Chapter 9 Calculating Binding Free Energy in Protein–Ligand Interaction

作者: Kaushik Raha , Kenneth M. Merz

DOI: 10.1016/S1574-1400(05)01009-1

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摘要: Publisher Summary This chapter examines the calculation of binding free energy in protein–ligand interaction. A deeper understanding way a protein recognizes its biologically relevant ligand or small molecule inhibitor will have profound effect on biological recognition processes and ability to design therapeutics. Binding affinity can be estimated experimentally by kinetic experiments that measure inhibition enzyme presence both substrate is reported as an constant. Theoretical calculations determine more direct fashion calculating properties individual structures protein, ligand, complex, their ensembles. state function treated such these calculations, which means it independent path taken from reactants product. Polarization charge transfer play significant role molecular interactions. Such effects captured using quantum mechanics. Rigorous exhaustive electrostatic interaction energies performed at high levels theory. are feasible only for model chemistries severely restricted computational cost associated with study larger molecules.

参考文章(91)
Mark Baker, Rajkumar Buyya, None, Cluster Computing at a Glance Prentice Hall PTR. pp. 3- 47 ,(1999)
Johan Åqvist, Victor B. Luzhkov, Bjørn O. Brandsdal, Ligand Binding Affinities from MD Simulations Accounts of Chemical Research. ,vol. 35, pp. 358- 365 ,(2002) , 10.1021/AR010014P
Johan Åqvist, Carmen Medina, Jan-Erik Samuelsson, A New Method for Predicting Binding Affinity in Computer-Aided Drug Design Protein Engineering. ,vol. 7, pp. 385- 391 ,(1994) , 10.1093/PROTEIN/7.3.385
Todd J.A. Ewing, Shingo Makino, A. Geoffrey Skillman, Irwin D. Kuntz, DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases Journal of Computer-aided Molecular Design. ,vol. 15, pp. 411- 428 ,(2001) , 10.1023/A:1011115820450
Gennady M. Verkhivker, Djamal Bouzida, Daniel K. Gehlhaar, Paul A. Rejto, Sandra Arthurs, Anthony B. Colson, Stephan T. Freer, Veda Larson, Brock A. Luty, Tami Marrone, Peter W. Rose, Deciphering common failures in molecular docking of ligand-protein complexes. Journal of Computer-aided Molecular Design. ,vol. 14, pp. 731- 751 ,(2000) , 10.1023/A:1008158231558
Matthew D. Eldridge, Christopher W. Murray, Timothy R. Auton, Gaia V. Paolini, Roger P. Mee, Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. Journal of Computer-aided Molecular Design. ,vol. 11, pp. 425- 445 ,(1997) , 10.1023/A:1007996124545
Jacopo Tomasi, Maurizio Persico, Molecular Interactions in Solution: An Overview of Methods Based on Continuous Distributions of the Solvent Chemical Reviews. ,vol. 94, pp. 2027- 2094 ,(1994) , 10.1021/CR00031A013
Erin K. Bradley, Paul Beroza, Julie E. Penzotti, Peter D. J. Grootenhuis, David C. Spellmeyer, Jennifer L. Miller, A Rapid Computational Method for Lead Evolution: Description and Application to α1-Adrenergic Antagonists Journal of Medicinal Chemistry. ,vol. 43, pp. 2770- 2774 ,(2000) , 10.1021/JM990578N
Robert S. DeWitte, Eugene I. Shakhnovich, SMoG: de Novo Design Method Based on Simple, Fast, and Accurate Free Energy Estimates. 1. Methodology and Supporting Evidence Journal of the American Chemical Society. ,vol. 118, pp. 11733- 11744 ,(1996) , 10.1021/JA960751U