First passage time of N excluded-volume particles on a line

Redundancy principle and the role of extreme statistics in molecular and cellular biology

The paradigm of chemical activation rates in cellular biology has been shifted from the mean arrival time of a single particle to the mean of the first among many particles to arrive at a small activation site. The activation rate is set by extremely rare events, which have drastically different time scales from the mean times between activations, and depends on different structural parameters. This shift calls for reconsideration of physical processes used in deterministic and stochastic modeling of chemical reactions that are based on the traditional forward rate, especially for fast activation processes in living cells. Consequently, the biological activation time is not necessarily exponentially distributed. We review here the physical models, the mathematical analysis and the new paradigm of setting the scale to be the shortest time for activation that clarifies the role of population redundancy in selecting and accelerating transient cellular search processes. We provide examples in cellular transduction, gene activation, cell senescence activation or spermatozoa selection during fertilization, where the rate depends on numbers. We conclude that the statistics of the minimal time to activation set kinetic laws in biology, which can be very different from the ones associated to average times.

Theory of bimolecular reactions in a solution with linear traps: Application to the problem of target search on DNA

One-dimensional sliding along DNA as a means to accelerate protein target search is a well-known phenomenon occurring in various biological systems. Using a biomimetic approach, we have recently demonstrated the practical use of DNA-sliding peptides to speed up bimolecular reactions more than an order of magnitude by allowing the reactants to associate not only in the solution by three-dimensional (3D) diffusion, but also on DNA via one-dimensional (1D) diffusion [A. Turkin et al., Chem. Sci. (2015)]. Here we present a mean-field kinetic model of a bimolecular reaction in a solution with linear extended sinks (e.g., DNA) that can intermittently trap molecules present in a solution. The model consists of chemical rate equations for mean concentrations of reacting species. Our model demonstrates that addition of linear traps to the solution can significantly accelerate reactant association. We show that at optimum concentrations of linear traps the 1D reaction pathway dominates in the kinetics of the bimolecular reaction; i.e., these 1D traps function as an assembly line of the reaction product. Moreover, we show that the association reaction on linear sinks between trapped reactants exhibits a nonclassical third-order behavior. Predictions of the model agree well with our experimental observations. Our model provides a general description of bimolecular reactions that are controlled by a combined 3D+1D mechanism and can be used to quantitatively describe both naturally occurring as well as biomimetic biochemical systems that reduce the dimensionality of search.

Optimal cooperative searching using purely repulsive interactions

Foraging, either solitarily or collectively, is a necessary behavior for survival that is demonstrated by many organisms. Foraging can be collectively optimized by utilizing communication between the organisms. Examples of such communication range from high level strategic foraging by animal groups to rudimentary signaling among unicellular organisms. Here we systematically study the simplest form of communication via long range repulsive interactions between multiple diffusing Brownian searchers on a one-dimensional lattice. We show that the mean first passage time for any one of them to reach a fixed target depends non-monotonically on the range of the interaction and can be optimized for a repulsive range that is comparable to the average spacing between searchers. Our results suggest that even the most rudimentary form of collective searching does in fact lower the search time for the foragers suggesting robust mechanisms for search optimization in cellular communities.

Breathing dynamics based parameter sensitivity analysis of hetero-polymeric DNA

We study the parameter sensitivity of hetero-polymeric DNA within the purview of DNA breathing dynamics. The degree of correlation between the mean bubble size and the model parameters is estimated for this purpose for three different DNA sequences. The analysis leads us to a better understanding of the sequence dependent nature of the breathing dynamics of hetero-polymeric DNA. Out of the 14 model parameters for DNA stability in the statistical Poland-Scheraga approach, the hydrogen bond interaction ε(hb)(AT) for an AT base pair and the ring factor ξ turn out to be the most sensitive parameters. In addition, the stacking interaction ε(st)(TA-TA) for an TA-TA nearest neighbor pair of base-pairs is found to be the most sensitive one among all stacking interactions. Moreover, we also establish that the nature of stacking interaction has a deciding effect on the DNA breathing dynamics, not the number of times a particular stacking interaction appears in a sequence. We show that the sensitivity analysis can be used as an effective measure to guide a stochastic optimization technique to find the kinetic rate constants related to the dynamics as opposed to the case where the rate constants are measured using the conventional unbiased way of optimization.

Intracellular facilitated diffusion: searchers, crowders, and blockers

In bacteria, regulatory proteins search for a specific DNA-binding target via "facilitated diffusion": a series of rounds of three-dimensional diffusion in the cytoplasm, and one-dimensional (1D) linear diffusion along the DNA contour. Using large scale Brownian dynamics simulations we find that each of these steps is affected differently by crowding proteins, which can either be bound to the DNA acting as a road block to the 1D diffusion, or freely diffusing in the cytoplasm. Macromolecular crowding can strongly affect mechanistic features such as the balance between three-dimensional and 1D diffusion, but leads to surprising robustness of the total search time.

Effect of DNA conformation on facilitated diffusion

Within a living cell, site-specific DNA-binding proteins need to search the whole genome to find a target of ~10-20 bp. That they find the target, and do so quickly, is vital for the correct functioning of the DNA, and of the cell as a whole. The current understanding is that this search is performed via facilitated diffusion, i.e. by combining three-dimensional bulk diffusion within the cytoplasm or nucleoplasm, with one-dimensional diffusion along the DNA backbone, to which the protein binds non-specifically. After reviewing the standard theory of facilitated diffusion, we discuss in the present article the still rather rare direct computer simulations of this process, focusing on the three-dimensional part of the search, and the effect of DNA looping and the general DNA conformation on its efficiency. We close by highlighting some open questions in this field.

Diffusion-mediated geminate reactions under excluded volume interactions

In this paper, influence of crowding by inert particles on the geminate reaction kinetics is theoretically investigated. Time evolution equations for the survival probability of a geminate pair are derived from the master equation taking into account the correlation among all diffusing particles, and the results are compared with those obtained by Monte Carlo simulations. In general, excluded volume interactions by the inert particles slow down the diffusive motion of reactants. However, when the initial concentration of the inert particles is uniform and high, we show that additional influence of interference between reaction and correlated diffusion accelerates the transient decay of the survival probability in the diffusion-controlled limit. We also study the escape probability for a nonuniform initial distribution of the inert particles by taking the continuous limit in space. We show that reaction yield is increased when the reaction proceeds in the presence of a positive density gradient of the inert particles which inhibits the escape of reactants. The effect can be interpreted as a cage effect.

Biophysical characterization of DNA binding from single molecule force measurements

Single molecule force spectroscopy is a powerful method that uses the mechanical properties of DNA to explore DNA interactions. Here we describe how DNA stretching experiments quantitatively characterize the DNA binding of small molecules and proteins. Small molecules exhibit diverse DNA binding modes, including binding into the major and minor grooves and intercalation between base pairs of double-stranded DNA (dsDNA). Histones bind and package dsDNA, while other nuclear proteins such as high mobility group proteins bind to the backbone and bend dsDNA. Single-stranded DNA (ssDNA) binding proteins slide along dsDNA to locate and stabilize ssDNA during replication. Other proteins exhibit binding to both dsDNA and ssDNA. Nucleic acid chaperone proteins can switch rapidly between dsDNA and ssDNA binding modes, while DNA polymerases bind both forms of DNA with high affinity at distinct binding sites at the replication fork. Single molecule force measurements quantitatively characterize these DNA binding mechanisms, elucidating small molecule interactions and protein function.

Reaction under vacancy-assisted diffusion at high quencher concentration

The theory of diffusion-mediated reactions is already established for the target problem in the dilute limit, where the immobile target is surrounded by many quenchers. For lattice random walks in the crowded situation, each quencher is surrounded by other quenchers differently. As a result, each quencher migrates differently in the presence of site blocking effects. However, in the conventional theory, such difference is ignored and quenchers are assumed to move independently of each other. In this paper, theory of diffusion-mediated reactions of target problem is developed by taking into account the site blocking effects for quencher migration and the difference in the configuration of quenchers around each quencher. Our result interpolates between those in high and low limits of quencher concentrations and is a lower bound of the survival probability. In the static limit, the exact result is reproduced for a localized sink. In the presence of diffusion, the approximation is better when intrinsic reaction rates are low.

Interaction of bacteriophage T4 and T7 single-stranded DNA-binding proteins with DNA

Bacteriophages T4 and T7 are well-studied model replication systems, which have allowed researchers to determine the roles of many proteins central to DNA replication, recombination and repair. Here we summarize and discuss the results from two recently developed single-molecule methods to determine the salt-dependent DNA-binding kinetics and thermodynamics of the single-stranded DNA (ssDNA)-binding proteins (SSBs) from these systems. We use these methods to characterize both the equilibrium double-stranded DNA (dsDNA) and ssDNA binding of the SSBs T4 gene 32 protein (gp32) and T7 gene 2.5 protein (gp2.5). Despite the overall two-orders-of-magnitude weaker binding of gp2.5 to both forms of DNA, we find that both proteins exhibit four-orders-of-magnitude preferential binding to ssDNA relative to dsDNA. This strong preferential ssDNA binding as well as the weak dsDNA binding is essential for the ability of both proteins to search dsDNA in one dimension to find available ssDNA-binding sites at the replication fork.

Kinetics and thermodynamics of salt-dependent T7 gene 2.5 protein binding to single- and double-stranded DNA

Bacteriophage T7 gene 2.5 protein (gp2.5) is a single-stranded DNA (ssDNA)-binding protein that has essential roles in DNA replication, recombination and repair. However, it differs from other ssDNA-binding proteins by its weaker binding to ssDNA and lack of cooperative ssDNA binding. By studying the rate-dependent DNA melting force in the presence of gp2.5 and its deletion mutant lacking 26 C-terminal residues, we probe the kinetics and thermodynamics of gp2.5 binding to ssDNA and double-stranded DNA (dsDNA). These force measurements allow us to determine the binding rate of both proteins to ssDNA, as well as their equilibrium association constants to dsDNA. The salt dependence of dsDNA binding parallels that of ssDNA binding. We attribute the four orders of magnitude salt-independent differences between ssDNA and dsDNA binding to nonelectrostatic interactions involved only in ssDNA binding, in contrast to T4 gene 32 protein, which achieves preferential ssDNA binding primarily through cooperative interactions. The results support a model in which dimerization interactions must be broken for DNA binding, and gp2.5 monomers search dsDNA by 1D diffusion to bind ssDNA. We also quantitatively compare the salt-dependent ssDNA- and dsDNA-binding properties of the T4 and T7 ssDNA-binding proteins for the first time.

Quantifying DNA-protein interactions by single molecule stretching

In this chapter, we discuss a new method for quantifying DNA-protein interactions. A single double-stranded DNA (dsDNA) molecule is stretched beyond its contour length, causing the base pairs to break while increasing the length from that of dsDNA to that of ssDNA. When applied in a solution containing DNA binding ligands, this method of force-induced DNA melting can be used to quantify the free energy of ligand binding, including the free energy of protein binding. The dependence of melting force on protein concentration is used to obtain the equilibrium binding constant of the ligand to DNA. We have applied this method to a well-studied DNA-binding protein, bacteriophage T4 gene 32 protein (gp32), and have obtained binding constants for the protein to single-stranded DNA (ssDNA) under a wide range of solution conditions. Our analysis of measurements conducted at several salt concentrations near physiological conditions indicates that a salt-dependent conformational change regulates DNA binding by gp32.

Mechanisms of DNA binding determined in optical tweezers experiments

The last decade has seen rapid development in single molecule manipulation of RNA and DNA. Measuring the response force for a particular manipulation has allowed the free energies of various nucleic acid structures and configurations to be determined. Optical tweezers represent a class of single molecule experiments that allows the energies and structural dynamics of DNA to be probed up to and beyond the transition from the double helix to its melted single strands. These experiments are capable of high force resolution over a wide dynamic range. Additionally, these investigations may be compared with results obtained when the nucleic acids are in the presence of proteins or other binding ligands. These ligands may bind into the major or minor groove of the double helix, intercalate between bases or associate with an already melted single strand of DNA. By varying solution conditions and the pulling dynamics, energetic and dynamic information may be deduced about the mechanisms of binding to nucleic acids, providing insight into the function of proteins and the utility of drug treatments.

Sequence sensitivity of breathing dynamics in heteropolymer DNA

We study the fluctuation dynamics of localized denaturation bubbles in heteropolymer DNA with a master equation and complementary stochastic simulation based on novel DNA stability data. A significant dependence of opening probability and waiting time between bubble events on the local DNA sequence is revealed and quantified for a biological sequence of the T7 bacteriophage. Quantitative agreement with data from fluorescence correlation spectroscopy is demonstrated.

Optimal target search on a fast-folding polymer chain with volume exchange

We study the search process of a target on a rapidly folding polymer ("DNA") by an ensemble of particles ("proteins"), whose search combines 1D diffusion along the chain, Lévy type diffusion mediated by chain looping, and volume exchange. A rich behavior of the search process is obtained with respect to the physical parameters, in particular, for the optimal search.