Analysis and Modeling of the Variable Region of Camelid Single Domain Antibodies

By Aroop Sircar, K. Sanni, Jiye Shi, Jeffrey J. Gray. 2011

92 citations recorded by the source corpus.

Camelids have a special type of Ab, known as heavy chain Abs, which are devoid of classical Ab light chains. Relative to classical Abs, camelid heavy chain Abs (cAbs) have comparable immunogenicity, Ag recognition diversity and binding affinities, higher stability and solubility, and better manufacturability, making them promising candidates for alternate therapeutic scaffolds. Rational engineering of cAbs to improve therapeutic function requires knowledge of the differences of sequence and structural features between cAbs and classical Abs. In this study, amino acid sequences of 27 cAb variable regions (VHH) were aligned with the respective regions of 54 classical Abs to detect amino acid differences, enabling automatic identification of cAb VHH CDRs. CDR analysis revealed that the H1 often (and sometimes the H2) adopts diverse conformations not classifiable by established canonical rules. Also, although the cAb H3 is much longer than classical H3 loops, it often contains common structural motifs and sometimes a disulfide bond to the H1. Leveraging these observations, we created a Monte Carlo-based cAb VHH structural modeling tool, where the CDR H1 and H2 loops exhibited a median root-mean-square deviation to natives of 3.1 and 1.5 Å, respectively. The protocol generated 8–12, 14–16, and 16–24 residue H3 loops with a median root-mean-square deviation to natives of 5.7, 4.5, and 6.8 Å, respectively. The large deviation of the predicted loops underscores the challenge in modeling such long loops. cAb VHH homology models can provide structural insights into interaction mechanisms to enable development of novel Abs for therapeutic and biotechnological use.

Subfields: Molecular Biology, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies (2022, background): “This nano-body features a 15-residue CDR3 loop that adopts the “ stretched-twist ” conformation 42 , in which the CDR3 loop bends to contact the framework residues that would otherwise be obstructed by a light chain in a paired antibody.”