CIDCA   05380
CENTRO DE INVESTIGACION Y DESARROLLO EN CRIOTECNOLOGIA DE ALIMENTOS
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Structural modeling of an anti-transglutaminase antibody and analysis of its binding mode to transglutaminase using blind rigid-body protein-protein docking
Lugar:
Quilmes
Reunión:
Congreso; 1er Congreso Argentino de Bioinformática y Biología Computacional (CAB2C; 2010
Institución organizadora:
Sociedad Argentina de Bioinformatica
Resumen:
Background
Human tissue transglutaminase (htTG) is an enzyme that plays an important role in blood coagulation.
Incidentially, it is the main auto-antigen of Celiac disease patients; therefore serum
reactivity against it is one of the main indicators of Celiac disease[6].
We cloned and sequenced a murine monoclonal antibody against htTG. In order to gain knowledge
regarding the antibody-antigen binding mode and the nature of the contact surface, we
proceeded to perform molecular modeling of its variable domains, followed by blind, rigid-body
protein-protein docking against the antigens crystallized protein structure.
Modeling
The modeling of the variable zones of the antibody heterodimer was done by homology modeling
for the structurally conserved zones. For the complementary determining regions (CDRs)
that define the antibody specificity (and for which there are almost never reliable templates to
derive the structure from), two independent approaches were carried out: ab initio loop refinement
using Modeller[4], and knowledge-based assessment of loop conformations using the canonical
structures[7] method as implemented by Rosetta[2].
Rigid body protein protein docking
These structures were used to perform rigid body docking simulations against the crystallized
htTG structure (PDBID 1KV3A) using ZDOCK[1].
Results show that, for both modeling methods, there is a clear energy funnel in score vs rmsd
plots that show a consensual and highly favored binding mode, suggesting binding specificity. In
contrast, two negative control antibodies not only yielded lower binding energy scores, but also
top-scoring decoys lacked similarity, as judged by their large mutual rmsd values.
Clustering and residue-residue contact map
Average residue-residue contact maps were calculated. First, all 50.000 decoys of each model were
clustered into groups using the k-medoids clustering algorithm. A contact map for each member
of the top 2 scoring clusters was done by means of Voronois polyhedra method[5] and averaged
within each cluster.
The resulting maps show that there is a high similarity among the contact surfaces of different
models. Moreover, the antigen binding zone corresponds very closely with the antibodys epitope,
as previously determined using phage display[3]. This confirms that both the modeling and docking
procedures faithfully represent their molecular entities and that further residue-residue contact
information can be extracted from this models, which may guide the design of potential single or
multi-point mutants with increased affinity.
References
[1] Rong Chen, Li Li, and Zhiping Weng. ZDOCK: an initial-stage protein-docking algorithm.
Proteins, 52(1):807, 2003.
[2] Rhiju Das and David Baker. Macromolecular modeling with rosetta. Annual review of biochemistry,
77:36382, 2008.
[3] Roberto Di Niro, Fortunato Ferrara, Tarcisio Not, Andrew R M Bradbury, Fernando Chirdo,
Roberto Marzari, and Daniele Sblattero. Characterizing monoclonal antibody epitopes by
filtered gene fragment phage display. The Biochemical journal, 388(Pt 3):88994, June 2005.
[4] Narayanan Eswar, Ben Webb, Marc A Marti-Renom, M S Madhusudhan, David Eramian,
Min-Yi Shen, Ursula Pieper, and Andrej Sali. Comparative protein structure modeling using
MODELLER. Current protocols in protein science / editorial board, John E. Coligan ... [et
al.], Chapter 2:Unit 2.9, 2007.
[5] Tiffany B Fischer, J Bradley Holmes, Ian R Miller, Jerod R Parsons, Leon Tung, James C
Hu, and Jerry Tsai. Assessing methods for identifying pair-wise atomic contacts across binding
interfaces. Journal of structural biology, 153(2):10312, 2006.
[6] S Reif. Tissue transglutaminasethe key player in celiac disease: a review. Autoimmunity
Reviews, 3(1):4045, 2004.
[7] Arvind Sivasubramanian, Aroop Sircar, Sidhartha Chaudhury, and Jeffrey J Gray. Toward
high-resolution homology modeling of antibody Fv regions and application to antibody-antigen
docking. Proteins, 74(2):497514, 2009.
2