Abstract
Affinity maturation and rational design have a raised importance in the application of nanobody (VHH), and its unique structure guaranteed these processes quickly done in vitro. An anti-CD47 nanobody, Nb02, was screened via a synthetic phage display library with 278 nM of KD value. In this study, a new strategy based on homology modeling and Rational Mutation Hotspots Design Protocol (RMHDP) was presented for building a fast and efficient platform for nanobody affinity maturation. A three-dimensional analytical structural model of Nb02 was constructed and then docked with the antigen, the CD47 extracellular domain (CD47ext). Mutants with high binding affinity are predicted by the scoring of nanobody-antigen complexes based on molecular dynamics trajectories and simulation. Ultimately, an improved mutant with an 87.4-fold affinity (3.2 nM) and 7.36 °C higher thermal stability was obtained. These findings might contribute to computational affinity maturation of nanobodies via homology modeling using the recent advancements in computational power. The add-in of aromatic residues which formed aromatic-aromatic interaction plays a pivotal role in affinity and thermostability improvement. In a word, the methods used in this study might provide a reference for rapid and efficient in vitro affinity maturation of nanobodies.
Highlights
CD47 molecule, a ubiquitous cell-surface receptor that promotes immune evasion by interacting with signal-regulatory protein alpha (SIRPα) [1], is a member of immunoglobulin (Ig) superfamily and is considered as a promising cancer biomarker [2]
The structure of Nb02 was modeled by homology modeling using MODELLER v9.19
The fast and efficient approach designed in this study, which uses homologous modeling structure in ADAPT platform to screen multiple mutations, is useful for increasing the binding affinity of a phage display VHH while enhancing stability
Summary
CD47 molecule, a ubiquitous cell-surface receptor that promotes immune evasion by interacting with signal-regulatory protein alpha (SIRPα) [1], is a member of immunoglobulin (Ig) superfamily and is considered as a promising cancer biomarker [2]. Targeted blocking CD47-SIRPα interaction for engaging macrophages to attack cancer cells represents a potentially promising immunotherapeutic strategy. We had screened a panel of single anti-CD47 nanobodies from a semi-synthetic library via Phage display technology (submitted work), and the optimal one (Nb02) was chosen as the parental VHH in this study. Some strategies about affinity optimization were undertaken previously to improve the binding affinity and stability of biotherapeutics [9,10,11,12]. Given the time-consuming process of conventional approach and improved computational capabilities, structure-based computational methods involved the in silico selection of promising candidates with a high likelihood of improving binding affinity has aroused considerable interest [13,14,15,16,17]
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