Molecular recognition between pancreatic lipase and natural and synthetic inhibitors

Lean, 2006, ABC of obesity: strategies for preventing obesity, BMJ: Br. Med. J., 333, 959, 10.1136/bmj.333.7575.959 Puhl, 2009, The stigma of obesity: a review and update, Obesity, 17, 941, 10.1038/oby.2008.636 Wang, 2013, Comparative analyses of lipoprotein lipase, hepatic lipase, and endothelial lipase, and their binding properties with known inhibitors, PLoS One, 8, e72146, 10.1371/journal.pone.0072146 Mendes, 2012, Properties and biotechnological applications of porcine pancreatic lipase, J. Mol. Catal. B: Enzym., 78, 119, 10.1016/j.molcatb.2012.03.004 Cai, 2012, In vitro inhibitory effect on pancreatic lipase activity of subfractions from ethanol extracts of fermented oats (Avena sativa L.) and synergistic effect of three phenolic acids, J. Agric. Food Chem., 60, 7245, 10.1021/jf3009958 Lowe, 1994, Pancreatic triglyceride lipase and colipase: insights into dietary fat digestion, Gastroenterology, 107, 10.1016/0016-5085(94)90559-2 Erlanson-Albertsson, 1983, The interaction between pancreatic lipase and colipase: a protein-proteininteraction regulated by a lipid, FEBS Lett., 162, 225, 10.1016/0014-5793(83)80760-1 Chen, 2014, Autophagy inhibition contributes to the synergistic interaction between EGCG and doxorubicin to kill the hepatoma hep3 B cells, PLoS One, 9, e85771, 10.1371/journal.pone.0085771 Wolfram, 2006, Anti-obesity effects of green tea: from bedside to bench, Mol. Nutr. Food Res., 50, 176, 10.1002/mnfr.200500102 de Mejia, 2009, Bioactive components of tea: cancer, inflammation and behavior, Brain Behav. Immun., 23, 721, 10.1016/j.bbi.2009.02.013 Tang, 2012, EGCG enhances the therapeutic potential of gemcitabine and CP690550 by inhibiting STAT3 signaling pathway in human pancreatic cancer, PLoS One, 7, e31067, 10.1371/journal.pone.0031067 Sergent, 2012, Phenolic compounds and plant extracts as potential natural anti-obesity substances, Food Chem., 135, 68, 10.1016/j.foodchem.2012.04.074 Grove, 2012, (−)-Epigallocatechin-3gallate inhibits pancreatic lipase and reduces body weight gain in high fat-fed obese mice, Obesity, 20, 2311, 10.1038/oby.2011.139 Nakai, 2005, Inhibitory effects of oolong tea polyphenols on pancreatic lipase in vitro, J. Agric. Food Chem., 53, 4593, 10.1021/jf047814+ Chen, 2012, In silico identification of potent pancreatic triacylglycerol lipase inhibitors from traditional Chinese medicine, PLoS One, 7, e43932, 10.1371/journal.pone.0043932 Zhi, 1995, Review of limited systemic absorption of orlistat, a lipase inhibitor, in healthy human volunteers, J. Clin. Pharmacol., 35, 1103, 10.1002/j.1552-4604.1995.tb04034.x Guerciolini, 1997, Mode of action of orlistat, Int. J. Obes. Relat. Metab. Disord., 21, S12 Karamadoukis, 2009, An unusual complication of treatment with orlistat, Clin. Nephrol., 71, 430, 10.5414/CNP71430 Ballinger, 2002, Orlistat: its current status as an anti-obesity drug, Eur. J. Pharmacol., 440, 109, 10.1016/S0014-2999(02)01422-X de la Garza, 2011, Natural inhibitors of pancreatic lipase as new players in obesity treatment, Planta Med., 77, 773, 10.1055/s-0030-1270924 Zhou, 2014, Epigallocatechin-3-Gallate (EGCG), a green tea polyphenol, stimulates hepatic autophagy and lipid clearance, PLoS One, 9, e87161, 10.1371/journal.pone.0087161 Bose, 2008, The major green tea polyphenol, (−)-epigallocatechin-3-gallate, inhibits obesity, metabolic syndrome, and fatty liver disease in high-fat-fed mice, J. Nutr., 138, 1677, 10.1093/jn/138.9.1677 Wang, 2014, Molecular interactions between (−)-epigallocatechin gallate analogs and pancreatic lipase, PLoS One, 9, e111143, 10.1371/journal.pone.0111143 Wu, 2013, Characterization of binding interactions of (−)-epigallocatechin-3-gallate fromgreen tea and lipase, J. Agric. Food Chem., 61, 8829, 10.1021/jf401779z Morris, 2009, AutoDock4 and AutoDockTools4. Automated docking with selective receptor flexiblity, J. Comput. Chem., 30, 2785, 10.1002/jcc.21256 Morris, 1998, Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function, J. Comput. Chem., 19, 1639, 10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B Irwin, 2005, ZINC-a free database of commercially available compounds for virtual screening, J. Chem. Inf. Model., 45, 177, 10.1021/ci049714+ Gaussian 09, Revision D.01, Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robb, M.A., Cheeseman, J.R., Scalmani, G., Barone, V., Mennucci, B., Petersson, G.A., Nakatsuji, H., Caricato, M., Li, X., Hratchian, H.P., Izmaylov, A.F., Bloino, J., Zheng, G., Sonnenberg, J.L., Hada, M., Ehara, M., Toyota, K., Fukuda, R., Hasegawa, J., Ishida, M., Nakajima, T., Honda, Y., Kitao, O., Nakai, H., Vreven, T., Montgomery, J. A., Jr., Peralta, J.E., Ogliaro, F., Bearpark, M., Heyd, J.J., Brothers, E., Kudin, K.N., Staroverov, V.N., Kobayashi, R., Normand, J., Raghavachari, K., Rendell, A., Burant, J. C., Iyengar, S.S., Tomasi, J., Cossi, M., Rega, N., Millam, J.M., Klene, M., Knox, J.E., Cross, J.B., Bakken, V., Adamo, C., Jaramillo, J., Gomperts, R., Stratmann, R.E., Yazyev, O., Austin, A.J., Cammi, R., Pomelli, C., Ochterski, J.W., Martin, R.L., Morokuma, K., Zakrzewski, V.G., Voth, G.A., Salvador, P., Dannenberg, J.J., Dapprich, S., Daniels, A.D., Farkas, Ö., Foresman, J.B., Ortiz, J.V., Cioslowski, J., Fox, D.J. Gaussian, Inc., Wallingford CT, 2009 Case, 2005, The amber biomolecular simulation programs, J. Comput. Chem., 26, 1668, 10.1002/jcc.20290 Duan, 2003, A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations, J. Comput. Chem., 24, 1999, 10.1002/jcc.10349 Wang, 2004, Development and testing of a general amber force field, J. Comput. Chem., 15, 1157, 10.1002/jcc.20035 Jorgensen, 1983, Comparison of simple potential functions for simulating liquid water, J. Chem. Phys., 79, 926, 10.1063/1.445869 Van Gunsteren, 1977, Algorithms for macromolecular dynamics and constraint dynamics, Mol. Phys., 34, 1311, 10.1080/00268977700102571 Darden, 1993, Particle mesh Ewald-an N·Log(N) method for Ewald sums in large systems, J. Chem. Phys., 98, 10089, 10.1063/1.464397 Berendsen, 1984, Molecular-dynamics with coupling to an external bath, J. Chem. Phys., 81, 3684, 10.1063/1.448118 Berendsen, 1995, GROMACS: a message-passing parallel molecular dynamics implementation, Comput. Phys. Commun., 91, 43, 10.1016/0010-4655(95)00042-E Van der Spoel, 2005, GROMACS fast, flexible, and free, J. Comput. Chem., 26, 1701, 10.1002/jcc.20291 Lindahl, 2001, GROMACS 3.0: a package for molecular simulation and trajectory analysis, J. Mol. Model., 7, 306, 10.1007/s008940100045 DeLano, 2002 Maestro, version 10.5. Schrödinger, LLC; New York, NY, USA : 2016-1. Amadei, 1993, Berendsen essential dynamics of protein, Proteins, 17, 412, 10.1002/prot.340170408 Miller, 2012, MMPBSA.py: an efficient program for end-state free energy calculations, J. Chem. Theory Comput., 8, 3314, 10.1021/ct300418h Gohlke, 2004, Converging free energy estimates: MMPB(GB)SA studies on the protein–protein complex Ras-Raf, J. Comput. Chem., 25, 238, 10.1002/jcc.10379 Kollman, 2000, Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models, Acc. Chem. Res., 33, 889, 10.1021/ar000033j Xu, 2013, Assessing the performance of MM/PBSA and MM/GBSA methods: 3. The impact of force fields and ligand charge models, J. Phys. Chem. B, 117, 8408, 10.1021/jp404160y Sun, 2014, Assessing the performance of MM/PBSA and MM/GBSA methods: 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set, Phys. Chem. Chem. Phys., 16, 16719, 10.1039/C4CP01388C Sun, 2014, Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring, Phys. Chem. Chem. Phys., 16, 22035, 10.1039/C4CP03179B Hou, 2010, Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations, J. Chem. Inf. Model., 51, 69, 10.1021/ci100275a Hou, 2011, Assessing the performance of the molecular mechanics/poisson Boltzmann surface area and molecular mechanics/generalized born surface area methods. II. The accuracy of ranking poses generated from docking, J. Comput. Chem., 32, 866, 10.1002/jcc.21666 Chen, 2016, Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein–protein binding free energies and re-rank binding poses generated by protein–protein docking, Phys. Chem. Chem. Phys., 18, 22129, 10.1039/C6CP03670H Onufriev, 2004, Exploring protein native states and large-scale conformational changes with a modified generalized born model, Proteins, 55, 383, 10.1002/prot.20033 Gohlke, 2004, Converging free energy estimates: MMPB(GB)SA studies on the protein–protein complex Ras-Raf, J. Comput. Chem., 25, 238, 10.1002/jcc.10379 Hou, 2008, Characterization of domain–peptide interaction interface: a case study on the amphiphysin-1 SH3 domain, J. Mol. Biol., 376, 1201, 10.1016/j.jmb.2007.12.054 Hou, 2009, Characterization of domain-peptide interaction interface a generic structure-based model to decipher the binding specificity of SH3 domains, Mol. Cell. Proteomics, 8, 639, 10.1074/mcp.M800450-MCP200 Hou, 2012, Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein–protein interaction network in yeast by generic structure-based models, J. Proteome Res., 11, 2982, 10.1021/pr3000688 Nygaard, 2013, The dynamic process of β(2) adrenergic receptor activation, Cell., 152, 532, 10.1016/j.cell.2013.01.008 Shi, 2004, Lipid metabolic enzymes: emerging drug targets for the treatment of obesity, Nat. Rev. Drug Discov., 3, 695, 10.1038/nrd1469 Egloff, 1995, Crystallographic study of the structure of colipase and of the interaction with pancreatic lipase, Protein Sci., 4, 44, 10.1002/pro.5560040107 Donner, 1976, Biochemistry, 15, 5413, 10.1021/bi00669a031 Patton, 1978, J. Biol. Chem., 253, 4195, 10.1016/S0021-9258(17)34703-8 Bourne, 1994, Horse pancreatic lipase: the crystal structure refined at 2.3 A resolution, J. Mol. Biol., 238, 709, 10.1006/jmbi.1994.1331 Birari, 2007, Pancreatic lipase inhibitors from natural sources: unexplored potential, Drug Discov. Today, 12, 879, 10.1016/j.drudis.2007.07.024 Veeramachaneni, 2015, High-throughput virtual screening with e-pharmacophore and molecular simulations study in the designing of pancreatic lipase inhibitors, Drug Des. Devel. Ther., 9, 4397, 10.2147/DDDT.S84052 Winkler, 1990, Structure of human pancreatic lipase, Nature, 343, 771, 10.1038/343771a0 Khedidja, 2011, Selection of orlistat as a potential inhibitor for lipase from Candida species, Bioinformation, 7, 125, 10.6026/97320630007125