Browsing by Subject "Binding"

RNA recognition frequently results in conformational changes that optimize

intermolecular binding. As a consequence, the overall binding affinity of RNA

to its binding partners depends not only on the intermolecular interactions

formed in the bound state, but also on the energy cost associated with changing

the RNA conformational distribution. Measuring these conformational penalties

is however challenging because bound RNA conformations tend to have equilibrium

populations in the absence of the binding partner that fall outside detection by

conventional biophysical methods.

In this work we employ as a model system HIV-1 TAR RNA and its interaction with

the ligand argininamide (ARG), a mimic of TAR’s cognate protein binding partner,

the transactivator Tat. We use NMR chemical shift perturbations (CSP) and NMR

relaxation dispersion (RD) in combination with Bayesian inference to develop a

detailed thermodynamic model of coupled conformational change and ligand

binding. Starting from a comprehensive 12-state model of the equilibrium, we

estimate the energies of six distinct detectable thermodynamic states that are

not accessible by currently available methods.

Our approach identifies a minimum of four RNA intermediates that differ in terms

of the TAR conformation and ARG-occupancy. The dominant bound TAR conformation

features two bound ARG ligands and has an equilibrium population in the absence

of ARG that is below detection limit. Consequently, even though ARG binds to TAR

with an apparent overall weak affinity ($\Kdapp \approx \SI{0.2}{\milli

\Molar}$), it binds the prefolded conformation with a $K_{\ch{d}}$ in the nM

range. Our results show that conformational penalties can be major determinants

of RNA-ligand binding affinity as well as a source of binding cooperativity,

with important implications for a predictive understanding of how RNA is

recognized and for RNA-targeted drug discovery.

Additionally, we describe in detail the development of our approach for fitting

complex ligand binding data to mathematical models using Bayesian

inference. We provide crucial benchmarks and demonstrate the

robustness of our fitting approach with the goal of application

to other systems. This thesis aims to provide new insight into

the dynamics of RNA-ligand recognition as well as provide new

methods that can be applied to achieve this goal.

Digital microfluidic (DMF) technology is being utilized for commercial applications such as point-of-care diagnostics, sample processing and genomic library preparation. Advances in this field offer exciting possibilities into immunoassays, enzymatic analysis, and next-generation sequencing. However, typical biomolecular protocols performed in laboratories are far more complex, requiring large reagent volumes, long processing times and provide a low throughput analysis. Using a DMF platform enables overcoming experimental barriers of manual laboratory protocol execution, allowing for scaling the platform geometry, assay times, volumes of reagents used, and minimizing the use of external mechanical equipment. The DMF platform also allows for easy integration with detection systems enabling real-time data analysis and efficient resource allocation. This thesis explores theoretical and experimental approaches for carrying out enhanced biomolecular binding to magnetic beads on a DMF platform as part of a sample preparation protocol. Different DMF prototypes were designed using standard microfabrication procedures to compare passive mixing, active mixing on electrode arrays and local bead actuation on an integrated current-wire electrode, whereby current is sequenced through copper wires fabricated on the electrode to generate magnetic-fields on-chip that cause the magnetic beads in the assay to move relative to the antibody. By making use of an integrated fluorescence detection system, the binding efficiency for each of these approaches is determined. The current-wire device design proves to be a valuable tool in creating an integrated DMF system to carry out intensive bead binding in an assay allowing for lower reagent volumes, shorter assay times and reduced surface area, thus impacting device yield.

Ligand binding can modulate function of proteins and nucleic acids by changing both the populations of functionally distinct conformational states and the timescales on which they interconvert. For this reason, both thermodynamic and kinetic details of coupling can be important to proper function. How tightly does ligand bind to the different conformational states? What effect does ligand binding have on the conformational equilibrium and conformational kinetics? On what timescales and in what order do binding and conformational change occur? Using a combination of stopped-flow kinetics, isothermal titration calorimetry, and x-ray crystallography, we determine the mechanisms of coupled binding and conformational change in protein (Bacillus subtilis RNase P protein) and RNA (DP17 biosensor) systems.

The results demonstrate that rigorous kinetic analysis can be used to estimate the equilibrium and rate constants for conformational changes, as well as the affinities of ligands for different conformational states. A single ligand can bind to different conformational states of the same protein or nucleic acid with affinities that differ by orders of magnitude. This binding shifts the conformational equilibrium towards the higher affinity state through a combination of increasing rate constants for the forward conformational change and decreasing rate constants for the reverse conformational change. Using a flux-based analysis of the mechanisms we show that molecular recognition is kinetically partitioned between a number of pathways that differ by the order in which binding and conformational change occur. The absolute and relative flux through these pathways varies with ligand concentration, the affinities of the ligand for the various conformational states, and the ability of ligand to accelerate the conformational change. Together, the results give insights into how biological function depends on the kinetic and thermodynamic details of coupled binding and conformational change.