Normal mode analysis as a prerequisite for drug design: Application to matrix metalloproteinases inhibitors

Floquet, Nicolas; Maréchal, Jean‐Didier; Badet‐Denisot, Marie‐Ange; Robert, Charles H.; Dauchez, Manuel; Pérahia, David

doi:10.1016/j.febslet.2006.08.037

Cited by 62 publications

(62 citation statements)

References 32 publications

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“…13 To generate realistic motions/conformers along the computed NM, we used the same minimization approach as described in other recent papers. [16][17][18][19] NMs were computed on each of the three conformations as defined above; low-energy conformers were generated for each one along the 20 lowest-frequency NMs in the mass-weighted rootmean-square (MRMS) range − 3 Å to + 3 Å (60 minimized structures for each studied mode). For a detailed description of MRMS, please see Materials and Methods.…”

Section: Collective Motions Of the G-protein Hetero-trimermentioning

confidence: 99%

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A Concerted Mechanism for Opening the GDP Binding Pocket and Release of the Nucleotide in Hetero-Trimeric G-Proteins

Louet

Pérahia

Martinez

et al. 2011

Journal of Molecular Biology

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Section: Collective Motions Of the G-protein Hetero-trimermentioning

confidence: 99%

“…One possibility to circumvent this problem is to generate energy-minimized structures along the so-identified directions as described in previous studies. [16][17][18][19] Such a protocol was shown efficient in building sets of protein conformations useful for protein/ligand docking experiments, 18 Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

A Concerted Mechanism for Opening the GDP Binding Pocket and Release of the Nucleotide in Hetero-Trimeric G-Proteins

Louet

Pérahia

Martinez

et al. 2011

Journal of Molecular Biology

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“…On the other hand, modeling of receptor flexibility is still a challenging problem due to the need of large conformational space that must be sampled. In order to overcome this challenge, multiple receptor conformations (MRCs) are generated in several ways: (i) using multiple conformations from molecular dynamics (MD) snapshots, [8][9][10][11][12][13] (ii) applying principal component analysis to MD trajectories, 14 (iii) using the snapshots based on geometrybased simulation techniques, 15 (iv) detecting rigid and hinge regions with the Gaussian Network Model and the Elastic Network Model (ENM), respectively, 16,17 (v) perturbing receptor conformations along different normal modes directions, [18][19][20][21] (vi) using normal modes as additional flexible variables during docking simulations, [22][23][24][25] and (vii) using multiple structures of the protein receptor obtained from experimental studies, for example X-ray crystallography or NMR analysis. [26][27][28] The majority of these types of approaches are very computationally intensive.…”

Section: Introductionmentioning

confidence: 99%

A flexible docking scheme to explore the binding selectivity of PDZ domains

Gerek

Ozkan

2010

Protein Science

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Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å . We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

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“…They are insensitive to structural details or underlying force field, but defined by the overall architecture, or topology of interresidue contacts in the native structure (16,(19)(20). Applications of NMA are becoming increasingly popular in modeling protein-drug interactions (21)(22)(23).…”

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confidence: 99%

The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding

Bakan

Bahar

2009

Proc. Natl. Acad. Sci. U.S.A.

259

285

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The conformational flexibility of target proteins continues to be a major challenge in accurate modeling of protein-inhibitor interactions. A fundamental issue, yet to be clarified, is whether the observed conformational changes are controlled by the protein or induced by the inhibitor. Although the concept of induced fit has been widely adopted for describing the structural changes that accompany ligand binding, there is growing evidence in support of the dominance of proteins' intrinsic dynamics which has been evolutionarily optimized to accommodate its functional interactions. The wealth of structural data for target proteins in the presence of different ligands now permits us to make a critical assessment of the balance between these two effects in selecting the bound forms. We focused on three widely studied drug targets, HIV-1 reverse transcriptase, p38 MAP kinase, and cyclin-dependent kinase 2. A total of 292 structures determined for these enzymes in the presence of different inhibitors and unbound form permitted us to perform an extensive comparative analysis of the conformational space accessed upon ligand binding, and its relation to the intrinsic dynamics before ligand binding as predicted by elastic network model analysis. Our results show that the ligand selects the conformer that best matches its structural and dynamic properties among the conformers intrinsically accessible to the protein in the unliganded form. The results suggest that simple but robust rules encoded in the protein structure play a dominant role in predefining the mechanisms of ligand binding, which may be advantageously exploited in designing inhibitors.anisotropic network model ͉ conformational flexibility ͉ ensemble of structures ͉ pre-existing equilibrium ͉ principal component analysis T he dynamic nature of proteins plays a critical role in molecular recognition. Understanding the determinants of ligandrecognition and -binding dynamics is a major challenge with impact on drug discovery. Yet, progress in this field has been impeded by the complexity and specificity of interactions, the multiplicity of conformations accessible under equilibrium conditions, and insufficient data on the structure and energetics of protein-ligand interactions.Two different models have been proposed for explaining the conformational changes observed between the bound and unbound forms of proteins. The classical view, which dates back to the original work of Koshland in 1958, proposes an induced fit mechanism whereby ligand binding induces conformational changes on the target protein. Such an onset of conformational changes could be plausible on a local scale, i.e., slight rearrangements in side chain reorientations or even transitions between isomeric states could be triggered by the ligand. However, the more cooperative changes observed in other complexes, including concerted rearrangements of entire domains, have challenged this classical concept. The second, alternate view, pioneered by Monod, Wyman, and Changeux (MWC model), has gained broad ...

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Normal mode analysis as a prerequisite for drug design: Application to matrix metalloproteinases inhibitors

Cited by 62 publications

References 32 publications

A Concerted Mechanism for Opening the GDP Binding Pocket and Release of the Nucleotide in Hetero-Trimeric G-Proteins

A Concerted Mechanism for Opening the GDP Binding Pocket and Release of the Nucleotide in Hetero-Trimeric G-Proteins

A flexible docking scheme to explore the binding selectivity of PDZ domains

The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding

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