A Method for Predicting Individual Residue Contributions to Enzyme Specificity and Binding-site Energies, and Its Application to MTH1

Overview

Journal J Mol Model

Publisher Springer

Specialty Molecular Biology

Date 2016 Oct 8

PMID 27714533

Citations 5

Authors

James J P Stewart

Affiliations

Soon will be listed here.

Abstract

A new method for predicting the energy contributions to substrate binding and to specificity has been developed. Conventional global optimization methods do not permit the subtle effects responsible for these properties to be modeled with sufficient precision to allow confidence to be placed in the results, but by making simple alterations to the model, the precisions of the various energies involved can be improved from about ±2 kcal mol to ±0.1 kcal mol. This technique was applied to the oxidized nucleotide pyrophosphohydrolase enzyme MTH1. MTH1 is unusual in that the binding and reaction sites are well separated-an advantage from a computational chemistry perspective, as it allows the energetics involved in docking to be modeled without the need to consider any issues relating to reaction mechanisms. In this study, two types of energy terms were investigated: the noncovalent interactions between the binding site and the substrate, and those responsible for discriminating between the oxidized nucleotide 8-oxo-dGTP and the normal dGTP. Both of these were investigated using the semiempirical method PM7 in the program MOPAC. The contributions of the individual residues to both the binding energy and the specificity of MTH1 were calculated by simulating the effect of mutations. Where comparisons were possible, all calculated results were in agreement with experimental observations. This technique provides fresh insight into the binding mechanism that enzymes use for discriminating between possible substrates.

Citing Articles

A semiempirical method optimized for modeling proteins.

Stewart J, Stewart A J Mol Model. 2023; 29(9):284.

PMID: 37608199 PMC: 10444645. DOI: 10.1007/s00894-023-05695-1.

In Silico Study, Physicochemical, and In Vitro Lipase Inhibitory Activity of ,-Amyrenone Inclusion Complexes with Cyclodextrins.

Oliveira L, Menezes D, Da Silva V, Lourenco E, Miranda P, Silva M Int J Mol Sci. 2021; 22(18).

PMID: 34576044 PMC: 8468659. DOI: 10.3390/ijms22189882.

Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions.

Scantlebury J, Brown N, von Delft F, Deane C J Chem Inf Model. 2020; 60(8):3722-3730.

PMID: 32701288 PMC: 7611237. DOI: 10.1021/acs.jcim.0c00263.

An investigation into the applicability of the semiempirical method PM7 for modeling the catalytic mechanism in the enzyme chymotrypsin.

Stewart J J Mol Model. 2017; 23(5):154.

PMID: 28378242 PMC: 5380709. DOI: 10.1007/s00894-017-3326-8.

Combined Docking with Classical Force Field and Quantum Chemical Semiempirical Method PM7.

Sulimov A, Kutov D, Katkova E, Sulimov V Adv Bioinformatics. 2017; 2017:7167691.

PMID: 28191015 PMC: 5278191. DOI: 10.1155/2017/7167691.

References

Hayakawa H, Hofer A, Thelander L, Kitajima S, Cai Y, Oshiro S . Metabolic fate of oxidized guanine ribonucleotides in mammalian cells. Biochemistry. 1999; 38(12):3610-4. DOI: 10.1021/bi982361l. View

Berman H, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H . The Protein Data Bank. Nucleic Acids Res. 1999; 28(1):235-42. PMC: 102472. DOI: 10.1093/nar/28.1.235. View

Fujikawa K, Kamiya H, Yakushiji H, Nakabeppu Y, Kasai H . Human MTH1 protein hydrolyzes the oxidized ribonucleotide, 2-hydroxy-ATP. Nucleic Acids Res. 2001; 29(2):449-54. PMC: 29672. DOI: 10.1093/nar/29.2.449. View

Sakai Y, Furuichi M, Takahashi M, Mishima M, Iwai S, Shirakawa M . A molecular basis for the selective recognition of 2-hydroxy-dATP and 8-oxo-dGTP by human MTH1. J Biol Chem. 2002; 277(10):8579-87. DOI: 10.1074/jbc.M110566200. View

Friesner R, Banks J, Murphy R, Halgren T, Klicic J, Mainz D . Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem. 2004; 47(7):1739-49. DOI: 10.1021/jm0306430. View

Mishima M, Sakai Y, Itoh N, Kamiya H, Furuichi M, Takahashi M . Structure of human MTH1, a Nudix family hydrolase that selectively degrades oxidized purine nucleoside triphosphates. J Biol Chem. 2004; 279(32):33806-15. DOI: 10.1074/jbc.M402393200. View

Yu N, Yennawar H, Merz Jr K . Refinement of protein crystal structures using energy restraints derived from linear-scaling quantum mechanics. Acta Crystallogr D Biol Crystallogr. 2005; 61(Pt 3):322-32. DOI: 10.1107/S0907444904033669. View

Mooij W, Verdonk M . General and targeted statistical potentials for protein-ligand interactions. Proteins. 2005; 61(2):272-87. DOI: 10.1002/prot.20588. View

Jurecka P, Sponer J, cerny J, Hobza P . Benchmark database of accurate (MP2 and CCSD(T) complete basis set limit) interaction energies of small model complexes, DNA base pairs, and amino acid pairs. Phys Chem Chem Phys. 2006; 8(17):1985-93. DOI: 10.1039/b600027d. View

10.

Korb O, Stutzle T, Exner T . Empirical scoring functions for advanced protein-ligand docking with PLANTS. J Chem Inf Model. 2009; 49(1):84-96. DOI: 10.1021/ci800298z. View

11.

Trott O, Olson A . AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2009; 31(2):455-61. PMC: 3041641. DOI: 10.1002/jcc.21334. View

12.

Grimme S, Antony J, Ehrlich S, Krieg H . A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J Chem Phys. 2010; 132(15):154104. DOI: 10.1063/1.3382344. View

13.

Fanfrlik J, Bronowska A, rezac J, Prenosil O, Konvalinka J, Hobza P . A reliable docking/scoring scheme based on the semiempirical quantum mechanical PM6-DH2 method accurately covering dispersion and H-bonding: HIV-1 protease with 22 ligands. J Phys Chem B. 2010; 114(39):12666-78. DOI: 10.1021/jp1032965. View

14.

Dobes P, Fanfrlik J, rezac J, Otyepka M, Hobza P . Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors. J Comput Aided Mol Des. 2011; 25(3):223-35. DOI: 10.1007/s10822-011-9413-5. View

15.

Svensson L, Jemth A, Desroses M, Loseva O, Helleday T, Hogbom M . Crystal structure of human MTH1 and the 8-oxo-dGMP product complex. FEBS Lett. 2011; 585(16):2617-21. DOI: 10.1016/j.febslet.2011.07.017. View

16.

rezac J, Riley K, Hobza P . S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures. J Chem Theory Comput. 2011; 7(8):2427-2438. PMC: 3152974. DOI: 10.1021/ct2002946. View

17.

Hobza P . Calculations on noncovalent interactions and databases of benchmark interaction energies. Acc Chem Res. 2012; 45(4):663-72. DOI: 10.1021/ar200255p. View

18.

Stewart J . Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters. J Mol Model. 2012; 19(1):1-32. PMC: 3536963. DOI: 10.1007/s00894-012-1667-x. View

19.

Carvalho A, Barrozo A, Doron D, Kilshtain A, Major D, Kamerlin S . Challenges in computational studies of enzyme structure, function and dynamics. J Mol Graph Model. 2014; 54:62-79. DOI: 10.1016/j.jmgm.2014.09.003. View

20.

Brandon C, Martin B, McGee K, Stewart J, Braun-Sand S . An approach to creating a more realistic working model from a protein data bank entry. J Mol Model. 2015; 21(1):3. PMC: 4578224. DOI: 10.1007/s00894-014-2520-1. View