2zdm Citations

Congeneric but still distinct: how closely related trypsin ligands exhibit different thermodynamic and structural properties.

J Mol Biol 405 1170-87 (2011)
Related entries: 2zdk, 2zdl, 2zdn, 2zfs, 2zft, 2zhd, 2zq1, 2zq2, 3ljj, 3ljo

Cited: 28 times
EuropePMC logo PMID: 21111747

Abstract

A congeneric series of benzamidine-type ligands with a central proline moiety and a terminal cycloalkyl group--linked by a secondary amine, ether, or methylene bridge--was synthesized as trypsin inhibitors. This series of inhibitors was investigated by isothermal titration calorimetry, crystal structure analysis in two crystal forms, and molecular dynamics simulations. Even though all of these congeneric ligands exhibited essentially the same affinity for trypsin, their binding profiles at the structural, dynamic, and thermodynamic levels are very distinct. The ligands display a pronounced enthalpy/entropy compensation that results in a nearly unchanged free energy of binding, even though individual enthalpy and entropy terms change significantly across the series. Crystal structures revealed that the secondary amine-linked analogs scatter over two distinct conformational families of binding modes that occupy either the inside or of the outside the protein's S3/S4 specificity pocket. In contrast, the ether-linked and methylene-linked ligands preferentially occupy the hydrophobic specificity pocket. This also explains why the latter ligands could only be crystallized in the conformationally restricting closed crystal form whereas the derivative with the highest residual mobility in the series escaped our attempts to crystallize it in the closed form; instead, a well-resolved structure could only be achieved in the open form with the ligand in disordered orientation. These distinct binding modes are supported by molecular dynamics simulations and correlate with the shifting enthalpic/entropic signatures of ligand binding. The examples demonstrate that, at the molecular level, binding modes and thermodynamic binding signatures can be very different even for closely related ligands. However, deviating binding profiles provide the opportunity to optimally address a given target.

Articles - 2zdm mentioned but not cited (1)

  1. Quantum-Chemical Quasi-Docking for Molecular Dynamics Calculations. Sulimov A, Kutov D, Ilin I, Sulimov V. Nanomaterials (Basel) 12 274 (2022)


Reviews citing this publication (7)

  1. Entropy-enthalpy compensation: role and ramifications in biomolecular ligand recognition and design. Chodera JD, Mobley DL. Annu Rev Biophys 42 121-142 (2013)
  2. Finding the sweet spot: the role of nature and nurture in medicinal chemistry. Hann MM, Keserü GM. Nat Rev Drug Discov 11 355-365 (2012)
  3. Applying thermodynamic profiling in lead finding and optimization. Klebe G. Nat Rev Drug Discov 14 95-110 (2015)
  4. The Molecular Origin of Enthalpy/Entropy Compensation in Biomolecular Recognition. Fox JM, Zhao M, Fink MJ, Kang K, Whitesides GM. Annu Rev Biophys 47 223-250 (2018)
  5. Be on Target: Strategies of Targeting Alternative and Lectin Pathway Components in Complement-Mediated Diseases. Dobó J, Kocsis A, Gál P. Front Immunol 9 1851 (2018)
  6. Correlating structure and energetics in protein-ligand interactions: paradigms and paradoxes. Martin SF, Clements JH. Annu Rev Biochem 82 267-293 (2013)
  7. In silico prediction of human serum albumin binding for drug leads. Vallianatou T, Lambrinidis G, Tsantili-Kakoulidou A. Expert Opin Drug Discov 8 583-595 (2013)

Articles citing this publication (20)

  1. Best Practices for Alchemical Free Energy Calculations [Article v1.0]. Mey ASJS, Allen BK, Macdonald HEB, Chodera JD, Hahn DF, Kuhn M, Michel J, Mobley DL, Naden LN, Prasad S, Rizzi A, Scheen J, Shirts MR, Tresadern G, Xu H. Living J Comput Mol Sci 2 18378 (2020)
  2. An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever. Powers CN, Setzer WN. Comb Chem High Throughput Screen 19 516-536 (2016)
  3. DeepFrag: a deep convolutional neural network for fragment-based lead optimization. Green H, Koes DR, Durrant JD. Chem Sci 12 8036-8047 (2021)
  4. Quantifying protein-ligand binding constants using electrospray ionization mass spectrometry: a systematic binding affinity study of a series of hydrophobically modified trypsin inhibitors. Cubrilovic D, Biela A, Sielaff F, Steinmetzer T, Klebe G, Zenobi R. J Am Soc Mass Spectrom 23 1768-1777 (2012)
  5. Water mediated ligand functional group cooperativity: the contribution of a methyl group to binding affinity is enhanced by a COO(-) group through changes in the structure and thermodynamics of the hydration waters of ligand-thermolysin complexes. Nasief NN, Tan H, Kong J, Hangauer D. J Med Chem 55 8283-8302 (2012)
  6. Tuning activity-based probe selectivity for serine proteases by on-resin 'click' construction of peptide diphenyl phosphonates. Serim S, Mayer SV, Verhelst SH. Org Biomol Chem 11 5714-5721 (2013)
  7. Evaluation of docking performance in a blinded virtual screening of fragment-like trypsin inhibitors. Surpateanu G, Iorga BI. J Comput Aided Mol Des 26 595-601 (2012)
  8. In vitro and in silico investigations of the binding interactions between chlorophenols and trypsin. Wang YQ, Tan CY, Zhuang SL, Zhai PZ, Cui Y, Zhou QH, Zhang HM, Fei Z. J Hazard Mater 278 55-65 (2014)
  9. Mechanism of cinnamic acid-induced trypsin inhibition: a multi-technique approach. Zhang H, Zhou Q, Cao J, Wang Y. Spectrochim Acta A Mol Biomol Spectrosc 116 251-257 (2013)
  10. Solvent effects on ligand binding to a serine protease. Gopal SM, Klumpers F, Herrmann C, Schäfer LV. Phys Chem Chem Phys 19 10753-10766 (2017)
  11. Prediction of trypsin/molecular fragment binding affinities by free energy decomposition and empirical scores. Benson ML, Faver JC, Ucisik MN, Dashti DS, Zheng Z, Merz KM. J Comput Aided Mol Des 26 647-659 (2012)
  12. Protein-ligand interactions: probing the energetics of a putative cation-π interaction. Myslinski JM, Clements JH, Martin SF. Bioorg Med Chem Lett 24 3164-3167 (2014)
  13. Understanding PIM-1 kinase inhibitor interactions with free energy simulation. Wang X, Sun Z. Phys Chem Chem Phys 21 7544-7558 (2019)
  14. Protein-Ligand Interactions: Thermodynamic Effects Associated with Increasing the Length of an Alkyl Chain. Myslinski JM, Clements JH, Delorbe JE, Martin SF. ACS Med Chem Lett 4 (2013)
  15. The impact of introducing a histidine into an apolar cavity site on docking and ligand recognition. Merski M, Shoichet BK. J Med Chem 56 2874-2884 (2013)
  16. Probing deep into the binding mechanisms of folic acid with α-amylase, pepsin and trypsin: An experimental and computational study. Shi W, Wang Y, Zhang H, Liu Z, Fei Z. Food Chem 226 128-134 (2017)
  17. Some thermodynamic effects of varying nonpolar surfaces in protein-ligand interactions. Cramer DL, Cheng B, Tian J, Clements JH, Wypych RM, Martin SF. Eur J Med Chem 208 112771 (2020)
  18. A Novel, Poly(Ethyl Ethylene Ether) Inhibitor to Trypsin from Marine Cyanobacteria, Lyngbya confervoides. Devi A, Prasanth S, Murugesh E, Haridas KR, Sabu A, Haridas M. Appl Biochem Biotechnol 178 891-899 (2016)
  19. Changing the selectivity profile - from substrate analog inhibitors of thrombin and factor Xa to potent matriptase inhibitors. Maiwald A, Hammami M, Wagner S, Heine A, Klebe G, Steinmetzer T. J Enzyme Inhib Med Chem 31 89-97 (2016)
  20. Connecting Classical QSAR and LERE Analyses Using Modern Molecular Calculations, LERE-QSAR (VI): Hydrolysis of Substituted Hippuric Acid Phenyl Esters by Trypsin. Mashima A, Kurahashi M, Sasahara K, Yoshida T, Chuman H. Mol Inform 33 802-814 (2014)