Allosterism and signal transfer in DNA

Role of Shape Deformation of DNA-Binding Sites in Regulating the Efficiency and Specificity in Their Recognition by DNA-Binding Proteins

Accurate transcription of genetic information is crucial, involving precise recognition of the binding motifs by DNA-binding proteins. While some proteins rely on short-range hydrophobic and hydrogen bonding interactions at binding sites, others employ a DNA shape readout mechanism for specific recognition. In this mechanism, variations in DNA shape at the binding motif resulted from either inherent flexibility or binding of proteins at adjacent sites are sensed and capitalized by the searching proteins to locate them specifically. Through extensive computer simulations, we investigate both scenarios to uncover the underlying mechanism and origin of specificity in the DNA shape readout mechanism. Our findings reveal that deformation in shape at the binding motif creates an entropy funnel, allowing information about altered shapes to manifest as fluctuations in minor groove widths. This signal enhances the efficiency of nonspecific search of nearby proteins by directing their movement toward the binding site, primarily driven by a gain in entropy. We propose this as a generic mechanism for DNA shape readout, where specificity arises from the alignment between the molecular frustration of the searching protein and the ruggedness of the entropic funnel governed by molecular features of the protein and arrangement of the DNA bases at the binding site, respectively.

CGeNArate: a sequence-dependent coarse-grained model of DNA for accurate atomistic MD simulations of kb-long duplexes

We present CGeNArate, a new model for molecular dynamics simulations of very long segments of B-DNA in the context of biotechnological or chromatin studies. The developed method uses a coarse-grained Hamiltonian with trajectories that are back-mapped to the atomistic resolution level with extreme accuracy by means of Machine Learning Approaches. The method is sequence-dependent and reproduces very well not only local, but also global physical properties of DNA. The efficiency of the method allows us to recover with a reduced computational effort high-quality atomic-resolution ensembles of segments containing many kilobases of DNA, entering into the gene range or even the entire DNA of certain cellular organelles.

Mechanisms of DNA-Mediated Allostery

Proteins often regulate their activities via allostery-or action at a distance-in which the binding of a ligand at one binding site influences the affinity for another ligand at a distal site. Although less studied than in proteins, allosteric effects have been observed in experiments with DNA as well. In these experiments two or more proteins bind at distinct DNA sites and interact indirectly with each other, via a mechanism mediated by the linker DNA molecule. We develop a mechanical model of DNA/protein interactions which predicts three distinct mechanisms of allostery. Two of these involve an enthalpy-mediated allostery, while a third mechanism is entropy driven. We analyze experiments of DNA allostery and highlight the distinctive signatures allowing one to identify which of the proposed mechanisms best fits the data.

Decoding the dual recognition mechanism of the glucocorticoid receptor for DNA and RNA: sequence versus shape

Transcription factors (TFs) regulate eukaryotic transcription through selective DNA-binding, can also specifically interact with RNA, which may present another layer of transcriptional control. The mechanisms of the TFs-DNA recognition are often well-characterised, while the details of TFs-RNA complexation are less understood. Here we investigate the dual recognition mechanism of the glucocorticoid receptor (GR), which interacts with similar affinities with consensus DNA and diverse RNA hairpin motifs but discriminates against uniform dsRNA. Using atomic molecular dynamics simulations, we demonstrate that the GR binding to nucleic acids requires a wide and shallow groove pocket. The protein effectively moulds its binding site within DNA major groove, which enables base-specific interactions. Contrary, the GR binding has little effect on the grooves geometry of RNA systems, most notably in uniform dsRNA. Instead, a hairpin motif in RNA yields a wide and shallow major groove pocket, allowing the protein to anchor itself through nonspecific electrostatic contacts with RNA backbone. Addition of a bulge increases RNA hairpin flexibility, which leads to a greater number of GR-RNA contacts and, thus, higher affinity. Thus, the combination of structural motifs defines the GR-RNA selective binding: a recognition mechanism, which may be shared by other zinc finger TFs.

Binding of the transcription activator-like effector augments transcriptional regulation by another transcription factor

DNA transcription is regulated by a range of diverse mechanisms and primarily by transcription factors that recruit the RNA polymerase complex to the promoter region on the DNA. Protein binding to DNA at nearby or distant sites can synergistically affect this process in a variety of ways, but mainly through direct interactions between DNA-binding proteins. Here we show that a Transcription Activator-Like Effector (TALE), which lacks an activation domain, can enhance transcription in mammalian cells when it binds in the vicinity of and without direct interaction with several different dimeric or monomeric transcription factors. This effect was observed for several TALEs regardless of the recognition sequences and their DNA-bound orientation. TALEs can exert an effect over the distance of tens of nucleotides and it also potentiated KRAB-mediated repression. The augmentation of transcriptional regulation of another transcription factor is characteristic of TALEs, as it was not observed for dCas9/gRNA, zinc finger, or Gal4 DNA-binding domains. We propose that this mechanism involves an allosteric effect exerted on DNA structure or dynamics. This mechanism could be used to modulate transcription but may also play a role in the natural context of TALEs.

Information Flow and Allosteric Communication in Proteins

Based on Schreiber's work on transfer entropy, a molecular theory of nonlinear information transfer in proteins is developed. The joint distribution function for residue fluctuations is expressed in terms of tensor Hermite polynomials which conveniently separate harmonic and nonlinear contributions to information transfer. The harmonic part of information transfer is expressed as the difference between time dependent and independent mutual information. Third order nonlinearities are discussed in detail. Amount and speed of information transfer between residues, important for understanding allosteric activity in proteins, are discussed. While mutual information shows the maximum amount of information that may be transferred between two residues, it does not explain the actual amount of transfer nor the transfer rate of information. For this, dynamic equations of the system are needed. The solution of the Langevin equation and molecular dynamics trajectories are used in the present work for this purpose. Allosteric communication in Human NAD-dependent isocitrate dehydrogenase is studied as an example. Calculations show that several paths contribute collectively to information transfer. Important residues on these paths are identified. Time resolved information transfer between these residues, their amplitudes and transfer rates, which are in agreement with time resolved ultraviolet resonance Raman measurements in general, are estimated. Estimated transfer rates are in the order of 1-20 megabits per second. Information transfer from third order contributions are one to two orders of magnitude smaller than the harmonic terms, showing that harmonic analysis is a good approximation to information transfer.

Combining steady state and temperature jump IR spectroscopy to investigate the allosteric effects of ligand binding to dsDNA

Changes in the structural dynamics of double stranded (ds)DNA upon ligand binding have been linked to the mechanism of allostery without conformational change, but direct experimental evidence remains elusive. To address this, a combination of steady state infrared (IR) absorption spectroscopy and ultrafast temperature jump IR absorption measurements has been used to quantify the extent of fast (∼100 ns) fluctuations in (ds)DNA·Hoechst 33258 complexes at a range of temperatures. Exploiting the direct link between vibrational band intensities and base stacking shows that the absolute magnitude of the change in absorbance caused by fast structural fluctuations following the temperature jump is only weakly dependent on the starting temperature of the sample. The observed fast dynamics are some two orders of magnitude faster than strand separation and associated with all points along the 10-base pair duplex d(GCATATATCC). Binding the Hoechst 33258 ligand causes a small but consistent reduction in the extent of these fast fluctuations of base pairs located outside of the ligand binding region. These observations point to a ligand-induced reduction in the flexibility of the dsDNA near the binding site, consistent with an estimated allosteric propagation length of 15 Å, about 5 base pairs, which agrees well with both molecular simulation and coarse-grained statistical mechanics models of allostery leading to cooperative ligand binding.

Low-frequency vibrational modes in G-quadruplexes reveal the mechanical properties of nucleic acids

Low-frequency vibrations play an essential role in biomolecular processes involving DNA such as gene expression, charge transfer, drug intercalation, and DNA–protein recognition. However, understanding the vibrational basis of these mechanisms relies on theoretical models due to the lack of experimental evidence. Here we present the low-frequency vibrational spectra of G-quadruplexes (structures formed by four strands of DNA) and B-DNA characterized using femtosecond optical Kerr-effect spectroscopy. Contrary to expectation, we found that G-quadruplexes show several strongly underdamped delocalized phonon-like modes that have the potential to contribute to the biology of the DNA at the atomic level. In addition, G-quadruplexes present modes at a higher frequency than B-DNA demonstrating that changes in the stiffness of the molecule alter its gigahertz to terahertz vibrational profile.

Low-frequency vibrations play an essential role in biomolecular processes involving DNA such as gene expression, charge transfer, drug intercalation, and DNA–protein recognition.

A perspective on the molecular simulation of DNA from structural and functional aspects

As genetic material, DNA not only carries genetic information by sequence, but also affects biological functions ranging from base modification to replication, transcription and gene regulation through its structural and dynamic properties and variations. The motion and structural properties of DNA involved in related biological processes are also multi-scale, ranging from single base flipping to local DNA deformation, TF binding, G-quadruplex and i-motif formation, TAD establishment, compartmentalization and even chromosome territory formation, just to name a few. The sequence-dependent physical properties of DNA play vital role in all these events, and thus it is interesting to examine how simple sequence information affects DNA and the formation of the chromatin structure in these different hierarchical orders. Accordingly, molecular simulations can provide atomistic details of interactions and conformational dynamics involved in different biological processes of DNA, including those inaccessible by current experimental methods. In this perspective, which is mainly based on our recent studies, we provide a brief overview of the atomistic simulations on how the hierarchical structure and dynamics of DNA can be influenced by its sequences, base modifications, environmental factors and protein binding in the context of the protein-DNA interactions, gene regulation and structural organization of chromatin. We try to connect the DNA sequence, the hierarchical structures of DNA and gene regulation.

Binding Dynamics of siRNA with Selected Lipopeptides: A Computer-Aided Study of the Effect of Lipopeptides' Functional Groups and Stereoisomerism

The engineering issues pertaining to nanoparticle systems toward targeted gene therapies have not been fully probed. Recent experiments have identified specific structural characteristics of a novel class of lipopeptides (LP) that may lead to potent nanocarriers intended as RNAi therapeutics, albeit the molecular mechanism that underlies their performance remains unexplored. We conducted molecular dynamics simulations in atomistic detail coupled with free energy computations to study the dynamics and thermodynamics of an acrylate- and an epoxide-derived LP, members of the aforesaid class, upon their binding to siRNA in aqueous solution aiming at examining structure-potency relations. We found that the entropic part of the free energy of binding predominates; moreover, the first LP class tends to disrupt the Watson-Crick base pairing of siRNA, whereas the latter leaves the double helix intact. Moreover, the identified tug-of-war effect between LP-water and LP-siRNA hydrogen bonding in the supramolecular complex can underpin synthesis routes toward tuning the association dynamics. Our simulations on two diastereomers of the epoxide-derived LP showed significant structural and energetics differences upon binding, as a result of steric effects imposed by the different absolute configurations at their chiral centers. These findings may serve as crucial design parameters toward modulating the interplay between complex stability and ease of releasing the nucleic acid drug into the cell.

Structure-mechanics statistical learning unravels the linkage between local rigidity and global flexibility in nucleic acids

The mechanical properties of nucleic acids underlie biological processes ranging from genome packaging to gene expression, but tracing their molecular origin has been difficult due to the structural and chemical complexity. We posit that concepts from machine learning can help to tackle this long-standing challenge. Here, we demonstrate the feasibility and advantage of this strategy through developing a structure-mechanics statistical learning scheme to elucidate how local rigidity in double-stranded (ds)DNA and dsRNA may lead to their global flexibility in bend, stretch, and twist. Specifically, the mechanical parameters in a heavy-atom elastic network model are computed from the trajectory data of all-atom molecular dynamics simulation. The results show that the inter-atomic springs for backbone and ribose puckering in dsRNA are stronger than those in dsDNA, but are similar in strengths for base-stacking and base-pairing. Our analysis shows that the experimental observation of dsDNA being easier to bend but harder to stretch than dsRNA comes mostly from the respective B- and A-form topologies. The computationally resolved composition of local rigidity indicates that the flexibility of both nucleic acids is mostly due to base-stacking. But for properties like twist-stretch coupling, backbone springs are shown to play a major role instead. The quantitative connection between local rigidity and global flexibility sets foundation for understanding how local binding and chemical modification of genetic materials effectuate longer-ranged regulatory signals.

The mechanical properties of nucleic acids underlie biological processes ranging from genome packaging to gene expression. We devise structural mechanics statistical learning method to reveal their molecular origin in terms of chemical interactions.

A multi-modal coarse grained model of DNA flexibility mappable to the atomistic level

We present a new coarse grained method for the simulation of duplex DNA. The algorithm uses a generalized multi-harmonic model that can represent any multi-normal distribution of helical parameters, thus avoiding caveats of current mesoscopic models for DNA simulation and representing a breakthrough in the field. The method has been parameterized from accurate parmbsc1 atomistic molecular dynamics simulations of all unique tetranucleotide sequences of DNA embedded in long duplexes and takes advantage of the correlation between helical states and backbone configurations to derive atomistic representations of DNA. The algorithm, which is implemented in a simple web interface and in a standalone package reproduces with high computational efficiency the structural landscape of long segments of DNA untreatable by atomistic molecular dynamics simulations.

SerraNA: a program to determine nucleic acids elasticity from simulation data

AT-rich motifs can generate extreme mechanical properties, which are critical for creating strong global bends when phased properly.

Modulation of the helical properties of DNA: next-to-nearest neighbour effects and beyond

We used extensive molecular dynamics simulations to study the structural and dynamic properties of the central d(TpA) step in the highly polymorphic d(CpTpApG) tetranucleotide. Contrary to the assumption of the dinucleotide-model and its nearest neighbours (tetranucleotide-model), the properties of the central d(TpA) step change quite significantly dependent on the next-to-nearest (hexanucleotide) sequence context and in a few cases are modulated by even remote neighbours (beyond next-to-nearest from the central TpA). Our results highlight the existence of previously undescribed dynamical mechanisms for the transmission of structural information into the DNA and demonstrate the existence of certain sequences with special physical properties that can impact on the global DNA structure and dynamics.

Constructing Controllable Logic Circuits Based on DNAzyme Activity

Recently, DNA molecules have been widely used to construct advanced logic devices due to their unique properties, such as a simple structure and predictable behavior. In fact, there are still many challenges in the process of building logic circuits. Among them, the scalability of the logic circuit and the elimination of the crosstalk of the cascade circuit have become the focus of research. Inspired by biological allosteric regulation, we developed a controllable molecular logic circuit strategy based on the activity of DNAzyme. The E6 DNAzyme sequence was temporarily blocked by hairpin DNA and activated under appropriate input trigger conditions. Using a substrate with ribonucleobase (rA) modification as the detection strand, a series of binary basic logic gates (YES, AND, and INHIBIT) were implemented on the computational component platform. At the same time, we demonstrate a parallel demultiplexer and two multi-level cascade circuits (YES-YES and YES-Three input AND (YES-TAND)). In addition, the leakage of the cascade process was reduced by exploring factors such as concentration and DNA structure. The proposed DNAzyme activity regulation strategy provides great potential for the expansion of logic circuits in the future.

Allosteric DNAzyme-based DNA logic circuit: operations and dynamic analysis

Recently, due to the dual roles of DNA and enzyme, DNAzyme has been widely used in the field of DNA circuit, which has a wide range of applications in bio-engineered system, information processing and biocomputing. In fact, the activity of DNAzymes was regulated by subunits assembly, pH control and metal ions triggers. However, those regulations required to change the sequences of whole DNAzyme, as separating parts and inserting extra DNA sequence. Inspired by the allosteric regulation of proteins in nature, a new allosteric strategy is proposed to regulate the activity of DNAzyme without DNA sequences changes. In this strategy, DNA strand displacement was used to regulate the DNAzyme structure, through which the activity of DNAzyme was well controlled. The strategy was applied to E6-type DNAzymes, and the operations of DNA logic circuit (YES, OR, AND, cascading and feedback) were established and simulated with the dynamic analyses. The allosteric regulation has potential to construct more complicated molecular systems, which can be applied to bio-sensing and detection.