Antibody Modeling Assessment

Creative Biolabs provides professional antibody modeling assessment services for antibody modeling. With our most devoted scientists, we are confident to deliver you the comprehensive and professional assessment to meet your project development.

Antibody Homology Model

The three-dimensional (3D) structure of antibodies offers an understanding of their function and evolution, and assists in drug design and optimization. When an experimental structure is unavailable, the antibody’s 3D structure is usually obtained through comparative modeling, also known as homology modeling, as well as via de novo computational methods. Commonly, there are four steps to construct a homology model: template selection, template–target sequence alignment, model building, and model evaluation. Besides, many sequence alignment tools and protein structure databases are available to meet the task, such as the Protein Data Bank (PDB), which has more than 1000 crystal structures of antibody fragments (Fab or Fv).

Antibody Structure

The antigen-binding sites of antibodies are made up of six loops, also called “complementarity-determining regions (CDRs), three from the light chain (VL) and three from the heavy chain (VH). The framework regions (FRs) which are outside these loops are extremely conserved in both sequence and main-chain conformation and they are able to be accurately predicted by homology modeling method. Among the CDRs, five assume a limited number of main-chain conformations, named “canonical structures.” However, the sixth loop, CDR-H3, is highly variable in sequence and conformation, and has not been fully categorized.

Fig 1. Sketch map of the average rmsd values for all models from CCG, Accelrys and PIGS. (Almagro, J. C., 2011)

At present, numerous methods are available for antibody modeling. Creative Biolabs offers antibody modeling assessment service to help you obtain the optimal antibody models.

Antibody Modeling Assessment

To assess an antibody model, a series of elements should be taken into consideration, including the canonical structures, Carbonyl RMSD, VL/VH tilt angle, Cis-trans isomers, and CDR-H3. Generally, there are two major criteria to assess the quality and accuracy of the models: Molprobity profile and rmsd values determined for different segments of the Fvs after overlaying a different variety of backbone atoms of these or other segments of the models and the corresponding benchmark structures.

• MolProbity Server

The MolProbity server offers a group of metrics to assess the quality of experimental structures of proteins and nucleic acids. Now, these metrics were used to estimate protein models generated at CASP8. From the metrics MolProbity offers, we utilize the clash score, which refers to the number of unfavorable all-atom steric overlaps at >0.4 Å per1000 atoms; the percentage of backbone conformations in the favored Ramachandran region; as well as Molprobity score which integrate clash score, percentage of side-chain conformations classed as rotamer outliers, and the percentage of backbone Ramachandran conformations outside the favored region.

Fig 2. Part A and B shows the quality of CASD-NMR2010 Structures. A: Molprobity, and B: Procheck-all Z-score values. (Rosato, A., 2012)

• RMSD Values

Except for Molprobilty as a global metric to evaluate the quality of the models, we also compared the models with the structures to assess the backbone structure of different regions of the Fv. We subjected the available duplicate Fv crystal structure conformers to the same rmsd analysis as the computational models. The presence of additional crystallographic structures in the asymmetric unit offers an assessment of the structural variability of given antibodies with identical sequence but in different environments.

Fig 3. Root mean square deviation analysis. (Bernardi, R. C., 2014)

References

1. Almagro, J. C., (2011). “Antibody modeling assessment.” Proteins: Structure, Function, and Bioinformatics, 79(11), 3050-3066.
2. Teplyakov, A., Luo, J., (2014). “Antibody modeling assessment II. Structures and models.” Proteins: Structure, Function, and Bioinformatics, 82(8), 1563-1582.
3. Bernardi, R. C., (2014). “Molecular dynamics study of enhanced Man5B enzymatic activity.” Biotechnology for biofuels, 7(1), 83.
4. Rosato, A., (2012). “Blind testing of routine, fully automated determination of protein structures from NMR data.” Structure, 20(2), 227-236.

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