http://dx.doi.org/10.1021/acs.jcim.6b00678
---------- MLA ----------
Arcon, J.P., Defelipe, L.A., Modenutti, C.P., López, E.D., Alvarez-Garcia, D., Barril, X., et al. "Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions" . Journal of Chemical Information and Modeling, vol. 57, no. 4, 2017, pp. 846-863.
http://dx.doi.org/10.1021/acs.jcim.6b00678
---------- VANCOUVER ----------
Arcon, J.P., Defelipe, L.A., Modenutti, C.P., López, E.D., Alvarez-Garcia, D., Barril, X., et al. Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions. J. Chem. Inf. Model. 2017;57(4):846-863.
http://dx.doi.org/10.1021/acs.jcim.6b00678