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Comparative analysis of nanobody sequence and structure data
- Source :
- Proteins
- Publication Year :
- 2018
- Publisher :
- Wiley, 2018.
-
Abstract
- Nanobodies are a class of antigen‐binding protein derived from camelids that achieve comparable binding affinities and specificities to classical antibodies, despite comprising only a single 15 kDa variable domain. Their reduced size makes them an exciting target molecule with which we can explore the molecular code that underpins binding specificity—how is such high specificity achieved? Here, we use a novel dataset of 90 nonredundant, protein‐binding nanobodies with antigen‐bound crystal structures to address this question. To provide a baseline for comparison we construct an analogous set of classical antibodies, allowing us to probe how nanobodies achieve high specificity binding with a dramatically reduced sequence space. Our analysis reveals that nanobodies do not diversify their framework region to compensate for the loss of the VL domain. In addition to the previously reported increase in H3 loop length, we find that nanobodies create diversity by drawing their paratope regions from a significantly larger set of aligned sequence positions, and by exhibiting greater structural variation in their H1 and H2 loops.
- Subjects :
- Models, Molecular
0301 basic medicine
single domain antibody
Protein Conformation
VHH
Sequence alignment
Computational biology
Biochemistry
Antibodies
Structural variation
HcAb
Structure-Activity Relationship
03 medical and health sciences
0302 clinical medicine
Protein structure
framework
Antibody Specificity
Structural Biology
antibody
Framework region
Molecular Biology
Research Articles
Physics
heavy chain antibody
Heavy-chain antibody
biology
loop
Single-Domain Antibodies
030104 developmental biology
Single-domain antibody
biology.protein
camelid
Paratope
Binding Sites, Antibody
Sequence space (evolution)
Sequence Alignment
VH
030217 neurology & neurosurgery
Research Article
Subjects
Details
- ISSN :
- 08873585
- Volume :
- 86
- Database :
- OpenAIRE
- Journal :
- Proteins: Structure, Function, and Bioinformatics
- Accession number :
- edsair.doi.dedup.....f7abfda8cbd0349f9478b6ddf839c047
- Full Text :
- https://doi.org/10.1002/prot.25497