| 研究課題/領域番号 |
18F18074
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| 研究機関 | 国立研究開発法人理化学研究所 |
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研究代表者 |
ZHANG KAM 国立研究開発法人理化学研究所, 生命機能科学研究センター, チームリーダー (60558906)
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| 研究分担者 |
PADHI ADITYA 国立研究開発法人理化学研究所, 生命機能科学研究センター, 外国人特別研究員
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| 研究期間 (年度) |
2018-10-12 – 2021-03-31
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| キーワード | Unnatural amino acid / Nanobodies |
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| 研究実績の概要 |
Protein engineering and design employing the twenty natural amino acids have been extensively used in the production of stable protein scaffolds and in the affinity maturation of therapeutic proteins. While this confer some advantages, it often restricts the sequence and chemical space, and ultimately limiting the functional diversity of proteins. Among a plethora of applications, although site-specific incorporation of non-canonical amino acids (ncAAs) has proven to be a valuable strategy in protein engineering and therapeutics development, it’s utility in improving the affinity of protein-protein interactions is not fully explored. Moreover, current experimental methods often exclude the use of ncAAs due to their enormous library size and due to an infinite possibility of ncAA-based combinations. To address this, we have developed an integrated computational pipeline employing structure-based protein design methodologies, molecular dynamics (MD) simulations, free energy calculations and in cerebro approaches to quickly predict potent ncAA-conjugated binders. We show that by incorporating 3-chloro-L-tyrosine at multiple sites, the affinity of 9G8 nanobody can be substantially improved towards epidermal growth factor receptor (EGFR), a crucial target for many cancers. In conclusion, we show that our method can facilitate screening large libraries of ncAAs and predict potent site-specific ncAA incorporated binders against crucial disease targets.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We tested our computational pipeline by considering one of the key cancer-causing proteins, EGFR targeted with 9G8 nanobody incorporated with ncAAs. Specifically, tyrosine residues in 9G8 nanobody were substituted with 3-chloro-L-tyrosines (3MY) at 11 positions with a total of 1023 3MY-incorporated nanobody models consisting of 11 single mutants, 55 double mutants, 165 triple mutants, 330 quadruple mutants and 462 quintuple mutants. Several 3MY-incorporated nanobody designs were shortlisted based on types of intermolecular interactions using PRODIGY and PPCheck, followed by MOE and Rosetta based protein design approaches related to Unary Quadratic Optimization (UQO) and physicochemical approaches respectively. A final rank order and shortlisting based on MD simulations and free energy of binding suggested ~30 designs that could improve the affinity towards EGFR. Biophysical characterization and surface plasmon resonance (SPR) measurements of the computationally selected 3MY-incorporated 9G8 nanobody revealed that several designs have improved their affinity towards EGFR than the wild-type, with the best one being up to six-folds than the wild-type (in low picomolar affinity), thus, validating our computational method.
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| 今後の研究の推進方策 |
i.Our results demonstrate that structure-based computational design approach can be used to improve the affinity of other crucial therapeutic proteins conjugated with ncAAs. To demonstrate this, we plan to introduce several halogenated tyrosine modifications and azido-phenylalanine into inhibitory nanobodies such as MU375, MU551 and MU1053 that target CD38, which is a cell surface antigen highly expressed in several malignancies including multiple myeloma and chronic lymphoid leukemia.
ii.Binding energies will be calculated for ~698 systems (combinations up to quintuple mutants) for CD38-nanobody complexes and potential affinity-maturation designs will be shortlisted and rank-ordered using our computational pipeline.
To gain further structural and molecular insights, biophysical assays including SPR, ITC and MST will be carried out. X-ray crystallographic studies are also planned for the computationally shortlisted ncAA-incorporated EGFR-nanobody and CD38-nanobody designed complexes to gain further knowledge on inhibition mechanisms.
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