Origin and prediction of free-solution interaction studies performed label-free

Bornhop, Darryl J.; Kammer, Michael N.; Kussrow, Amanda; Flowers, Robert A.; Meiler, Jens

doi:10.1073/pnas.1515706113

Cited by 38 publications

(74 citation statements)

References 79 publications

(92 reference statements)

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“…In response to the letter submitted by Varma (1), we respectfully disagree with the assertion that our proposed free-solution response function (FreeSRF) model (2) does not explain the signal origin for free-solution measurements. His theoretical considerations are appreciated; however, as we have shown (2), they do not apply here.…”

contrasting

confidence: 63%

Reply to Varma: Elucidation of the signal origin for label-free, free-solution interactions

Bornhop¹,

Kammer²,

Kussrow³

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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In response to the letter submitted by Varma (1), we respectfully disagree with the assertion that our proposed free-solution response function (FreeSRF) model (2) does not explain the signal origin for free-solution measurements. His theoretical considerations are appreciated; however, as we have shown (2), they do not apply here.i) Our empirical model is informative, experimentally consistent, and a reasonable starting point for further elucidating interferometric free-solution, label-free assays. Our approach exhibits a strong correlation (Spearman's rank) between signal magnitude with binding-induced conformation and hydration changes. This correlation held true for a diverse set of binding pairs, ranging widely in affinity and molecular mass. FreeSRF is supported by the published modeling literature that substantiates the use of radius of gyration, R gyr , and solvent-accessible surface area (SASA) as physical parameters to represent intrinsic solution property changes for protein-ligand binding (3, 4). Marsh and Teichmann (4) validate our use of avgSASA in χ, showing it provides an excellent estimation of structural change upon binding. Because SASA also correlates with the amplitude of conformational change, it is reasonable to ascribe the refractive index (RI) signal to this property. We do admit that the dependence on structural and dynamical parameters may be more complex than our linear fit model, so an expanded model may emerge for predicting RI changes in free-solution measurements. ii) Having a large constant term is not reason to discount the validity of an expression, particularly if the physical parameters used in the equation vary widely with respect to the intrinsic property being measured. Although suitable currently, we do anticipate the emergence of a better definition for "E" (the error or disturbance term). iii) Varma's approach, using the Maxwell-Garnett formulation (1), and that used by others (5, 6) predicted ΔRI signal for protein-ligand binding to be below the detection limit (DL) for BSI. This observation is not disputed (2), because we also predicted undetectable binding signals by BSI (<5 × 10 −7 ) using a widely accepted relationship (7) for refractive index increment (RII) calculations (equations S13-S17 and figures S2 and S3 of ref.2). However, quantification of the actual ΔRI signal produced for a binding pair ( (8) and (c) the effect of the medium on the dielectric constant of the protein (and vice versa) (9) is ignored.We conclude that the currently accepted model (5-7) does not accurately predict the signal for freesolution RI measurements. FreeSRF considers hydration and conformation changes and is predictive of both magnitude and directionality for the relative RI change. We hope the "difficulties in replicating BSI experiments" (5, 6) can be reconciled, allowing its successful use, as others have independently shown (10, 11).

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contrasting

confidence: 63%

Reply to Varma: Elucidation of the signal origin for label-free, free-solution interactions

Bornhop¹,

Kammer²,

Kussrow³

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…The medium is water. The effective permittivity of the solution ε eff based on Maxwell‐Garnett effective medium theory can be written as:

n_{eff} = \sqrt{ε_{italiceff}} = n_{d} + \frac{3}{2} n_{d} f_{a} ((), \frac{ε_{a} - ε_{d}}{ε_{a} + 2 ε_{d}})

…”

Section: Impact Of Solute Concentration On the Reflectivity And The Dmentioning

confidence: 99%

Modeling of surface plasmon resonance nanobiosensor with the transverse resonance method

Borghol

Aguili

2019

Int J RF Microw Comput Aided Eng

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This article describes a new approach for the detection and identification of a molecular interaction in real‐time and non‐label with surface plasmon resonance (SPR). This approach is based on the transverse resonance method, modeling the nanobiosensor by an equivalent circuit that allows studying the dispersion characteristics of surface plasmon and the reflectivity. The results obtained from these two studies show that the dispersive study is very precise than the reflectivity one to determine the presence and nature of molecular interactions.

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“…In the first approach, values of radius of gyration (R g ) were obtained from the supporting information provided with 6 . The volumes were approximated to using the relation = M w (Da).…”

Section: S-6mentioning

confidence: 99%

Detection Limit for Optically Sensing Specific Protein Interactions in Free-solution

Sasikumar¹,

Varma²

2017

Preprint

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Optical molecular sensing techniques are often limited by the refractive index change associated with the probed interactions. In this work, we present a closed form analytical model to estimate the magnitude of optical refractive index change arising from protein-protein interactions. The model, based on the Maxwell Garnett effective medium theory and first order chemical kinetics serves as a general framework for estimating the detection limits of optical sensing of molecular interactions. The model is applicable to situations where one interacting species is immobilized to a surface, as commonly done, or to emerging techniques such as Back-Scattering Interferometry (BSI) where both interacting species are un-tethered. Our findings from this model point to the strong role of as yet unidentified factors in the origin of the BSI signal resulting in significant deviation from linear optical response.

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Origin and prediction of free-solution interaction studies performed label-free

Cited by 38 publications

References 79 publications

Reply to Varma: Elucidation of the signal origin for label-free, free-solution interactions

Reply to Varma: Elucidation of the signal origin for label-free, free-solution interactions

Modeling of surface plasmon resonance nanobiosensor with the transverse resonance method

Detection Limit for Optically Sensing Specific Protein Interactions in Free-solution

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