Discrete-State Kinetics Model for NMR-Based Analysis of Protein Translocation on DNA at Equilibrium

Analyzing paramagnetic NMR data on target DNA search by proteins using a discrete-state kinetic model for translocation

Before reaching their targets, sequence-specific DNA-binding proteins nonspecifically bind to DNA through electrostatic interactions and stochastically change their locations on DNA. Investigations into the dynamics of DNA-scanning by proteins are nontrivial due to the simultaneous presence of multiple translocation mechanisms and many sites for the protein to nonspecifically bind to DNA. Nuclear magnetic resonance (NMR) spectroscopy can provide information about the target DNA search processes at an atomic level. Paramagnetic relaxation enhancement (PRE) is particularly useful to study how the proteins scan DNA in the search process. Previously, relatively simple two-state or three-state exchange models were used to explain PRE data reflecting the target search process. In this work, using more realistic discrete-state stochastic kinetics models embedded into an NMR master equation, we analyzed the PRE data for the HoxD9 homeodomain interacting with DNA. The kinetic models that incorporate sliding, dissociation, association, and intersegment transfer can reproduce the PRE profiles observed at some different ionic strengths. The analysis confirms the previous interpretation of the PRE data and shows that the protein's probability distribution among nonspecific sites is nonuniform during the target DNA search process.

Discrete-state stochastic kinetic models for target DNA search by proteins: Theory and experimental applications

To perform their functions, transcription factors and DNA-repair/modifying enzymes randomly search DNA in order to locate their specific targets on DNA. Discrete-state stochastic kinetic models have been developed to explain how the efficiency of the search process is influenced by the molecular properties of proteins and DNA as well as by other factors such as molecular crowding. These theoretical models not only offer explanations on the relation of microscopic processes to macroscopic behavior of proteins, but also facilitate the analysis and interpretation of experimental data. In this review article, we provide an overview on discrete-state stochastic kinetic models and explain how these models can be applied to experimental investigations using stopped-flow, single-molecule, nuclear magnetic resonance (NMR), and other biophysical and biochemical methods.

Dynamics of Ionic Interactions at Protein-Nucleic Acid Interfaces

Molecular association of proteins with nucleic acids is required for many biological processes essential to life. Electrostatic interactions via ion pairs (salt bridges) of nucleic acid phosphates and protein side chains are crucial for proteins to bind to DNA or RNA. Counterions around the macromolecules are also key constituents for the thermodynamics of protein–nucleic acid association. Until recently, there had been only a limited amount of experiment-based information about how ions and ionic moieties behave in biological macromolecular processes. In the past decade, there has been significant progress in quantitative experimental research on ionic interactions with nucleic acids and their complexes with proteins. The highly negatively charged surfaces of DNA and RNA electrostatically attract and condense cations, creating a zone called the ion atmosphere. Recent experimental studies were able to examine and validate theoretical models on ions and their mobility and interactions with macromolecules. The ionic interactions are highly dynamic. The counterions rapidly diffuse within the ion atmosphere. Some of the ions are released from the ion atmosphere when proteins bind to nucleic acids, balancing the charge via intermolecular ion pairs of positively charged side chains and negatively charged backbone phosphates. Previously, the release of counterions had been implicated indirectly by the salt-concentration dependence of the association constant.

Recently, direct detection of counterion release by NMR spectroscopy has become possible and enabled more accurate and quantitative analysis of the counterion release and its entropic impact on the thermodynamics of protein–nucleic acid association. Recent studies also revealed the dynamic nature of ion pairs of protein side chains and nucleic acid phosphates. These ion pairs undergo transitions between two major states. In one of the major states, the cation and the anion are in direct contact and form hydrogen bonds. In the other major state, the cation and the anion are separated by water. Transitions between these states rapidly occur on a picosecond to nanosecond time scale. When proteins interact with nucleic acids, interfacial arginine (Arg) and lysine (Lys) side chains exhibit considerably different behaviors. Arg side chains show a higher propensity to form rigid contacts with nucleotide bases, whereas Lys side chains tend to be more mobile at the molecular interfaces. The dynamic ionic interactions may facilitate adaptive molecular recognition and play both thermodynamic and kinetic roles in protein–nucleic acid interactions.

Quantifying the two-state facilitated diffusion model of protein-DNA interactions

The current report extends the facilitated diffusion model to account for conflict between the search and recognition binding modes adopted by DNA-binding proteins (DBPs) as they search DNA and subsequently recognize and bind to their specific binding site. The speed of the search dynamics is governed by the energetic ruggedness of the protein-DNA landscape, whereas the rate for the recognition process is mostly dictated by the free energy barrier for the transition between the DBP's search and recognition binding modes. We show that these two modes are negatively coupled, such that fast 1D sliding and rapid target site recognition probabilities are unlikely to coexist. Thus, a tradeoff occurs between optimizing the timescales for finding and binding the target site. We find that these two kinetic properties can be balanced to produce a fast timescale for the total target search and recognition process by optimizing frustration. Quantification of the facilitated diffusion model by including a frustration term enables it to explain several experimental observations concerning search and recognition speeds. The extended model captures experimental estimate of the energetic ruggedness of the protein-DNA landscape and predicts how various molecular properties of protein-DNA binding affect recognition kinetics. Particularly, point mutations may change the frustration and so affect protein association with DNA, thus providing a means to modulate protein-DNA affinity by manipulating the protein's association or dissociation reactions.

NMR-based investigations into target DNA search processes of proteins

To perform their function, transcription factors and DNA-repair/modifying enzymes must first locate their targets in the vast presence of nonspecific, but structurally similar sites on genomic DNA. Before reaching their targets, these proteins stochastically scan DNA and dynamically move from one site to another on DNA. Solution NMR spectroscopy provides unique atomic-level insights into the dynamic DNA-scanning processes, which are difficult to gain by any other experimental means. In this review, we provide an introductory overview on the NMR methods for the structural, dynamic, and kinetic investigations of target DNA search by proteins. We also discuss advantages and disadvantages of these NMR methods over other methods such as single-molecule techniques and biochemical approaches.