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Antibody-antigen Complex Modeling

Creative Biolabs is an undisputed global leader in the rapidly emerging market of antibody structure modeling. Based on the well-established antibody structure modeling platform, we offer high-quality antibody-antigen complex modeling service to meet every customer’s special requirements.

Antibody-antigen Complex Structure

In order to develop antibodies used in medical devices and as drugs, the antibody requires high specificity and affinity to capture a biomarker or antigen. Nowadays, high-affinity antibodies are created via the mutation of amino acid residues at the antibody-antigen interface depended on structural data. However, the development of novel antibodies via experimental approaches generally needs significant time and effort. Thus, the development of a rapid computational approach for precisely predicting the structure of antibody-antigen complexes would be very powerful for the progress of novel high-affinity antibodies. Importantly, the prediction of an antibody-antigen complex structure needs to predict the position of the antigen bound to the CDR of the antibody, because the binding site of an antibody is almost limited to the CDR.

Antibody-antigen Complex ModelingFig 1. Schematic diagram of the predicted models of the complex of west Nile virus envelope protein DIII with neutralizing E16 antibody Fab. (Sircar, A., 2010)

At present, antibody-antigen complex modeling methods are available in Creative Biolabs. We offer antibody-antigen complex modeling service to help you obtain the optimal antibody-antigen complex models.

GB/SA Method

Generally, for an antibody-antigen complexes, electrostatic interactions are more dominant than hydrophobic interactions when contrast to other protein–protein complexes. Due to the interfaces between antibodies and antigens interact with the solvent when they are not in complex, the affinity of the complex enables to be evaluated through the difference between the free energy of the complex and the sum of the free energies of the two proteins in the apo-state. A simple approach for estimating electrostatic and solvation free energies is to utilize the continuum solvation model, computing the former electrostatic energy via the generalized Born (GB) approach and the latter hydration free energy from the solvent-accessible surface area (SA). This approach, called the GB/SA method, has been widely used to estimate binding affinities between proteins and ligands, and to predict protein-protein docking after filtering with a knowledge base score.

Antibody-antigen Complex Modeling

Our modeling service takes advantage of state-of-the-art docking software tools to discover the relative transformation and conformation of the antibody and antigen involved in energetically favorable complex formation. Importantly, our modeling service takes into consideration of the latest scientific knowledge of antibody–antigen interactions and conformational flexibility of the CDR region (especially the H3 loop).

  • Firstly, a rigid body global search is achieved and geometrically plausible antibody–antigen complex models are formed. In this process, user-defined restraints (obtained from experimental data) are used to limit the search space.
  • Secondly, the resulting models are scored and ranked through a scoring function, developed specifically for antibody systems.
  • Finally, the best-scored structures are clustered and representatives of the largest clusters selected for structural optimization by energy minimization before being presented to the customer.

With our high-quality antibody-antigen complex modeling service, the experienced scientists here at Creative Biolabs are dedicated to help you develop antibody structure models. We also provide other various services regarding antibody-antigen complex analysis. Please feel free to contact us for more information and a detailed quote.


  1. Sircar, A., (2010). “SnugDock: paratope structural optimization during antibody-antigen docking compensates for errors in antibody homology models.” PloS computational biology, 6(1), e1000644.
  2. Shimba, N., (2016). “Model Building of Antibody–Antigen Complex Structures Using GBSA Scores.” Journal of chemical information and modeling, 56(10), 2005-2012.
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