Processing Multimode Binding Situations in Simulation-Based Prediction of Ligand−Macromolecule Affinities

Khandelwal, Akash; Lukáčová, Viera; Kroll, D. M.; Raha, Soumyendu; Çömez, Doğan; Baláž, Štefan

doi:10.1021/jp051105x

Cited by 5 publications

(9 citation statements)

References 51 publications

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“…The most likely possibilities are either described by complexes 2Cm and 2Em or 2Az and 2Bz or 2Fz. However, it is unlike that binding of 2 is a multimodal process 64, 75. Direct interactions with the C‐terminus should be negligible for all complexes, but 2Fz.…”

Section: Discussionmentioning

confidence: 94%

“…Complexes were considered relevant binding modes in the discussion below only if their average LIE score less one standard deviation was smaller (or more stable) than the lowest average LIE plus one standard deviation within the same ligand‐structural model pair. Only binding modes with the lowest intrinsic binding free energies (or highest partial association constant) will contribute significantly to the measured inhibition constants 64, 75…”

Section: Resultsmentioning

confidence: 99%

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Flexibility and inhibitor binding in cdc25 phosphatases

Arantes

2010

Proteins

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Cdc25 phosphatases involved in cell cycle checkpoints are now active targets for the development of anti-cancer therapies. Rational drug design would certainly benefit from detailed structural information for Cdc25s. However, only apo- or sulfate-bound crystal structures of the Cdc25 catalytic domain have been described so far. Together with previously available crystalographic data, results from molecular dynamics simulations, bioinformatic analysis, and computer-generated conformational ensembles shown here indicate that the last 30-40 residues in the C-terminus of Cdc25B are partially unfolded or disordered in solution. The effect of C-terminal flexibility upon binding of two potent small molecule inhibitors to Cdc25B is then analyzed by using three structural models with variable levels of flexibility, including an equilibrium distributed ensemble of Cdc25B backbone conformations. The three Cdc25B structural models are used in combination with flexible docking, clustering, and calculation of binding free energies by the linear interaction energy approximation to construct and validate Cdc25B-inhibitor complexes. Two binding sites are identified on top and beside the Cdc25B active site. The diversity of interaction modes found increases with receptor flexibility. Backbone flexibility allows the formation of transient cavities or compact hydrophobic units on the surface of the stable, folded protein core that are unexposed or unavailable for ligand binding in rigid and densely packed crystal structures. The present results may help to speculate on the mechanisms of small molecule complexation to partially unfolded or locally disordered proteins.

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Section: Discussionmentioning

confidence: 94%

Section: Resultsmentioning

confidence: 99%

Flexibility and inhibitor binding in cdc25 phosphatases

Arantes

2010

Proteins

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“…The computation details were described previously [18,22]. Briefly, the protocol consisted of: (1) FlexX docking of the ligands to the processed structure of MMP-9 taken from the Protein Data Bank [30] (file 1GKC [31]), with the pose selected primarily on the basis of acceptable distances between the catalytic zinc and the hydroxamate atoms; (2) QM/MM minimization of the selected poses, with the QM region including the ligand, tha catalytic zinc, Glu402 and the His triad as shown in Figure 1; (3) (Table S1).…”

Section: Computational Protocolmentioning

confidence: 99%

“…Some ligands exhibit extensive movements and need much longer MD simulations to equilibrate than the rest of compounds. To reduce the cost, these ligands can be included in the LR correlations by treating them as assuming several binding modes, as described in our multi-mode (mm) approach [22].…”

Section: Introductionmentioning

confidence: 99%

Improved estimation of ligand–macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods

Khandelwal

Baláž

2007

J Comput Aided Mol Des

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Structure-based predictions of binding affinities of ligands binding to proteins by coordination bonds with transition metals, covalent bonds, and bonds involving charge re-distributions are hindered by the absence of proper force fields. This shortcoming affects all methods which use force-field-based molecular simulation data on complex formation for affinity predictions. One of the most frequently used methods in this category is the Linear Response (LR) approach of Åquist, correlating binding affinities with van der Waals and electrostatic energies, as extended by Jorgensen's inclusion of solvent-accessible surface areas. All these terms represent the differences, upon binding, in the ensemble averages of pertinent quantities, obtained from molecular dynamics (MD) or Monte Carlo simulations of the complex and of single components. Here we report a modification of the LR approach by: (1) the replacement of the two energy terms through the single-point QM/MM energy of the time-averaged complex structure from an MD simulation; and (2) a rigorous consideration of multiple modes (mm) of binding. The first extension alleviates the force-field related problems, while the second extension deals with the ligands exhibiting large-scale motions in the course of an MD simulation. The second modification results in the correlation equation that is nonlinear in optimized coefficients, but does not lead to an increase in the number of optimized coefficients. The application of the resulting mm QM/MM LR approach to the inhibition of zinc-dependent gelatinase B (matrix metalloproteinase 9) by 28 hydroxamate ligands indicates a significant improvement of descriptive and predictive abilities.

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“…The k = 1 in eq 6 in these cases. Sometimes, MD simulations oscillate between two or more states and the correlations can be improved by considering multiple binding modes, as demonstrated for 28 inhibitors of matrix metalloproteinase 9 [84]. …”

Section: Introductionmentioning

confidence: 99%

Rigorous Incorporation of Tautomers, Ionization Species, and Different Binding Modes into Ligand-Based and Receptor-Based 3D-QSAR Methods

Natesan¹,

Baláž²

2013

CPD

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Speciation of drug candidates and receptors caused by ionization, tautomerism, and/or covalent hydration complicates ligand- and receptor-based predictions of binding affinities by 3-dimensional structure-activity relationships (3D-QSAR). The speciation problem is exacerbated by tendency of tautomers to bind in multiple conformations or orientations (modes) in the same binding site. New forms of the 3D-QSAR correlation equations, capable of capturing this complexity, can be developed using the time hierarchy of all steps that lie behind the monitored biological process – binding, enzyme inhibition or receptor activity. In most cases, reversible interconversions of individual ligand and receptor species can be treated as quickly established equilibria because they are finished in a small fraction of the exposure time that is used to determine biological effects. The speciation equilibria are satisfactorily approximated by invariant fractions of individual ligand and receptor species for buffered experimental or in vivo conditions. For such situations, the observed drug-receptor association constant of a ligand is expressed as the sum of products, for each ligand and receptor species pair, of the association microconstant and the fractions of involved species. For multiple binding modes, each microconstant is expressed as the sum of microconstants of individual modes. This master equation leads to new 3D-QSAR correlation equations integrating the results of all molecular simulations or calculations, which are run for each ligand-receptor species pair separately. The multispecies, multimode 3D-QSAR approach is illustrated by a ligand-based correlation of transthyretin binding of thyroxine analogs and by a receptor-based correlation of inhibition of MK2 by benzothiophenes and pyrrolopyrimidines.

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Processing Multimode Binding Situations in Simulation-Based Prediction of Ligand−Macromolecule Affinities

Cited by 5 publications

References 51 publications

Flexibility and inhibitor binding in cdc25 phosphatases

Flexibility and inhibitor binding in cdc25 phosphatases

Improved estimation of ligand–macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods

Rigorous Incorporation of Tautomers, Ionization Species, and Different Binding Modes into Ligand-Based and Receptor-Based 3D-QSAR Methods

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