An integrated computational pipeline for designing high-affinity nanobodies with expanded genetic codes
An integrated computational pipeline for designing high-affinity nanobodies with expanded genetic codes
复制标题
用于设计具有扩展遗传密码的高亲和力纳米体的集成计算管道
DOI:
10.1093/bib/bbab338
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发表时间:
2021
影响因子:
9.5
通讯作者:
Kam Y J Zhang
中科院分区:
文献类型:
--
作者:
Aditya K Padhi;Ashutosh Kumar;Ken-ichi Haruna;Haruna Sato;Hiroko Tamura;Satoru Nagatoishi;Kouhei Tsumoto;Atushi Yamaguchi;Fumie Iraha;Mihoko Takahashi;Kensaku Sakamoto;Kam Y J Zhang
Protein engineering and design principles employing the 20 standard amino acids have been extensively used to achieve stable protein scaffolds and deliver their specific activities. Although this confers some advantages, it often restricts the sequence, chemical space, and ultimately the functional diversity of proteins. Moreover, although site-specific incorporation of non-natural amino acids (nnAAs) has been proven to be a valuable strategy in protein engineering and therapeutics development, its utility in the affinity-maturation of nanobodies is not fully explored. Besides, current experimental methods do not routinely employ nnAAs due to their enormous library size and infinite combinations. To address this, we have developed an integrated computational pipeline employing structure-based protein design methodologies, molecular dynamics simulations and free energy calculations, for the binding affinity prediction of an nnAA-incorporated nanobody toward its target and selection of potent binders. We show that by incorporating halogenated tyrosines, the affinity of 9G8 nanobody can be improved toward epidermal growth factor receptor (EGFR), a crucial cancer target. Surface plasmon resonance (SPR) assays showed that the binding of several 3-chloro-l-tyrosine (3MY)-incorporated nanobodies were improved up to 6-fold into a picomolar range, and the computationally estimated binding affinities shared a Pearson’srof 0.87 with SPR results. The improved affinity was found to be due to enhanced van der Waals interactions of key 3MY-proximate nanobody residues with EGFR, and an overall increase in the nanobody’s structural stability. In conclusion, we show that our method can facilitate screening large libraries and predict potent site-specific nnAA-incorporated nanobody binders against crucial disease-targets.
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DOI:
--
发表时间:
2009
期刊:
Structure 17
影响因子:
--
作者:
Sakamoto;K.;Murayama;K.;Oki;K.;Iraha;F.;Kato-Murayama;M.;Takahashi;M.;Ohtake;K.;Kobayashi;T.;Kuramitsu;S.;Shirouzu;M.;Yokoyama S.
通讯作者:
Yokoyama S.
影响因子:
15
作者:
Kim CH;Axup JY;Dubrovska A;Kazane SA;Hutchins BA;Wold ED;Smider VV;Schultz PG
通讯作者:
Schultz PG
影响因子:
5.6
作者:
Wang, W;Kollman, PA
通讯作者:
Kollman, PA
影响因子:
5.7
作者:
Schmitz, Karl R.;Bagchi, Atrish;Roovers, Rob C.;Henegouwen, Paul M. P. van Bergen En;Ferguson, Kathryn M.
通讯作者:
Ferguson, Kathryn M.
影响因子:
4.6
作者:
Ohtake K;Yamaguchi A;Mukai T;Kashimura H;Hirano N;Haruki M;Kohashi S;Yamagishi K;Murayama K;Tomabechi Y;Itagaki T;Akasaka R;Kawazoe M;Takemoto C;Shirouzu M;Yokoyama S;Sakamoto K
通讯作者:
Sakamoto K