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PDBsum entry 1ovh
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* Residue conservation analysis
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Enzyme class:
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E.C.3.2.1.17
- lysozyme.
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Reaction:
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Hydrolysis of the 1,4-beta-linkages between N-acetyl-D-glucosamine and N-acetylmuramic acid in peptidoglycan heteropolymers of the prokaryotes cell walls.
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DOI no:
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J Mol Biol
337:1161-1182
(2004)
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PubMed id:
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Testing a flexible-receptor docking algorithm in a model binding site.
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B.Q.Wei,
L.H.Weaver,
A.M.Ferrari,
B.W.Matthews,
B.K.Shoichet.
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ABSTRACT
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Sampling receptor flexibility is challenging for database docking. We consider a
method that treats multiple flexible regions of the binding site independently,
recombining them to generate different discrete conformations. This algorithm
scales linearly rather than exponentially with the receptor's degrees of
freedom. The method was first evaluated for its ability to identify known
ligands of a hydrophobic cavity mutant of T4 lysozyme (L99A). Some 200000
molecules of the Available Chemical Directory (ACD) were docked against an
ensemble of cavity conformations. Surprisingly, the enrichment of known ligands
from among a much larger number of decoys in the ACD was worse than simply
docking to the apo conformation alone. Large decoys, accommodated in the larger
cavity conformations sampled in the ensemble, were ranked better than known
small ligands. The calculation was redone with an energy correction term that
considered the cost of forming the larger cavity conformations. Enrichment
improved, as did the balance between high-ranking large and small ligands. In a
second retrospective test, the ACD was docked against a conformational ensemble
of thymidylate synthase. Compared to docking against individual enzyme
conformations, the flexible receptor docking approach improved enrichment of
known ligands. Including a receptor conformational energy weighting term
improved enrichment further. To test the method prospectively, the ACD database
was docked against another cavity mutant of lysozyme (L99A/M102Q). A total of 18
new compounds predicted to bind this polar cavity and to change its conformation
were tested experimentally; 14 were found to bind. The bound structures for
seven ligands were determined by X-ray crystallography. The predicted geometries
of these ligands all corresponded to the observed geometries to within 0.7A RMSD
or better. Significant conformational changes of the cavity were observed in all
seven complexes. In five structures, part of the observed accommodations were
correctly predicted; in two structures, the receptor conformational changes were
unanticipated and thus never sampled. These results suggest that although
sampling receptor flexibility can lead to novel ligands that would have been
missed when docking a rigid structure, it is also important to consider receptor
conformational energy.
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Selected figure(s)
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Figure 6.
Figure 6. Stereo views of difference electron density maps
for seven ligands bound to L99A/M102Q. a, 2-n-Propyl aniline; b,
2-allyl-6-methyl phenol; c, 3-fluoro-2-methyl aniline; d,
2-allyl phenol; e, 2-chloro-6-methyl aniline; f,
4-fluorophenethyl alcohol; and g, N-allyl aniline. The
coefficients are (F[o] -F[c]), where the F[o] are the observed
structure amplitudes for the ligand-bound complex and the F[c]
and phases were calculated from the refined model with all atoms
removed from the cavity. Maps are contoured at +3s (continuous
lines) and -3s (broken lines).
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Figure 8.
Figure 8. Docking against the apo L99A/M102Q cavity (PDB
entry 1LGU) led to incorrect prediction of the binding geometry
of a, 2-chloro-6-methyl aniline and b, 3-fluoro-2-methyl
aniline. Color scheme is the same as in Figure 7. The pictures
are in stereo.
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The above figures are
reprinted
by permission from Elsevier:
J Mol Biol
(2004,
337,
1161-1182)
copyright 2004.
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Figures were
selected
by an automated process.
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Literature references that cite this PDB file's key reference
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PubMed id
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Reference
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F.Lauck,
C.A.Smith,
G.F.Friedland,
E.L.Humphris,
and
T.Kortemme
(2010).
RosettaBackrub--a web server for flexible backbone protein structure modeling and design.
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Nucleic Acids Res,
38,
W569-W575.
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I.Bahar,
T.R.Lezon,
A.Bakan,
and
I.H.Shrivastava
(2010).
Normal mode analysis of biomolecular structures: functional mechanisms of membrane proteins.
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Chem Rev,
110,
1463-1497.
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N.Brooijmans,
and
C.Humblet
(2010).
Chemical space sampling by different scoring functions and crystal structures.
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J Comput Aided Mol Des,
24,
433-447.
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R.E.Amaro,
and
W.W.Li
(2010).
Emerging methods for ensemble-based virtual screening.
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Curr Top Med Chem,
10,
3.
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S.Y.Huang,
and
X.Zou
(2010).
Advances and challenges in protein-ligand docking.
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Int J Mol Sci,
11,
3016-3034.
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A.N.Jain
(2009).
Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation.
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J Comput Aided Mol Des,
23,
355-374.
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C.Hartmann,
I.Antes,
and
T.Lengauer
(2009).
Docking and scoring with alternative side-chain conformations.
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Proteins,
74,
712-726.
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D.J.Huggins,
M.D.Altman,
and
B.Tidor
(2009).
Evaluation of an inverse molecular design algorithm in a model binding site.
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Proteins,
75,
168-186.
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D.L.Mobley,
and
K.A.Dill
(2009).
Binding of small-molecule ligands to proteins: "what you see" is not always "what you get".
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Structure,
17,
489-498.
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G.Bottegoni,
I.Kufareva,
M.Totrov,
and
R.Abagyan
(2009).
Four-dimensional docking: a fast and accurate account of discrete receptor flexibility in ligand docking.
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J Med Chem,
52,
397-406.
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G.D.Friedland,
N.A.Lakomek,
C.Griesinger,
J.Meiler,
and
T.Kortemme
(2009).
A correspondence between solution-state dynamics of an individual protein and the sequence and conformational diversity of its family.
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PLoS Comput Biol,
5,
e1000393.
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PDB code:
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H.Fan,
J.J.Irwin,
B.M.Webb,
G.Klebe,
B.K.Shoichet,
and
A.Sali
(2009).
Molecular docking screens using comparative models of proteins.
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J Chem Inf Model,
49,
2512-2527.
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J.L.Paulsen,
and
A.C.Anderson
(2009).
Scoring ensembles of docked protein:ligand interactions for virtual lead optimization.
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J Chem Inf Model,
49,
2813-2819.
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S.E.Boyce,
D.L.Mobley,
G.J.Rocklin,
A.P.Graves,
K.A.Dill,
and
B.K.Shoichet
(2009).
Predicting ligand binding affinity with alchemical free energy methods in a polar model binding site.
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J Mol Biol,
394,
747-763.
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PDB codes:
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A.P.Graves,
D.M.Shivakumar,
S.E.Boyce,
M.P.Jacobson,
D.A.Case,
and
B.K.Shoichet
(2008).
Rescoring docking hit lists for model cavity sites: predictions and experimental testing.
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J Mol Biol,
377,
914-934.
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PDB codes:
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J.Lee,
and
C.Seok
(2008).
A statistical rescoring scheme for protein-ligand docking: Consideration of entropic effect.
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Proteins,
70,
1074-1083.
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L.S.Cheng,
R.E.Amaro,
D.Xu,
W.W.Li,
P.W.Arzberger,
and
J.A.McCammon
(2008).
Ensemble-based virtual screening reveals potential novel antiviral compounds for avian influenza neuraminidase.
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J Med Chem,
51,
3878-3894.
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M.Totrov,
and
R.Abagyan
(2008).
Flexible ligand docking to multiple receptor conformations: a practical alternative.
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Curr Opin Struct Biol,
18,
178-184.
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N.Huang,
and
B.K.Shoichet
(2008).
Exploiting ordered waters in molecular docking.
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J Med Chem,
51,
4862-4865.
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N.Kamiya,
Y.Yonezawa,
H.Nakamura,
and
J.Higo
(2008).
Protein-inhibitor flexible docking by a multicanonical sampling: native complex structure with the lowest free energy and a free-energy barrier distinguishing the native complex from the others.
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Proteins,
70,
41-53.
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P.Cozzini,
G.E.Kellogg,
F.Spyrakis,
D.J.Abraham,
G.Costantino,
A.Emerson,
F.Fanelli,
H.Gohlke,
L.A.Kuhn,
G.M.Morris,
M.Orozco,
T.A.Pertinhez,
M.Rizzi,
and
C.A.Sotriffer
(2008).
Target flexibility: an emerging consideration in drug discovery and design.
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J Med Chem,
51,
6237-6255.
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R.Kim,
and
J.Skolnick
(2008).
Assessment of programs for ligand binding affinity prediction.
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J Comput Chem,
29,
1316-1331.
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S.Wong,
and
M.P.Jacobson
(2008).
Conformational selection in silico: loop latching motions and ligand binding in enzymes.
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Proteins,
71,
153-164.
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D.L.Mobley,
A.P.Graves,
J.D.Chodera,
A.C.McReynolds,
B.K.Shoichet,
and
K.A.Dill
(2007).
Predicting absolute ligand binding free energies to a simple model site.
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J Mol Biol,
371,
1118-1134.
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PDB codes:
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G.M.Verkhivker
(2007).
Computational proteomics of biomolecular interactions in the sequence and structure space of the tyrosine kinome: deciphering the molecular basis of the kinase inhibitors selectivity.
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Proteins,
66,
912-929.
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M.K.Gilson,
and
H.X.Zhou
(2007).
Calculation of protein-ligand binding affinities.
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Annu Rev Biophys Biomol Struct,
36,
21-42.
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S.Y.Huang,
and
X.Zou
(2007).
Efficient molecular docking of NMR structures: application to HIV-1 protease.
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Protein Sci,
16,
43-51.
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S.Y.Huang,
and
X.Zou
(2007).
Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking.
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Proteins,
66,
399-421.
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V.M.Popov,
W.A.Yee,
and
A.C.Anderson
(2007).
Towards in silico lead optimization: scores from ensembles of protein/ligand conformations reliably correlate with biological activity.
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Proteins,
66,
375-387.
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A.Ahmed,
and
H.Gohlke
(2006).
Multiscale modeling of macromolecular conformational changes combining concepts from rigidity and elastic network theory.
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Proteins,
63,
1038-1051.
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A.J.Orry,
R.A.Abagyan,
and
C.N.Cavasotto
(2006).
Structure-based development of target-specific compound libraries.
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Drug Discov Today,
11,
261-266.
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G.Klebe
(2006).
Virtual ligand screening: strategies, perspectives and limitations.
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Drug Discov Today,
11,
580-594.
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H.Alonso,
A.A.Bliznyuk,
and
J.E.Gready
(2006).
Combining docking and molecular dynamic simulations in drug design.
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Med Res Rev,
26,
531-568.
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M.Y.Mizutani,
Y.Takamatsu,
T.Ichinose,
K.Nakamura,
and
A.Itai
(2006).
Effective handling of induced-fit motion in flexible docking.
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Proteins,
63,
878-891.
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N.P.Todorov,
C.L.Buenemann,
and
I.L.Alberts
(2006).
De novo ligand design to an ensemble of protein structures.
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Proteins,
64,
43-59.
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R.Brenk,
S.W.Vetter,
S.E.Boyce,
D.B.Goodin,
and
B.K.Shoichet
(2006).
Probing molecular docking in a charged model binding site.
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J Mol Biol,
357,
1449-1470.
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PDB codes:
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X.Barril,
and
R.Soliva
(2006).
Molecular modelling.
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Mol Biosyst,
2,
660-681.
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A.P.Graves,
R.Brenk,
and
B.K.Shoichet
(2005).
Decoys for docking.
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J Med Chem,
48,
3714-3728.
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PDB code:
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C.Machicado,
J.López-Llano,
S.Cuesta-López,
M.Bueno,
and
J.Sancho
(2005).
Design of ligand binding to an engineered protein cavity using virtual screening and thermal up-shift evaluation.
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J Comput Aided Mol Des,
19,
421-443.
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D.M.Lorber,
and
B.K.Shoichet
(2005).
Hierarchical docking of databases of multiple ligand conformations.
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Curr Top Med Chem,
5,
739-749.
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R.Brenk,
J.J.Irwin,
and
B.K.Shoichet
(2005).
Here be dragons: docking and screening in an uncharted region of chemical space.
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J Biomol Screen,
10,
667-674.
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A.M.Ferrari,
B.Q.Wei,
L.Costantino,
and
B.K.Shoichet
(2004).
Soft docking and multiple receptor conformations in virtual screening.
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J Med Chem,
47,
5076-5084.
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The most recent references are shown first.
Citation data come partly from CiteXplore and partly
from an automated harvesting procedure. Note that this is likely to be
only a partial list as not all journals are covered by
either method. However, we are continually building up the citation data
so more and more references will be included with time.
Where a reference describes a PDB structure, the PDB
code is
shown on the right.
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