Protein Binders Specific for Immunoglobulin G from Different Species for Immunoassays and Multiplex Imaging

Jeong, Sukyo; Heu, Woosung; Kim, Jong Won; Kim, Kwang Ho

doi:10.1021/acs.analchem.6b03851

Cited by 9 publications

(11 citation statements)

References 36 publications

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“…As shown in our previous work (29), the original RbF4 strongly binds to hIgG 1 with a binding affinity of 128.7 nM, and weakly to mIgG 1 with an 8-fold weaker affinity than hIgG 1 (1 µM), whereas it has a negligible binding affinity for rIgG ( Fig. 3 and Fig.…”

Section: Resultssupporting

confidence: 78%

“…The FoldX scan suggests that S241M may substantially enhance the binding affinities for hIgG 1 and mIgG 1 . The mutation was also observed during the phage display affinity maturation for the mIgG 1 -specific repebody (29). We then fixed S241M and introduced all other amino acids in silico at S244.…”

Section: Resultsmentioning

confidence: 97%

“…As a proof of concept, in this work, a human IgG 1 (hIgG 1 )-binding repebody (RbF4) (28) was targeted for the binding mode prediction and affinity maturation without the structure determination. There is indirect evidence that RbF4 binds to the constant region of hIgG 1 (hFc) (28, 29), but actual epitopes and the binding mode were completely unknown. RbF4 has a typical LRR protein sequence motif, whose structural scaffold consists of three major parts: 1) an N terminal cap (LRRNT), 2) LRR modules (LRRVs), and 3) a C terminal cap (LRRCT) with an additional loop ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Based on the predicted binding mode, we redesigned RbF4 to mitigate its binding specificity. RbF4 was identified as highly specific for human IgG 1 , while showing weak and negligible cross-reactivities against mouse IgG 1 and rabbit IgG (28, 29). The predicted binding mode reveals that the loop ( Fig.…”

Section: Resultsmentioning

confidence: 99%

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Computer-guided Binding Mode Identification and Affinity Improvement of an LRR Protein Binder without Structure Determination

Choi

Jeong²,

Choi³

et al. 2019

Preprint

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27Binding affinity maturation without structure determination remains a difficult challenge in the 28 computer-aided protein engineering. Precise binding mode identification is a vital prerequisite for 29 the affinity maturation. However, pure computational methods have been unreliable in practice so 30 far and experimental structural biology techniques are generally too costly. Herein, we show that 31 computational epitope localization followed by the full-atom energy minimization with 32 intermediate experimental validation can yield precisely bound complex model structure, which 33 ultimately enables effective affinity maturation and redesign of binding specificity. As a proof-of-34 concept, we targeted a leucine-rich repeat (LRR) protein binder which specifically binds to the 35 human IgG1 (hIgG1). Based on the computationally predicted binding mode of the LRR protein 36 binder to hIgG1, the binding affinity of the protein binder was significantly increased and its 37 specificity was redesigned toward multiple IgGs from other species. Experimental determination 38 of the complex structure showed that the predicted model closely matched the X-ray crystal 39 structure. Through the benchmark of therapeutically relevant existing LRR protein complexes, we 40 demonstrate that the present approach can be broadly applicable to other proteins which undergo 41 small conformational changes upon binding. 42 43 Significance Statement 44 45Computer-aided design of binding affinity and specificity of two interacting proteins without 46 structural determination is a challenging problem in protein engineering. Despite recent advances 47 in the computational biology techniques, however, in silico evaluation of binding energies has 48 proven to be extremely difficult. We show that, in the cases of protein-protein interactions where 49 only small structural changes upon binding occur, partial experimental validation of binding can 50 greatly complement the computational energy. Using an LRR (leucine-rich repeat) protein binder 51 as a model system, the binding orientation of two binding partners was precisely dentified by the 52 hybrid approach. Based on the predicted model, we could successfully redesign the binding affinity 53 and specificity of the protein binder by the full-atom energy calculation. 54 55

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Section: Resultssupporting

confidence: 78%

Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Computer-guided Binding Mode Identification and Affinity Improvement of an LRR Protein Binder without Structure Determination

Choi

Jeong²,

Choi³

et al. 2019

Preprint

Self Cite

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show abstract

“…Here, a human IgG 1 (hIgG 1 )-binding repebody, named RbF4 [30], was targeted for computationally-driven binding mode identification and subsequent affinity improvement as well as redesign of binding specificity. There is indirect evidence that RbF4 recognizes the constant region of hIgG 1 (hFc) [30,31], but the actual epitope residues and the binding mode were unknown. RbF4 has a typical LRR protein sequence motif, whose structural scaffold consists of three major parts: an N terminal cap (LRRNT), LRR modules (LRRVs), and a C terminal cap (LRRCT) with an additional loop (S1 Fig).…”

Section: Binding Mode Identification Of An Lrr Protein Bindermentioning

confidence: 99%

Computer-guided binding mode identification and affinity improvement of an LRR protein binder without structure determination

et al. 2020

Self Cite

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Precise binding mode identification and subsequent affinity improvement without structure determination remain a challenge in the development of therapeutic proteins. However, relevant experimental techniques are generally quite costly, and purely computational methods have been unreliable. Here, we show that integrated computational and experimental epitope localization followed by full-atom energy minimization can yield an accurate complex model structure which ultimately enables effective affinity improvement and redesign of binding specificity. As proof-of-concept, we used a leucine-rich repeat (LRR) protein binder, called a repebody (Rb), that specifically recognizes human IgG 1 (hIgG 1). We performed computationally-guided identification of the Rb:hIgG 1 binding mode and leveraged the resulting model to reengineer the Rb so as to significantly increase its binding affinity for hIgG 1 as well as redesign its specificity toward multiple IgGs from other species. Experimental structure determination verified that our Rb:hIgG 1 model closely matched the co-crystal structure. Using a benchmark of other LRR protein complexes, we further demonstrated that the present approach may be broadly applicable to proteins undergoing relatively small conformational changes upon target binding.

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Genetically functionalized ferritin nanoparticles with a high-affinity protein binder for immunoassay and imaging

Kim

Heu

Jeong

et al. 2017

Analytica Chimica Acta

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Protein Binders Specific for Immunoglobulin G from Different Species for Immunoassays and Multiplex Imaging

Cited by 9 publications

References 36 publications

Computer-guided Binding Mode Identification and Affinity Improvement of an LRR Protein Binder without Structure Determination

Computer-guided Binding Mode Identification and Affinity Improvement of an LRR Protein Binder without Structure Determination

Computer-guided binding mode identification and affinity improvement of an LRR protein binder without structure determination

Genetically functionalized ferritin nanoparticles with a high-affinity protein binder for immunoassay and imaging

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