Solvation and desolvation dynamics in apomyoglobin folding monitored by time-resolved infrared spectroscopy

Solvation and desolvation dynamics around helices during the kinetic folding process of apomyoglobin (apoMb) were investigated by using time-resolved infrared (IR) spectroscopy based on continuous-flow rapid mixing devices and an IR microscope. The folding of apoMb can be described by the collapse and search mechanism, in which the initial collapse occurring within several hundreds of microseconds is followed by the search for the correct secondary and tertiary structures. The time-resolved IR measurements showed a significant increase in solvated helix possessing a component of amide I' at 1633 cm(-1) within 100 mus after initiating the folding by a pD jump from pD2.2 to 6.0. In contrast, there was a minor increase in buried helices having amide I' at 1652 cm(-1) in this time domain. The observations demonstrate that the initially collapsed conformation of apoMb possesses a large amount of solvated helices, and suggest that much water is retained inside the collapsed domain. The contents of solvated and buried helices decrease and increase, respectively, in the time domain after the collapse, showing that the stepwise desolvation around helices is associated with the conformational search process. Interestingly, the largest changes in solvated and buried helices were observed at the final rate-limiting step of the apoMb folding. The persistence of the solvated helix until the final stage of apoMb folding suggests that the dissociation of hydrogen bonds between water and main-chain amides contributes to the energy barrier in the rate-determining step of the folding.     

Thermodynamic analysis of biomolecular interactions.

Direct measurement of the thermodynamics of biomolecular interactions is now relatively easy. Interpretation of these thermodynamics in simple molecular terms is not. Recent work shows how the multiplicity of weak noncovalent interactions, and the inevitable enthalpy/entropy compensation that these interactions engender, lead to difficulties in teasing out the different components.     

Prediction of protein interactions is essential for studying biomolecular mechanisms

Structural characterization of protein interactions is essential for our ability to understand and modulate physiological processes. Computational approaches to modeling of protein complexes provide structural information that far exceeds capabilities of the existing experimental techniques. Protein structure prediction in general, and prediction of protein interactions in particular, has been revolutionized by the rapid progress in Deep Learning techniques. The work of Schweke et al. (Proteomics 2023, 23, 2200323) presents a community-wide study of an important problem of distinguishing physiological protein–protein complexes/interfaces (experimentally determined or modeled) from non-physiological ones. The authors designed and generated a large benchmark set of physiological and non-physiological homodimeric complexes, and evaluated a large set of scoring functions, as well as AlphaFold predictions, on their ability to discriminate the non-physiological interfaces. The problem of separating physiological interfaces from non-physiological ones is very difficult, largely due to the lack of a clear distinction between the two categories in a crowded environment inside a living cell. Still, the ability to identify key physiologically significant interfaces in the variety of possible configurations of a protein–protein complex is important. The study presents a major data resource and methodological development in this important direction for molecular and cellular biology.     

Microfluidics and the quantification of biomolecular interactions

Microfluidic systems under laminar flow conditions provide in-solution information about species size and binding affinities at very modest sample costs. Flow-induced dispersion analysis directly measures the spread of the analyte profile using Taylor dispersion analysis, whereas microfluidic diffusional sizing quantifies the transfer of analyte from one phase to another. Species of sizes between 0.5 and 1000 nm can be analyzed, and different populations resolved. Both techniques also allow analysis in complex media and medium throughput analysis. These properties make them valuable complements to existing approaches to measure biomolecular interactions.     

Angle-scanning SPR imaging for detection of biomolecular interactions on microarrays

In this paper we describe the use of a commercial surface plasmon resonance (SPR) imaging instrument for monitoring the binding of biomolecules on user-defined regions of interest of a microarray. By monitoring the angle shift of the SPR-dip using a continuous angle-scanning mode instead of monitoring the change in reflectivity at a fixed angle, a linear relationship with respect to the mass density change on the surface will remain over a wide dynamic angle range of 8 degrees. Peptides (2.4 kDa) and proteins (150 kDa) were both spotted on the same sensor chip to illustrate that both, low and high molecular weight ligands with initial large differences in off-set SPR angles, can be applied within the same experiment. By using a fluorescently labeled antibody, SPR results can be confirmed by means of fluorescence microscopy after completion of a SPR experiment. SPR imaging in angle-scanning operation provides sensitive, accurate, and label-free detection of analyte binding on microarrays containing different molecular weight ligands.     

Designed metal-binding sites in biomolecular and bioinorganic interactions

The design of metal-binding functionality in proteins is expanding into many different areas with a wide range of practical and research applications. Here we review several developing areas of metal-related protein design, including the use of metals to induce protein-protein interactions or facilitate the assembly of extended nanostructures; the design of metallopeptides that bind metal and other inorganic surfaces, an area with potential in diverse applications ranging from nanoelectronics and photonics to biotechnology and biomedicine; and, the creation of sensitive and selective metal sensors for use both in vivo and in vitro.     

On statistical energy functions for biomolecular modeling and design

Statistical energy functions are general models about atomic or residue-level interactions in biomolecules, derived from existing experimental data. They provide quantitative foundations for structural modeling as well as for structure-based protein sequence design. Statistical energy functions can be derived computationally either based on statistical distributions or based on variational assumptions. We present overviews on the theoretical assumptions underlying the various types of approaches. Theoretical considerations underlying important pragmatic choices are discussed.     

Electrical detection of biomolecular interactions with metal-insulator-semiconductor diodes

We report the label-free detection of DNA hybridization using a metal-insulator-semiconductor (MIS) diode or capacitor. Upon immobilization of single-stranded DNA on the gold gate of a MIS capacitor, the capacitance versus voltage characteristics show a significant shift in the direction of negative voltages as expected from the immobilization of negative charges on the gate. The hybridization with the complementary strand gives rise to a further significant shift in the same direction as before, which is consistent with the increase of negative charges on the gate brought about by the hybridization. Fluorescence studies indicate that the immobilization and hybridization of DNA can be electrostatically promoted by electric fields externally applied to the MIS capacitors. The MIS diode detection method is applicable to all biomolecular interactions that affect the surface dipole at the interface between the metal gate and the electrolyte and can be extended to other chemical and biochemical systems such as proteins and cells.     

Label-free analysis of biomolecular interactions using SPR imaging

Surface plasmon resonance (SPR) is a label-free detection method by which molecular interactions may be analyzed on a surface. Binding data are collected in real time, allowing the determination of interaction kinetics. SPR imaging (SPRi), the focus of this review, improves upon the efficiency of SPR by facilitating analysis of multiple interactions simultaneously. Here we summarize the principles of SPRi, provide examples of how SPRi arrays can be fabricated, and illustrate the utility of SPRi through example applications from the fields of proteomics, genomics and bioengineering.     

Instrumental biosensors: new perspectives for the analysis of biomolecular interactions

The use of instrumental biosensors in basic research to measure biomolecular interactions in real time is increasing exponentially. Applications include protein–protein, protein–peptide, DNA–protein, DNA–DNA, and lipid–protein interactions. Such techniques have been applied to, for example, antibody–antigen, receptor–ligand, signal transduction, and nuclear receptor studies. This review outlines the principles of two of the most commonly used instruments and highlights specific operating parameters that will assist in optimising experimental design, data generation, and analysis. BioEssays 21:339–352, 1999. © 1999 John Wiley & Sons, Inc.     

Single-molecule approaches to characterizing kinetics of biomolecular interactions

Single-molecule fluorescence techniques have emerged as powerful tools to study biological processes at the molecular level. This review describes the application of these methods to the characterization of the kinetics of interaction between biomolecules. A large number of single-molecule assays have been developed that visualize association and dissociation kinetics in vitro by fluorescently labeling binding partners and observing their interactions over time. Even though recent progress has been significant, there are certain limitations to this approach. To allow the observation of individual, fluorescently labeled molecules requires low, nanomolar concentrations. I will discuss how such concentration requirements in single-molecule experiments limit their applicability to investigate intermolecular interactions and how recent technical advances deal with this issue.     

A generalized knowledge‐based discriminatory function for biomolecular interactions

Several novel and established knowledge‐based discriminatory function formulations and reference state derivations have been evaluated to identify parameter sets capable of distinguishing native and near‐native biomolecular interactions from incorrect ones. We developed the r·m·r function, a novel atomic level radial distribution function with mean reference state that averages over all pairwise atom types from a reduced atom type composition, using experimentally determined intermolecular complexes in the Cambridge Structural Database (CSD) and the Protein Data Bank (PDB) as the information sources. We demonstrate that r·m·r had the best discriminatory accuracy and power for protein‐small molecule and protein‐DNA interactions, regardless of whether the native complex was included or excluded, from the test set. The superior performance of the r·m·r discriminatory function compared with seventeen alternative functions evaluated on publicly available test sets for protein‐small molecule and protein‐DNA interactions indicated that the function was not over optimized through back testing on a single class of biomolecular interactions. The initial success of the reduced composition and superior performance with the CSD as the distribution set over the PDB implies that further improvements and generality of the function are possible by deriving probabilities from subsets of the CSD, using structures that consist of only the atom types to be considered for given biomolecular interactions. The method is available as a web server module at http://protinfo.compbio.washington.edu . Proteins 2009. © 2008 Wiley‐Liss, Inc.     

Solvation and desolvation effects in protein folding: native flexibility, kinetic cooperativity and enthalpic barriers under isostability conditions

As different parts of a protein chain approach one another during folding, they are expected to encounter desolvation barriers before optimal packing is achieved. This impediment originates from the water molecule's finite size, which entails a net energetic cost for water exclusion when the formation of compensating close intraprotein contacts is not yet complete. Based on recent advances, we extend our exploration of these microscopic elementary desolvation barriers' roles in the emergence of generic properties of protein folding. Using continuum Gō-like C(alpha) chain models of chymotrypsin inhibitor 2 (CI2) and barnase as examples, we underscore that elementary desolvation barriers between a protein's constituent groups can significantly reduce native conformational fluctuations relative to model predictions that neglected these barriers. An increasing height of elementary desolvation barriers leads to thermodynamically more cooperative folding/unfolding transitions (i.e., higher overall empirical folding barriers) and higher degrees of kinetic cooperativity as manifested by more linear rate-stability relationships under constant temperature. Applying a spatially non-uniform thermodynamic parametrization we recently introduced for the pairwise C(alpha) potentials of mean force, the present barnase model further illustrates that desolvation is a probable physical underpinning for the experimentally observed high intrinsic enthalpic folding barrier under isostability conditions.     

LED-based interferometric reflectance imaging sensor for quantitative dynamic monitoring of biomolecular interactions

Label-free optical biosensors have been established as proven tools for monitoring specific biomolecular interactions. However, compact and robust embodiments of such instruments have yet to be introduced in order to provide sensitive, quantitative, and high-throughput biosensing for low-cost research and clinical applications. Here we present the Interferometric Reflectance Imaging Sensor (IRIS) using an inexpensive and durable multi-color LED illumination source to monitor protein-protein and DNA-DNA interactions. We demonstrate the capability of this system to dynamically monitor antigen-antibody interactions with a noise floor of 5.2 pg/mm(2) and DNA single mismatch detection under denaturing conditions in an array format. Our experiments show that this platform has comparable sensitivity to high-end label-free biosensors at a much lower cost with the capability to be translated to field-deployable applications.     

Sensitivity deviation: instrumental linearity errors that influence concentration analyses and kinetic evaluation of biomolecular interactions.

Many scientific instruments utilise multiple element detectors, e.g. CCD's or photodiode arrays, to monitor the change in a position of an optical pattern. For example. instruments for affinity biosensing based on surface plasmon resonance (SPR) or resonant mirror are equipped with such detectors. An important and desired property of these bioanalytical instruments is that the calculation of the movement or change in shape follows the true change. This is often not the case and it may lead to linearity errors, and to sensitivity errors. The sensitivity is normally defined as the slope of the calibration curve. A new parameter is introduced to account for the linearity errors, the sensitivity deviation, defined as the deviation from the undistorted slope of the calibration curve. The linearity error and the sensitivity deviation are intimately related and the sensitivity deviation may lead to misinterpretation of kinetic data, mass transport limitations and concentration analyses. Because the linearity errors are small (e.g. 10 pg/mm2 of biomolecules on the sensor surface) with regard to the dynamic range (e.g. 30,000 pg/mm2), they can be difficult to discover. However, the linearity errors are often not negligible with regard to a typical response (e.g. 0-100 pg/mm2). and may therefore cause serious problems. A method for detecting linearity errors is outlined. Further on, this paper demonstrates how integral linearity errors of less than 1% can result in a sensitivity deviation of 10%, a value that in our opinion cannot be ignored in biospecific interaction analysis (BIA). It should also be stressed out that this phenomenon also occurs in other instruments using array detectors.