Binding free energies for nicotine analogs inhibiting cytochrome P450 2A6 by a combined use of molecular dynamics simulations and QM/MM-PBSA calculations

Lu, Hai-Ting; Huang, Xiaoqin; AbdulHameed, Mohamed Diwan M.; Chen, Zhan

doi:10.1016/j.bmc.2014.02.037

Cited by 18 publications

(13 citation statements)

References 49 publications

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“…We used this approach to estimate binding of ligands to cathepsin B, but found that QM/MM-PBSA energies ( r 2 = 0.59) were worse than gas-phase QM energies ( r 2 = 0.80) [85] . However more recently, accurate QM/MM-PBSA results have been obtained for cytochrome P450 [86] , showing that performance depends on the system.…”

Section: Replacing MM With Qmmentioning

confidence: 99%

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

Genheden

Ryde

2015

Expert Opinion on Drug Discovery

3,574

2,390

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Introduction: The molecular mechanics energies combined with the Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor–ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success. Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results.

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Section: Replacing MM With Qmmentioning

confidence: 99%

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

Genheden

Ryde

2015

Expert Opinion on Drug Discovery

3,574

2,390

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“…Zhan and co-workers have used a similar approach for metalloenzymes. − They combined pseudobond QM/MM energies with PBSA solvation, using RESP charges from the QM/MM calculation, and an entropy term from a simple count of the number of rotable bonds lost during the binding and the number of water molecules displaced by the ligand. They used the B3LYP density functional with either the 6-31G* or 6-31+G* basis set for the ligand and the metal ion(s), together with their first-sphere ligands, as well as a few nearby residues.…”

Section: End-point Approachesmentioning

confidence: 99%

Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods

2016

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One of the largest challenges of computational chemistry is calculation of accurate free energies for the binding of a small molecule to a biological macromolecule, which has immense implications in drug development. It is well-known that standard molecular-mechanics force fields used in most such calculations have a limited accuracy. Therefore, there has been a great interest in improving the estimates using quantum-mechanical (QM) methods. We review here approaches involving explicit QM energies to calculate binding affinities, with an emphasis on the methods, rather than on specific applications. Many different QM methods have been employed, ranging from semiempirical QM calculations, via density-functional theory, to strict coupled-cluster calculations. Dispersion and other empirical corrections are mandatory for the approximate methods, as well as large basis sets for the stricter methods. QM has been used for the ligand, for a few crucial groups around the ligand, for all the closest atoms (200-1000 atoms), or for the full receptor-ligand complex, but it is likely that with a proper embedding it might be enough to include all groups within ∼6 Å of the ligand. Approaches involving minimized structures, simulations of the end states of the binding reaction, or full free-energy simulations have been tested.

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“…Their analysis showed that BPA-A was the strongest binder to the receptor (Starovoytov et al, 2014 ). Other similar studies include globin, for its catalytic mechanism in the hydrolysis of substituted phenyl hexanoates (Ercan et al, 2014 ), the role of conserved residues in substrate binding to Brassica rapa auxin amidohydrolase (Smolko et al, 2016 ), the effect of hydrophobic interactions in substrate binding to recombinant enzyme carboxylesterase (Shao et al, 2014 ), the substrate-enzyme interactions of endo-1,4-β-xylanase (Zhan et al, 2014 ), azoreductase protein for the biodegradation of azo dyes (Dehghanian et al, 2016 ; Haghshenas et al, 2016 ), cytochrome P450 2A6 for nicotine addiction (Lu et al, 2014 ), Cel48F for producing bioethanol via fiber degradation (Qian M. D. et al, 2016 ), rubisco for biofuel production (Siqueira et al, 2016 ), streptavidin-biotin complex in biochemical sensing (Liu F. J. et al, 2016 ), sorotidine 5-monophosphate decarboxylase for its impressive rate enhancement (Jamshidi et al, 2014 ), tyrosyl-tRNA synthetases for genetic encoding of unnatural amino acids (Ren et al, 2015 ), T7 RNA polymerase for generating RNA labels (Borkotoky et al, 2016 ), AF9 in the YEATS family for the recognition of H3K9ac (Wang Q. et al, 2016 ), cysteine protease 1 precursor from Zea for the hydrolysate of corn gluten meal (Liu et al, 2014 ), folate receptor alpha for producing milk with high folate concentration (Sahoo et al, 2014c ), and both acid amido synthetase (Wang X. et al, 2015 ) and brassinosteroid (Lei et al, 2015 ) for plant growth.…”

Section: Applications Of Mmpbsamentioning

confidence: 99%

Recent Developments and Applications of the MMPBSA Method

Wang

Greene

Xiao

et al. 2018

Front. Mol. Biosci.

474

327

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The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

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Binding free energies for nicotine analogs inhibiting cytochrome P450 2A6 by a combined use of molecular dynamics simulations and QM/MM-PBSA calculations

Cited by 18 publications

References 49 publications

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods

Recent Developments and Applications of the MMPBSA Method

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