Abstract
MD simulations provide a powerful tool for the investigation of protein–drug complexes. The following chapter uses the aryl acylamidase–acetaminophen system as an example to describe a general protocol for preparing and running simulations of protein–drug complexes, complete with a step-by-step tutorial. The described approach is broadly applicable toward the study of drug interactions in the context of both biological targets and biosensing enzymes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lee EH, Hsin J, Sotomayor M, Comellas G, Schulten K (2009) Discovery through the computational microscope. Structure 17:1295–1306
Perilla JR, Goh BC, Keith Cassidy C, Bo L, Bernardi RC, Rudack T, Hang Y, Zhe W, Schulten K (2015) Molecular dynamics simulations of large macromolecular complexes. Curr Opin Struct Biol 31:64–74
Ebele AJ, Abdallah MA-E, Harrad S (2017) Pharmaceuticals and personal care products (PPCPs) in the freshwater aquatic environment. Emerging Contaminants 3(1):1–16
Banica F-G (2012) Chemical sensors and biosensors: fundamentals and applications. John Wiley & Sons, Chichester
Perilla JR, Hadden JA, Goh BC, Mayne CG, Schulten K (2016) All-atom molecular dynamics of virus capsids as drug targets. J Phys Chem Lett 7:1836–1844
Dart RC, Green JL (2016) The prescription paradox of acetaminophen safety. Pharmacoepidemiol Drug Saf 25(5):599–601
Hinson JA, Roberts DW, James LP (2010) Mechanisms of acetaminophen-induced liver necrosis. Handb Exp Pharmacol 196:369–405
Yoon E, Babar A, Choudhary M, Kutner M, Pyrsopoulos N (2016) Acetaminophen-induced hepatotoxicity: a comprehensive update. J Clin Transl Hepatol 4(2):131
Michael Bulger, Jan Holinsky (2014) Acetaminophen assay. US Patent 8,715,952, 6 May 2014
Hammond PM, Scawen MD, Tony Atkinson RSC, Price CP (1984) Development of an enzyme-based assay for acetaminophen. Anal Biochem 143(1):152–157
Morris HC, Overton PD, Richard Ramsay J, Stewart Campbell R, Hammond PM, Atkinson T, Price CP (1990) Development and validation of an automated enzyme assay for paracetamol (acetaminophen). Clin Chim Acta 187(2):95–104
Vaughan PA, Scott LDL, McAller JF (1991) Amperometric biosensor for the rapid determination of acetaminophen in whole blood. Anal Chim Acta 248(2):361–365
Lee S, Park E-H, Ko H-J, Bang WG, Kim H-Y, Kim KH, Choi IG (2015) Crystal structure analysis of a bacterial aryl acylamidase belonging to the amidase signature enzyme family. Biochem Biophys Res Commun 467(2):268–274
Humphrey W, Dalke A, Schulten K (1996) VMD–visual molecular dynamics. J Mol Graph 14(1):33–38
Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26:1781–1802
Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen M-y, Pieper U, Sali A (2006) Comparative protein structure modeling using MODELLER. Cur Protoc Bioinformatics. https://doi.org/10.1002/0471250953.bi0506s15
Das R, Baker D (2008) Macromolecular modeling with ROSETTA. Annu Rev Biochem 77:363–382
Wriggers W (2010) Using situs for the integration of multi-resolution structures. Biophys Rev 2:21–27
Trabuco LG, Villa E, Mitra K, Frank J, Schulten K (2008) Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics. Structure 16:673–683
Goh BC, Hadden JA, Bernardi RC, Singharoy A, McGreevy R, Rudack T, Keith Cassidy C, Schulten K (2016) Computational methodologies for real-space structural refinement of large macromolecular complexes. Annu Rev Biophys 45:253–278
Trott O, Olson AJ (2010) Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31(2):455–461
Pagadala NS, Syed K, Tuszynski J (2017) Software for molecular docking: a review. Biophys Rev 9(2):91–102
Dolinsky TJ, Czodrowski P, Li H, Nielsen JE, Jensen JH, Klebe G, Baker NA (2007) PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations. Nucleic Acids Res 35(Web Server):W522–W525
Søndergaard CR, Olsson MHM, Rostkowski M l, Jensen JH (2011) Improved treatment of ligands and coupling effects in empirical calculation and rationalization of pKa values. J Chem Theory Comput 7(7):2284–2295
Ko M, Huang Y, Jankowska AM, Pape UJ, Tahiliani M, Bandukwala HS, An J, Lamperti ED, Koh KP, Ganetzky R, Shirley Liu X, Aravind L, Agarwal S, Maciejewski JP, Rao A (2010) Impaired hydroxylation of 5-methylcytosine in myeloid cancers with mutant TET2. Nature 468:839–843
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935
Onufriev A (2008) Implicit solvent models in molecular dynamics simulations: a brief overview. Annu Rep Comput Chem 4:125–137
MacKerell AD Jr, Bashford D, Bellott M, Dunbrack RL Jr, Evanseck JD et al (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102:3586–3616
MacKerell AD Jr, Feig M, Brooks CL (2004) Improved treatment of the protein backbone in empirical force fields. J Am Chem Soc 126:698–699
Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Developing and testing of a general amber force field. J Comput Chem 25(9):1157–1174
Vanommeslaeghe K, Hatcher E, Acharya C, Kundu S, Zhong S, Shim J, Darian E, Guvench O, Lopes P, Vorobyov I, MacKerell AD Jr (2010) CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J Comput Chem 31(4):671–690
Vanommeslaeghe K, MacKerell AD Jr (2012) Automation of the CHARMM general force field (CGenFF) I: bond perception and atom typing. J Chem Inf Model 52(12):3144–3154
Vanommeslaeghe K, Prabhu Raman E, MacKerell AD Jr (2012) Automation of the CHARMM general force field (CGenFF) II: assignment of bonded parameters and partial atomic charges. J Chem Inf Model 52(12):3155–3168
Maestro Release 2017-2: MacroModel, Schrödinger, LLC, New York, NY, 2017
Mayne CG, Saam J, Schulten K, Tajkhorshid E, Gumbart JC (2013) Rapid parameterization of small molecules using the force field toolkit. J Comput Chem 34:2757–2770
Acknowledgements
The authors acknowledge funding from the University of Delaware and the National Institutes of Health COBRE grant 5P30GM110758-04.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Hadden, J.A., Perilla, J.R. (2018). Molecular Dynamics Simulations of Protein–Drug Complexes: A Computational Protocol for Investigating the Interactions of Small-Molecule Therapeutics with Biological Targets and Biosensors. In: Gore, M., Jagtap, U. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 1762. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7756-7_13
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7756-7_13
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-7755-0
Online ISBN: 978-1-4939-7756-7
eBook Packages: Springer Protocols