Studying the characteristics of nanobody CDR regions based on sequence analysis in combination with 3D structures.

Background: Single-domain antibodies or nanobodies have recently attracted much attention in research and applications because of their great potential and advantage over conventional antibodies. However, isolation of candidate nanobodies in the lab has been costly and time-consuming. Screening of leading nanobody candidates through synthetic libraries is a promising alternative, but it requires prior knowledge to control the diversity of the complementarity-determining regions (CDRs) while still maintaining functionality. In this work, we identified sequence characteristics that could contribute to nanobody functionality by analyzing three datasets, CDR1, CDR2, and CDR3.

Results: By classification of amino acids based on physicochemical properties, we found that two different amino acid groups were sufficient for CDRs. The nonpolar group accounted for half of the total amino acid composition in these sequences. Observation of the highest occurrence of each amino acid revealed that the usage of some important amino acids such as tyrosine and serine was highly correlated with the length of the CDR3. Amino acid repeat motifs were also under-represented and highly restricted as 3-mers. Inspecting the crystallographic data also demonstrated conservation in structural coordinates of dominant amino acids such as methionine, isoleucine, valine, threonine, and tyrosine and certain positions in the CDR1, CDR2, and CDR3 sequences.

Conclusions: We identified sequence characteristics that contributed to functional nanobodies including amino acid groups, the occurrence of each kind of amino acids, and repeat patterns. These results provide a simple set of rules to make it easier to generate desired candidates by computational means; also, they can be used as a reference to evaluate synthetic nanobodies.