Structural insight to elucidate the binding specificity of the anti-cortisol Fab fragment with glucocorticoids

Eronen, Veikko; Tullila, Antti; Iljin, Kristiina; Rouvinen, Juha; Nevanen, Tarja K.; Hakulinen, Nina

doi:10.1016/j.jsb.2023.107966

Cited by 4 publications

(14 citation statements)

References 30 publications

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“… 1 Average value obtained from three technical replicates. R1 Determined in this work. R2 Determined in our previous work N.D., not determined …”

Section: Resultsmentioning

confidence: 98%

“…Based on the previously determined crystal structures, the hapten is almost entirely embedded in the paratope of the anti-cortisol (17) Fab fragment . Cortisol has been observed to have extensive hydrophobic interactions together with four hydrogen bonds with the paratope.…”

Section: Resultsmentioning

confidence: 99%

“…The carbonyl oxygen O3 of cortisol forms a hydrogen bond with the side chain of Arg56-H, while the oxygen atoms of hydroxyl groups OH11, OH17, and OH21 are hydrogen-bonded to the carbonyl oxygen of Arg91-L, to the carbonyl oxygen of Tyr-59-H, and to the side chain of Asp61-H, respectively (Figure ). The crystal structures of anti-cortisol (17) Fab in complex with cortisol, prednisolone, cortisone, and corticosterone show similar binding modes . Based on the solved crystal structures, other steroids can be modeled into the binding site.…”

Section: Resultsmentioning

confidence: 99%

“…For instance, cortisol is a biomarker for numerous diseases, such as Cushing’s disease, chronic fatigue, and Addison’s disease . However, due to the shared cortisol structure originating from steroidogenesis (Figure ), high specificity is hard to obtain with biomolecular recognition elements such as antisteroid antibodies. − Recently, we have reported the crystal structure of an anti-cortisol (17) Fab with and without cortisol as well as in complex with three other glucocorticoids, prednisolone, cortisone, and corticosterone . Of these ligands, the anti-cortisol (17) Fab showed the highest affinity toward cortisol, measured by surface plasmon resonance (SPR).…”

Section: Introductionmentioning

confidence: 99%

“…5−8 Recently, we have reported the crystal structure of an anti-cortisol (17) Fab with and without cortisol as well as in complex with three other glucocorticoids, prednisolone, cortisone, and corticosterone. 9 Of these ligands, the anticortisol (17) Fab showed the highest affinity toward cortisol, measured by surface plasmon resonance (SPR). For diagnostic usage, a major disadvantage of anti-cortisol (17) Fab is its high cross-reactivity to prednisolone, which is a commonly used glucocorticoid drug.…”

Section: ■ Introductionmentioning

confidence: 99%

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Robust Approach for Quantifying Glucocorticoid Binding to the Anti-Cortisol Fab Fragment via Native Mass Spectrometry

Eronen,

Iljin,

Pääkkönen

et al. 2024

ACS Omega

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In the development of proteins, aptamers, and molecular imprints for diagnostic purposes, a major goal is to obtain a molecule with both a high binding affinity and specificity for the target ligand. Cushing syndrome or Addison’s disease can be diagnosed by cortisol level tests. We have previously characterized and solved the crystal structure of an anti-cortisol (17) Fab fragment having a high affinity to cortisol but also significant cross-reactivity to other glucocorticoids, especially the glucocorticoid drug prednisolone. We used native mass spectrometry (MS) to determine the binding affinities of nine steroid hormones to anti-cortisol (17) Fab, including steroidogenic precursors of cortisol. Based on the results, the number of hydroxyl groups in the structure of a steroid ligand plays a key role in the antigen recognition by the Fab fragment as the ligands with three hydroxyl groups, cortisol and prednisolone, had the highest affinities. The antibody affinity toward steroid hormones often decreases with a decrease in the number of hydroxyl groups in the structure. The presence of the hydroxyl group at position C11 increased the affinity more than did the other hydroxyl groups at positions C17 or C21. The binding affinities obtained by native MS were compared to the values determined by surface plasmon resonance (SPR), and the affinities were found to correlate well between these two techniques. Our study demonstrates that native MS with a large dynamic range and high sensitivity is a versatile tool for ligand binding studies of proteins.

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“… 1 Average value obtained from three technical replicates. R1 Determined in this work. R2 Determined in our previous work N.D., not determined …”

Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Robust Approach for Quantifying Glucocorticoid Binding to the Anti-Cortisol Fab Fragment via Native Mass Spectrometry

Eronen,

Iljin,

Pääkkönen

et al. 2024

ACS Omega

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Reduced graphene oxide electrodes meet lateral flow assays: A promising path to advanced point-of-care diagnostics

Calucho,

Álvarez-Diduk,

Piper

et al. 2024

Biosensors and Bioelectronics

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Efficient Generation of Protein Pockets with PocketGen

Zhang,

Shen,

Liu

et al. 2024

Preprint

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Designing small-molecule-binding proteins, such as enzymes and biosensors, is crucial in protein biology and bioengineering. Generating high-fidelity protein pockets—areas where proteins interact with ligand molecules—is challenging due to complex interactions between ligand molecules and proteins, flexibility of ligand molecules and amino acid side chains, and complex sequence-structure dependencies. Here, we introduce PocketGen, a deep generative method for generating the residue sequence and the full-atom structure within the protein pocket region that leverages sequence-structure consistency. PocketGen consists of a bilevel graph transformer for structural encoding and a sequence refinement module that uses a protein language model (pLM) for sequence prediction. The bilevel graph transformer captures interactions at multiple granularities (atom-level and residue/ligand-level) and aspects (intra-protein and protein-ligand) with bilevel attention mechanisms. For sequence refinement, a structural adapter using cross-attention is integrated into a pLM to ensure structure-sequence consistency. During training, only the adapter is fine-tuned, while the other layers of the pLM remain unchanged. Experiments show that PocketGen can efficiently generate protein pockets with higher binding affinity and validity than state-of-the-art methods. PocketGen is ten times faster than physics-based methods and achieves a 95% success rate (percentage of generated pockets with higher binding affinity than reference pockets) with over 64% amino acid recovery rate.

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Structural insight to elucidate the binding specificity of the anti-cortisol Fab fragment with glucocorticoids

Cited by 4 publications

References 30 publications

Robust Approach for Quantifying Glucocorticoid Binding to the Anti-Cortisol Fab Fragment via Native Mass Spectrometry

Robust Approach for Quantifying Glucocorticoid Binding to the Anti-Cortisol Fab Fragment via Native Mass Spectrometry

Reduced graphene oxide electrodes meet lateral flow assays: A promising path to advanced point-of-care diagnostics

Efficient Generation of Protein Pockets with PocketGen

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