The effect of obstacles in multi-site protein target search with DNA looping

Probing the modulation in facilitated diffusion guided by DNA-protein interactions in target search processes

Many fundamental biophysical processes involving gene regulation and gene editing rely, at the molecular level, on an intricate methodology of searching and locating the precise target base pair sequence on the genome by specific binding proteins. A unique mechanism, known as 'facilitated diffusion', which is a combination of 1D sliding along with 3D movement, is considered to be the key step for such events. This also explains the relatively much shorter timescale of the target searching process, compared to other diffusion-controlled biophysical processes. In this work, we aim to probe the modulation of target search dynamics of a protein moiety by estimating the rate of the target search process, and the statistics of the search rounds and timescales accomplished by the 1D and 3D motions, based on first passage time (FPT) calculations. This is studied with its characteristics getting influenced by various given conditions such as, when the DNA is rigid or flexible, and when the target is placed at different locations on the DNA. The current theoretical framework includes a Brownian dynamics simulation setup adopting a straightforward coarse-grained model for a diffusing protein on DNA. Moreover, this theoretical analysis provides insights into the complex target search dynamics by highlighting the significance of the chain dynamics in the mechanistic details of the facilitated diffusion process.

Why Are Nucleosome Breathing Dynamics Asymmetric?

In eukaryotic cells, DNA is bound to nucleosomes, but DNA segments occasionally unbind in the process known as nucleosome breathing. Although DNA can unwrap simultaneously from both ends of the nucleosome (symmetric breathing), experiments indicate that DNA prefers to dissociate from only one end (asymmetric breathing). However, the molecular origin of the asymmetry is not understood. We developed a new theoretical approach that gives microscopic explanations of asymmetric breathing. It is based on a stochastic description that leads to a comprehensive evaluation of dynamics by using effective free-energy landscapes. It is shown that asymmetric breathing follows the kinetically preferred pathways. In addition, it is also found that asymmetric breathing leads to a faster target search by transcription factors. Theoretical predictions, supported by computer simulations, agree with experiments. It is proposed that nature utilizes the symmetry of nucleosome breathing to achieve a better dynamic accessibility of chromatin for more efficient genetic regulation.

Role of Nucleosome Sliding in the Protein Target Search for Covered DNA Sites

Associations of transcription factors (TFs) with specific sites on DNA initiate major cellular processes. But DNA in eukaryotic cells is covered by nucleosomes which prevent TFs from binding. However, nucleosome structures on DNA are not static and exhibit breathing and sliding. We develop a theoretical framework to investigate the effect of nucleosome sliding on a protein target search. By analysis of a discrete-state stochastic model of nucleosome sliding, search dynamics are explicitly evaluated. It is found that for long sliding lengths the target search dynamics are faster for normal TFs that cannot enter the nucleosomal DNA. But for more realistic short sliding lengths, the so-called pioneer TFs, which can invade nucleosomal DNA, locate specific sites faster. It is also suggested that nucleosome breathing, which is a faster process, has a stronger effect on protein search dynamics than that of nucleosome sliding. Theoretical arguments to explain these observations are presented.

Nucleosome Breathing Facilitates the Search for Hidden DNA Sites by Pioneer Transcription Factors

Transfer of genetic information starts with transcription factors (TFs) binding to specific sites on DNA. But in living cells, DNA is mostly covered by nucleosomes. There are proteins, known as pioneer TFs, that can efficiently reach the DNA sites hidden by nucleosomes, although the underlying mechanisms are not understood. Using the recently proposed idea of interaction-compensation mechanism, we develop a stochastic model for the target search on DNA with nucleosome breathing. It is found that nucleosome breathing can significantly accelerate the search by pioneer TFs in comparison to situations without breathing. We argue that this is the result of the interaction-compensation mechanism that allows proteins to enter the inner nucleosome region through the outer DNA segment. It is suggested that nature optimized pioneer TFs to take advantage of nucleosome breathing. The presented theoretical picture provides a possible microscopic explanation for the successful invasion of nucleosome-buried genes.

How Pioneer Transcription Factors Search for Target Sites on Nucleosomal DNA

All major biological processes start after protein molecules known as transcription factors detect specific regulatory sequences on DNA and initiate genetic expression by associating to them. But in eukaryotic cells, much of the DNA is covered by nucleosomes and other chromatin structures, preventing transcription factors from binding to their targets. At the same time, experimental studies show that there are several classes of proteins, called "pioneer transcription factors", that are able to reach the targets on nucleosomal DNA; however, the underlying microscopic mechanisms remain not well understood. We propose a new theoretical approach that might explain how pioneer transcription factors can find their targets. It is argued that pioneer transcription factors might weaken the interactions between the DNA and nucleosome by substituting them with similar interactions between transcription factors and DNA. Using this idea, we develop a discrete-state stochastic model that allows for exact calculations of target search dynamics on nucleosomal DNA using first-passage probabilities approach. It is found that the target search on nuclesomal DNA for pioneer transcription factors might be significantly accelerated while the search is slower on naked DNA in comparison with normal transcription factors. Our theoretical predictions are supported by Monte Carlo computer simulations, and they also agree with available experimental observations.

Influence of Nonspecific Interactions between Proteins and In Vivo Cytoplasmic Crowders in Facilitated Diffusion of Proteins: Theoretical Insights

The binding of proteins to their respective specific sites on the DNA through facilitated diffusion serves as the initial step of various important biological processes. While this search process has been thoroughly investigated via in vitro studies, the cellular environment is complex and may interfere with the protein's search dynamics. The cytosol is heavily crowded, which can potentially modify the search by nonspecifically interacting with the protein that has been mostly overlooked. In this work, we probe the target search dynamics in the presence of explicit crowding agents that have an affinity toward the protein. We theoretically investigate the role of such protein-crowder associations in the target search process using a discrete-state stochastic framework that allows for the analytical description of dynamic properties. It is found that stronger nonspecific associations between the crowder and proteins can accelerate the facilitated diffusion of proteins in comparison with a purely inert, rather weakly interacting cellular environment. This effect depends on how strong these associations are, the spatial positions of the target with respect to the crowders, and the size of the crowded region. Our theoretical results are also tested with Monte Carlo computer simulations. Our predictions are in qualitative agreement with existing experimental observations and computational studies.

DNA Looping and DNA Conformational Fluctuations Can Accelerate Protein Target Search

Protein searching and binding to specific sites on DNA is a fundamentally important process that marks the beginning of all major cellular transformations. While the dynamics of protein-DNA interactions in in vitro settings is well investigated, the situation is much more complex for in vivo conditions because the DNA molecules in live cells are packed into chromosomal structures where they are undergoing strong dynamic and conformational fluctuations. In this work, we present a theoretical investigation on the role of DNA looping and DNA conformational fluctuations in the protein target search. It is based on a discrete-state stochastic analysis that allows for explicit calculations of dynamic properties, which is also supplemented by Monte Carlo computer simulations. It is found that for stronger nonspecific interactions between DNA and proteins the search occurs faster on the DNA looped conformation in comparison with the unlooped conformation, and the fastest search is observed when the loop is formed near the target site. It is also shown that DNA fluctuations between the looped and unlooped conformations influence the search dynamics, and this depends on the magnitude of conformational transition rates and on which conformation is more energetically stable. Physical-chemical arguments explaining these observations are presented. Our theoretical study suggests that the geometry and conformational changes in DNA are additional factors that might efficiently control the gene regulation processes.

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.