New general approach for determining the solution structure of a ligand bound weakly to a receptor: structure of a fibrinogen A?-like peptide bound to thrombin(S195A) obtained using NOE distance constraints and an ECEPP/3 flexible docking program

Maurer, Muriel C.; Trosset, Jean‐Yves; Lester, Cathy; DiBella, Elsie E.; Scheraga, Harold A.

doi:10.1002/(sici)1097-0134(19990101)34:1<29::aid-prot4>3.0.co;2-u

Cited by 24 publications

(20 citation statements)

References 75 publications

(171 reference statements)

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“…A harmonic force was imposed when the distance violation was more than the user-defined minimal distance, i.e., 5 Å for the first minimization steps and 3 Å for the following two minimization steps. If the violation was more than 2 Å from the minimal distance, the harmonic distance was replaced by a quasi-linear branch (29).…”

Section: Methodsmentioning

confidence: 99%

“…Mutational studies have revealed the mutual binding sites on IFN-␣2 and ifnar2. On IFN-␣2, ifnar2 binds to the A helix (residues 12-15), the AB loop (residues [26][27][28][29][30][31][32][33][34][35], and the E helix (residues 144-153) (7), whereas on ifnar2, IFN-␣2 binds to three loops of the N-terminal domain of the receptor (residues 45-52, 75-82, and 102-106) with no significant binding detected toward the Cterminal domain (8)(9)(10). Determination of the receptor-ligand structure will significantly promote our understanding of IFN signaling at the molecular level.…”

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confidence: 99%

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Structure of the interferon-receptor complex determined by distance constraints from double-mutant cycles and flexible docking

Roisman

Piehler

Trosset

et al. 2001

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

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The pleiotropic activity of type I interferons has been attributed to the specific interaction of IFN with the cell-surface receptor components ifnar1 and ifnar2. To date, the structure of IFN has been solved, but not that of the receptor or the complex. In this study, the structure of the IFN-␣2-ifnar2 complex was generated with a docking procedure, using nuclear Overhauser effect-like distance constraints obtained from double-mutant cycle experiments. The interaction free energy between 13 residues of the ligand and 11 of the receptor was measured by double-mutant cycles. Of the 100 pairwise interactions probed, five pairs of residues were found to interact. These five interactions were incorporated as distance constraints into the flexible docking program PRODOCK by using fixed and movable energy-gradient grids attached to the receptor and ligand, respectively. Multistart minimization and Monte Carlo minimization docking of IFN-␣2 onto ifnar2 converged to a welldefined average structure, with the five distance constraints being satisfied. Furthermore, no structural artifacts or intraloop energy strain were observed. The mutual binding sites on IFN-␣2 and ifnar2 predicted from the model showed an almost complete superposition with the ones determined from mutagenesis studies. Based on this structure, differences in IFN-␣2 versus IFN-␤ binding are discussed.protein-protein interaction ͉ PRODOCK ͉ Monte Carlo minimization ͉ grids T ype I interferons (IFNs) are a family of homologous cytokines that potently elicit an antiviral and antiproliferative state in cells. All human type I IFNs (IFN-␣, -␤, and -) bind to a cell surface receptor consisting of two transmembrane proteins, type I IFN receptor (ifnar) 1 (1) and ifnar2 (2), which associate upon binding. IFN binds with high affinity to ifnar2, probably recruiting ifnar1 subsequently. Type I IFNs belong to the class of helical cytokines and are built of five helices. The structures of human IFN-␣2 (3) and IFN-␤ have been resolved (4). The receptor structures are unknown, but can be modeled by homology to human cytokine receptors with known structures such as tissue factor (5) and IFN-␥ receptor (6). Mutational studies have revealed the mutual binding sites on IFN-␣2 and ifnar2. On IFN-␣2, ifnar2 binds to the A helix (residues 12-15), the AB loop (residues 26-35), and the E helix (residues 144-153) (7), whereas on ifnar2, IFN-␣2 binds to three loops of the N-terminal domain of the receptor (residues 45-52, 75-82, and 102-106) with no significant binding detected toward the Cterminal domain (8-10). Determination of the receptor-ligand structure will significantly promote our understanding of IFN signaling at the molecular level.Docking of protein complexes, and calculating the conformational changes that occur at the binding interface, is a computational challenge. Rigid protein docking software algorithms are fast and can be used to dock two proteins for which the NMR or x-ray structures have been solved independently (11, 12). However, successful docking relies o...

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Structure of the interferon-receptor complex determined by distance constraints from double-mutant cycles and flexible docking

Roisman

Piehler

Trosset

et al. 2001

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

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“…Limiting the conformational space using knowledge-based constraints is often crucial for successful peptide docking. The constraints may come from experiments (such as NOE data 80 ) or from previous knowledge of conserved positions for some of the peptide residues. [81][82][83] Scheraga and coworkers used a ''ligand-growing'' procedure.…”

Section: Structure-based Approaches For Peptide Design and Optimizationmentioning

confidence: 99%

“…It was applied to determine the structure of a fibrinogen A alike peptide bound to an active-site mutant of thrombin. 80 Schafroth and Floudas defined the pockets binding each of the peptide residues based on the known structure of the complex of a major histocompatibility complex (MHC) molecule HLA-DRB1*0101 with a cognate peptide, and used deterministic global optimization to dock MHC peptides. The pockets were predefined and considered to be independent of each other and the protein was considered to be rigid.…”

Section: Structure-based Approaches For Peptide Design and Optimizationmentioning

confidence: 99%

Peptidic modulators of protein‐protein interactions: Progress and challenges in computational design

Rubinstein

Niv

2009

Biopolymers

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With the decline in productivity of drug‐development efforts, novel approaches to rational drug design are being introduced and developed. Naturally occurring and synthetic peptides are emerging as novel promising compounds that can specifically and efficiently modulate signaling pathways in vitro and in vivo. We describe sequence‐based approaches that use peptides to mimic proteins in order to inhibit the interaction of the mimicked protein with its partners. We then discuss a structure‐based approach, in which protein‐peptide complex structures are used to rationally design and optimize peptidic inhibitors. We survey flexible peptide docking techniques and discuss current challenges and future directions in the rational design of peptidic inhibitors. © 2009 Wiley Periodicals, Inc. Biopolymers 91: 505–513, 2009.This article was originally published online as an accepted preprint. The “Published Online”date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com

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“…One approach to molecular docking is through descriptors of the surface shape5, 6 with provision for a limited degree of flexibility 4, 7, 8. A number of groups2, 3, 9–18 have utilized all‐atom models based on a molecular mechanics force field, with sampling of conformations by molecular mechanics, Monte Carlo, genetic algorithms, or distance embedding. More recent docking studies strive to include flexibility of the ligand and/or receptor.…”

Section: Introductionmentioning

confidence: 99%

Docking multiple conformations of a flexible ligand into a protein binding site using NMR restraints

Zabell

Post

2002

Proteins

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A method is described for docking a large, flexible ligand using intra-ligand conformational restraints from exchange-transferred NOE (etNOE) data. Numerous conformations of the ligand are generated in isolation, and a subset of representative conformations is selected. A crude model of the protein-ligand complex is used as a template for overlaying the selected ligand structures, and each complex is conformationally relaxed by molecular mechanics to optimize the interaction. Finally, the complexes were assessed for structural quality. Alternative approaches are described for the three steps of the method: generation of the initial docking template; selection of a subset of ligand conformations; and conformational sampling of the complex. The template is generated either by manual docking using interactive graphics or by a computational grid-based search of the binding site. A subset of conformations from the total number of peptides calculated in isolation is selected based on either low energy and satisfaction of the etNOE restraints, or a cluster analysis of the full set. To optimize the interactions in the complex, either a restrained Monte Carlo-energy minimization (MCM) protocol or a restrained simulated annealing (SA) protocol were used. This work produced 53 initial complexes of which 8 were assessed in detail. With the etNOE conformational restraints, all of the approaches provide reasonable models. The grid-based approach to generate an initial docking template allows a large volume to be sampled, and as a result, two distinct binding modes were identified for a fifteen-residue peptide binding to an enzyme active site.

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New general approach for determining the solution structure of a ligand bound weakly to a receptor: structure of a fibrinogen A?-like peptide bound to thrombin(S195A) obtained using NOE distance constraints and an ECEPP/3 flexible docking program

Cited by 24 publications

References 75 publications

Structure of the interferon-receptor complex determined by distance constraints from double-mutant cycles and flexible docking

Structure of the interferon-receptor complex determined by distance constraints from double-mutant cycles and flexible docking

Peptidic modulators of protein‐protein interactions: Progress and challenges in computational design

Docking multiple conformations of a flexible ligand into a protein binding site using NMR restraints

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