Open AccessModiBodies: A computational method for modifying nanobodies in nanobody-antigen complexes to improve binding affinity and specificity
Author(s) -
Aysima Hacisuleyman,
Burak Erman
Publication year - 2020
Publication title -
journal of biological physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 46
eISSN - 1573-0689
pISSN - 0092-0606
DOI - 10.1007/s10867-020-09548-3
Subject(s) - single domain antibody , protein data bank (rcsb pdb) , computational biology , complementarity determining region , structural biology , complementarity (molecular biology) , chemistry , biology , computer science , antibody , biochemistry , genetics , immunoglobulin light chain
Nanobodies are special derivatives of antibodies, which consist of single domain fragments. They have become of considerable interest as next-generation biotechnological tools for antigen recognition. They can be easily engineered due to their high stability and compact size. Nanobodies have three complementarity-determining regions, CDRs, which are enlarged to provide a similar binding surface to that of human immunoglobulins. Here, we propose a benchmark testing algorithm that uses 3D structures of already existing protein-nanobody complexes as initial structures followed by successive mutations on the CDR domains. The aim is to find optimum binding amino acids for hypervariable residues of CDRs. We use molecular dynamics simulations to compare the binding energies of the resulting complexes with that of the known complex and accept those that are improved by mutations. We use the MDM4-VH9 complex, (PDB id 2VYR), fructose-bisphosphate aldolase from Trypanosoma congolense (PDB id 5O0W) and human lysozyme (PDB id 4I0C) as benchmark complexes. By using this algorithm, better binding nanobodies can be generated in a short amount of time. We suggest that this method can complement existing immune and synthetic library-based methods, without a need for extensive experimentation or large libraries.