Predicting thermodynamic properties of RNA

Intelligent guide RNA: dual toehold switches for modulating luciferase in the presence of trigger RNA

The CRISPR system finds extensive application in molecular biology, but its continuous activity can yield adverse effects. Leveraging programmable CRISPR/Cas9 function via nano-device mediation effectively mitigates these drawbacks. The integration of RNA-sensing platforms into CRISPR thus empowers it as a potent tool for processing internal cell data and modulating gene activity. Here, an intelligent guide RNA-a cis-repressed gRNA synthetic circuit enabling efficient recognition of specific trigger RNAs-is developed. This platform carries two toehold switches and includes an inhibited CrRNA sequence. In this system, the presence of cognate trigger RNA promotes precise binding to the first toehold site, initiating a cascade that releases CrRNA to target a reporter gene (luciferase) in this study. Decoupling the CrRNA segment from the trigger RNA enhances the potential of this genetic logic circuit to respond to specific cellular circumstances, offering promise as a synthetic biology platform.

Kinetic dissection of pre-crRNA binding and processing by CRISPR-Cas12a

CRISPR-Cas12a binds and processes a single pre-crRNA during maturation, providing a simple tool for genome editing applications. Here, we constructed a kinetic and thermodynamic framework for pre-crRNA processing by Cas12a in vitro, and we measured the contributions of distinct regions of the pre-crRNA to this reaction. We find that the pre-crRNA binds rapidly and extraordinarily tightly to Cas12a (K d = 0.6 pM), such that pre-crRNA binding is fully rate limiting for processing and therefore determines the specificity of Cas12a for different pre-crRNAs. The guide sequence contributes 10-fold to the binding affinity of the pre-crRNA, while deletion of an upstream sequence has no significant effect. After processing, the mature crRNA remains very tightly bound to Cas12a with a comparable affinity. Strikingly, the affinity contribution of the guide region increases to 600-fold after processing, suggesting that additional contacts are formed and may preorder the crRNA for efficient DNA target recognition. Using a direct competition assay, we find that pre-crRNA-binding specificity is robust to changes in the guide sequence, addition of a 3' extension, and secondary structure within the guide region. However, stable secondary structure in the guide region can strongly inhibit DNA targeting, indicating that care should be taken in crRNA design. Together, our results provide a quantitative framework for pre-crRNA binding and processing by Cas12a and suggest strategies for optimizing crRNA design in genome editing applications.

START: A Versatile Platform for Bacterial Ligand Sensing with Programmable Performances

Recognition of signaling molecules for coordinated regulation of target genes is a fundamental process for biological systems. Cells often rely on transcription factors to accomplish these intricate tasks, yet the subtle conformational changes of protein structures, coupled with the complexity of intertwined protein interaction networks, pose challenges for repurposing these for bioengineering applications. This study introduces a novel platform for ligand-responsive gene regulation, termed START (Synthetic Trans-Acting Riboswitch with Triggering RNA). Inspired by the bacterial ligand sensing system, riboswitch, and the synthetic gene regulator, toehold switch, the START platform enables the implementation of synthetic biosensors for various ligands. Rational sequence design with targeted domain optimization yields high-performance STARTs with a dynamic range up to 67.29-fold and a tunable ligand sensitivity, providing a simple and intuitive strategy for sensor engineering. The START platform also exhibits modularity and composability to allow flexible genetic circuit construction, enabling seamless implementation of OR, AND, and NOT Boolean logic gates for multiple ligand inputs. The START design principle is capable of broadening the suite of synthetic biosensors for diverse chemical and protein ligands, providing a novel riboregulator chassis for synthetic biology and bioengineering applications.

Single-molecule force spectroscopy of toehold-mediated strand displacement

Toehold-mediated strand displacement (TMSD) is extensively utilized in dynamic DNA nanotechnology and for a wide range of DNA or RNA-based reaction circuits. Investigation of TMSD kinetics typically relies on bulk fluorescence measurements providing effective, bulk-averaged reaction rates. Information on individual molecules or even base pairs is scarce. In this work, we explore the dynamics of strand displacement processes at the single-molecule level using single-molecule force spectroscopy with a microfluidics-enhanced optical trap supported by state-of-the-art coarse-grained simulations. By applying force, we can trigger and observe TMSD in real-time with microsecond and nanometer resolution. We find TMSD proceeds very rapidly under load with single step times of 1 µs. Tuning invasion efficiency by introducing mismatches allows studying thousands of forward/backward invasion events on a single molecule and analyze the kinetics of the invasion process. Extrapolation to zero force reveals single step times for DNA invading DNA four times faster than for RNA invading RNA. We also study the kinetics of DNA invading RNA, a process that in the absence of force would rarely occur. Our results reveal the importance of sequence effects for the TMSD process and have relevance for a wide range of applications in nucleic acid nanotechnology and synthetic biology.

Tailored Synthetic sRNAs Dynamically Tune Multilayer Genetic Circuits

Predictable and controllable tuning of genetic circuits to regulate gene expression, including modulation of existing circuits or constructs without the need for redesign or rebuilding, is a persistent challenge in synthetic biology. Here, we propose rationally designed new small RNAs (sRNAs) that dynamically modulate gene expression of genetic circuits with a broad range (high, medium, and low) of repression. We designed multiple multilayer genetic circuits in which the variable effector element is a transcription factor (TF) controlling downstream the production of a reporter protein. The sRNAs target TFs instead of a reporter gene, and harnessing the intrinsic RNA-interference pathway in E. coli allowed for a wide range of expression modulation of the reporter protein, including the most difficult to achieve dynamic switch to an OFF state. The synthetic sRNAs are expressed independently of the circuit(s), thus allowing for repression without modifying the circuit itself. Our work provides a frame for achieving independent modulation of gene expression and dynamic and modular control of the multilayer genetic circuits by only including an independent control circuit expressing synthetic sRNAs, without altering the structure of existing genetic circuits.

Computational design and experimental verification of pseudoknotted ribozymes

The design of new RNA sequences that retain the function of a model RNA structure is a challenge in bioinformatics because of the structural complexity of these molecules. RNA can fold into its secondary and tertiary structures by forming stem-loops and pseudoknots. A pseudoknot is a set of base pairs between a region within a stem-loop and nucleotides outside of this stem-loop; this motif is very important for numerous functional structures. It is important for any computational design algorithm to take into account these interactions to give a reliable result for any structures that include pseudoknots. In our study, we experimentally validated synthetic ribozymes designed by Enzymer, which implements algorithms allowing for the design of pseudoknots. Enzymer is a program that uses an inverse folding approach to design pseudoknotted RNAs; we used it in this study to design two types of ribozymes. The ribozymes tested were the hammerhead and the glmS, which have a self-cleaving activity that allows them to liberate the new RNA genome copy during rolling-circle replication or to control the expression of the downstream genes, respectively. We demonstrated the efficiency of Enzymer by showing that the pseudoknotted hammerhead and glmS ribozymes sequences it designed were extensively modified compared to wild-type sequences and were still active.

Nucleic Acid Structure Prediction Including Pseudoknots Through Direct Enumeration of States: A User's Guide to the LandscapeFold Algorithm

Here we detail the LandscapeFold secondary structure prediction algorithm and how it is used. The algorithm was previously described and tested in (Kimchi O et al., Biophys J 117(3):520-532, 2019), though it was not named there. The algorithm directly enumerates all possible secondary structures into which up to two RNA or single-stranded DNA sequences can fold. It uses a polymer physics model to estimate the configurational entropy of structures including complex pseudoknots. We detail each of these steps and ways in which the user can adjust the algorithm as desired. The code is available on the GitHub repository https://github.com/ofer-kimchi/LandscapeFold .

Biological solution conditions and flanking sequence modulate LLPS of RNA G-quadruplex structures

Guanine-rich regions of DNA or RNA can form structures with two or more consecutive G-quartets called G-quadruplexes (GQ). Recent studies reveal the potential for these structures to aggregate in vitro. Here, we report effects of in vivo concentrations of additives-amino acids, nucleotides, and crowding agents-on the structure and solution behavior of RNAs containing GQ-forming sequences. We found that cytosine nucleotides destabilize a model GQ structure at biological salt concentrations, while free amino acids and other nucleotides do not do so to a substantial degree. We also report that the tendency of folded GQs to form droplets or to aggregate depends on the nature of flanking sequence and the presence of additives. Notably, in the presence of biological amounts of polyamines, flanking regions on the 5'-end of the RNA drive more droplet-like phase separation, while flanking regions on the 3'-end, as well as both the 5'- and 3'-ends, induce more condensed, granular structures. Finally, we provide an example of a biological sequence in the presence of polyamines and show that crowders such as PEG and dextran can selectively cause its phase separation. These findings have implications for the participation of GQS in LLPS in vivo.

A paper-based assay for the colorimetric detection of SARS-CoV-2 variants at single-nucleotide resolution

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has highlighted the need for versatile diagnostic assays that can discriminate among emerging variants of the virus. Here we report the development and performance benchmarking of an inexpensive (approximately US$0.30 per test) assay for the rapid (sample-to-answer time within 30 min) colorimetric detection of SARS-CoV-2 variants. The assay, which we integrated into foldable paper strips, leverages nucleic acid strand-displacement reactions, the thermodynamic energy penalty associated with single-base-pair mismatches and the metal-ion-controlled enzymatic cleavage of urea to amplify the recognition of viral RNAs for the colorimetric readout of changes in pH via a smartphone. For 50 throat swab samples, the assay simultaneously detected the presence of SARS-CoV-2 and mutations specific to the SARS-CoV-2 variants Alpha, Beta and Gamma, with 100% concordance with real-time quantitative polymerase chain reaction and RNA sequencing. Customizable and inexpensive paper-based assays for the detection of viruses and their variants may facilitate viral surveillance.

Decoding RNA Editing Sites Through Transcriptome Analysis in Rice Under Alkaline Stress

Ribonucleic acid editing (RE) is a post-transcriptional process that altered the genetics of RNA which provide the extra level of gene expression through insertion, deletions, and substitutions. In animals, it converts nucleotide residues C-U. Similarly in plants, the role of RNA editing sites (RES) in rice under alkaline stress is not fully studied. Rice is a staple food for most of the world population. Alkaline stress cause reduction in yield. Here, we explored the effect of alkaline stress on RES in the whole mRNA from rice chloroplast and mitochondria. Ribonucleic acid editing sites in both genomes (3336 RESs) including chloroplast (345 RESs) and mitochondria (2991 RESs) with average RES efficiency ∼55% were predicted. Our findings showed that majority of editing events found in non-synonymous codon changes and change trend in amino acids was hydrophobic. Four types of RNA editing A-G (A-I), C-T (C-U), G-A, and T-C were identified in treated and untreated samples. Overall, RNA editing efficiency was increased in the treated samples. Analysis of Gene Ontology revealed that mapped genes were engaged in many biological functions and molecular processes. We also checked the expression of pentatricopeptide repeat (PPR), organelle zinc-finger (OZI), and multiple organellar RNA editing factors/RNA editing factor interacting proteins genes in control and treatment, results revealed upregulation of PPR and OZ1 genes in treated samples. This induction showed the role of these genes in RNA editing. The current findings report that RNA editing increased under alkaline stress which may contribute in adaptation for rice by changing amino acids in edited genes (88 genes). These findings will provide basis for identification of RES in other crops and also will be useful in alkaline tolerance development in rice.

Thermodynamic characterization of naturally occurring RNA pentaloops

RNA folding is hierarchical; therefore, predicting RNA secondary structure from sequence is an intermediate step in predicting tertiary structure. Secondary structure prediction is based on a nearest neighbor model using free energy minimization. To improve secondary structure prediction, all types of naturally occurring secondary structure motifs need to be thermodynamically characterized. However, not all secondary structure motifs are well characterized. Pentaloops, the second most abundant hairpin size, is one such uncharacterized motif. In fact, the current thermodynamic model used to predict the stability of pentaloops was derived from a small data set of pentaloops and from data for other hairpins of different sizes. Here, the most commonly occurring pentaloops were identified and optically melted. New experimental data for 22 pentaloop sequences were combined with previously published data for nine pentaloop sequences. Using linear regression, a pentaloop-specific model was derived. This new model is simpler and more accurate than the current model. The new experimental data and improved model can be incorporated into software that is used to predict RNA secondary structure from sequence.

VfoldMCPX: predicting multistrand RNA complexes

Multistrand RNA complexes play a critical role in RNA-related biological processes. The understanding of RNA functions and the rational design of RNA nanostructures require accurate prediction of the structure and folding stability of the complexes, including those containing pseudoknots. Here, we present VfoldMCPX, a new model for predicting two-dimensional (2D) structures and folding stabilities of multistrand RNA complexes. Based on a partition function-based algorithm combined with physical loop free energy parameters, the VfoldMCPX model predicts not only the native structure but also the folding stability of the complex. An important advantage of the model is the ability to treat pseudoknotted structures. Extensive tests on structure predictions show the VfoldMCPX model provides improved accuracy for multistranded RNA complexes, especially for RNA complexes with three or more strands and/or containing pseudoknots. We have developed a freely accessible VfoldMCPX web server at http://rna.physics.missouri.edu/vfoldMCPX2.

RNA Structure Prediction, Analysis, and Design: An Introduction to Web-Based Tools

Understanding RNA structure has become critical in the study of RNA in their roles as mediators of biological processes. To aid in these studies, computational algorithms that utilize thermodynamics have been developed to predict RNA secondary structure. Due to the importance of intermolecular interactions, the algorithms have been expanded to determine and predict RNA-RNA hybridization. This chapter discusses popular webservers with the tools for RNA secondary structure prediction, RNA-RNA hybridization, and design. We address key features that distinguish common-functioning programs and their purposes for the interests of the user. Ultimately, we hope this review elucidates web-based tools researchers may take advantage of in their investigations of RNA structure and function.

Implementation of novel boolean logic gates for IMPLICATION and XOR functions using riboregulators

To date, several different types of synthetic genetic switches, including riboregulators, riboswitches, and toehold switches, have been developed to construct AND, OR, NOT, NAND, NOR, and NOT IMPLICATION (NIMP) gates. The logic gate can integrate multiple input signals following a set of algorithms and generate a response only if strictly defined conditions are met. However, there are still some logic gates that have not been implemented but are necessary to build complex genetic circuits. Here, based on the toehold switches and three-way-junction (3WJ) repressors, we designed two novel biological Boolean logic gates of IMPLICATION (IMP) and XOR. Subsequently, the outputs of these two logic gates were characterized by fluorescence analysis, indicating that they can achieve the truth tables of logical gates. Furthermore, the fluorescence intensity under the logical TRUE condition was significantly higher than under the logical FALSE condition, suggesting the high dynamic range of the ON/OFF ratios. Because of the programmability of synthetic RNA switches, the constructed RNA logic gates could serve as elementary units to build a versatile and powerful platform for translational regulation and RNA-based biological computation.

Design of Ribocomputing Devices for Complex Cellular Logic

The ability to control cell function is a critical goal for synthetic biology and motivates the development of ever-improving methods for precise regulation of gene expression. RNA-based systems represent powerful tools for this purpose since they can take full advantage of the predictable and programmable base pairing properties of RNA to control gene expression. This chapter is focused on the computational design of RNA-only biological circuits that can execute complex Boolean logic expressions in living cells. These ribocomputing devices use toehold switches as building blocks for circuit construction, integrating sensing, computation, and signal generation functions within a gate RNA transcript that regulates expression of a gene of interest. The gate RNA in turn assesses the assembly state of networks of interacting input RNAs to execute AND, OR, and NOT operations with high dynamic range in E. coli. Harnessing in silico tools for device design facilitates scaling of the circuits to complex logic expressions, including four-input AND, six-input OR, and disjunctive normal form expressions with up to 12 inputs. This molecular architecture provides an intuitive and modular strategy for devising logic systems that can be readily engineered using RNA sequence design software and applied in vivo and in vitro. In this chapter, we describe the process for designing ribocomputing devices from the generation of orthogonal toehold switch libraries through to their use as building blocks for AND, OR, and NOT circuitry.

Stability and Activity of the 10-23 DNAzyme Under Molecular Crowding Conditions

DNAzymes are biocatalysts that have been selected in vitro and their function inside cells (in vivo) is extremely low. Thus, almost all studies have been carried out in diluted solutions (in vitro). The cellular presence of molecules such as amino acids, polypeptides, alcohols, and sugars introduces forces that modify the kinetics and thermodynamics of DNAzyme-mediated catalysis. The crowded intracellular environment referred to as molecular crowding can be mimicked by adding high concentrations of natural or synthetic macromolecules to the reaction conditions. Here, we investigate the activity of the 10-23 DNAzyme and the stability of the DNAzyme:RNA complex under molecular crowding conditions. Therefore, we use a Förster resonance energy transfer (FRET)-based activity assay in combination with denaturing urea polyacrylamide gel electrophoresis and circular dichroism (CD) spectroscopy.

Kinetics of RNA and RNA:DNA Hybrid Strand Displacement

In nucleic acid nanotechnology, strand displacement is a widely used mechanism where one strand from a hybridized duplex is exchanged with an invading strand that binds to a toehold, a single-stranded region on the duplex. It is used to perform logic operations on a molecular level, initiate cascaded reactions, or even for in vivo diagnostics and treatments. While systematic experimental studies have been carried out to probe the kinetics of strand displacement in DNA with different toehold lengths, sequences, and mismatch positions, there has not been a comparable investigation of RNA or RNA-DNA hybrid systems. Here, we experimentally study how toehold length, toehold location (5' or 3' end of the strand), and mismatches influence the strand displacement kinetics. We observe reaction acceleration with increasing toehold length and placement of the toehold at the 5' end of the substrate. We find that mismatches closer to the interface of toehold and duplex slow down the reaction more than remote mismatches. A comparison of RNA and DNA displacement with hybrid displacement (RNA invading DNA or DNA invading RNA) is partly explainable by the thermodynamic stabilities of the respective toehold regions, but also suggests that the rearrangement from B-form to A-form helix in the case of RNA invading DNA might play a role in the kinetics.

Diagrammatic approaches to RNA structures with trinucleotide repeats

Trinucleotide repeat expansion disorders are associated with the overexpansion of (CNG) repeats on the genome. Messenger RNA transcripts of sequences with greater than 60–100 (CNG) tandem units have been implicated in trinucleotide repeat expansion disorder pathogenesis. In this work, we develop a diagrammatic theory to study the structural diversity of these (CNG)_n RNA sequences. Representing structural elements on the chain’s conformation by a set of graphs and employing elementary diagrammatic methods, we have formulated a renormalization procedure to re-sum these graphs and arrive at a closed-form expression for the ensemble partition function. With a simple approximation for the renormalization and applied to extended (CNG)_n sequences, this theory can comprehensively capture an infinite set of conformations with any number and any combination of duplexes, hairpins, multiway junctions, and quadruplexes. To quantify the diversity of different (CNG)_n ensembles, the analytical equations derived from the diagrammatic theory were solved numerically to derive equilibrium estimates for the secondary structural contents of the chains. The results suggest that the structural ensembles of (CNG)_n repeat sequence with n ∼60 are surprisingly diverse, and the distribution is sensitive to the ability of the N nucleotide to make noncanonical pairs and whether the (CNG)_n sequence can sustain stable quadruplexes. The results show how perturbations in the form of biases on the stabilities of the various structural motifs, duplexes, junctions, helices, and quadruplexes could affect the secondary structures of the chains and how these structures may switch when they are perturbed.

Computer-Aided Design of Active Pseudoknotted Hammerhead Ribozymes

Pseudoknots are important motifs for stabilizing the structure of functional RNAs. As an example, pseudoknotted hammerhead ribozymes are highly active compared to minimal ribozymes. The design of new RNA sequences that retain the function of a model RNA structure includes taking in account pseudoknots presence in the structure, which is usually a challenge for bioinformatics tools. Our method includes using "Enzymer," a software for designing RNA sequences with desired secondary structures that may include pseudoknots. Enzymer implements an efficient stochastic search and optimization algorithm to sample RNA sequences from low ensemble defect mutational landscape of an initial design template to generate an RNA sequence that is predicted to fold into the desired target structure.

A Unified Dynamic Programming Framework for the Analysis of Interacting Nucleic Acid Strands: Enhanced Models, Scalability, and Speed

Dynamic programming algorithms within the NUPACK software suite enable analysis of nucleic acid sequences over complex and test tube ensembles containing arbitrary numbers of interacting strand species, serving the needs of researchers in molecular programming, nucleic acid nanotechnology, synthetic biology, and across the life sciences. Here, to enhance the underlying physical model, ensure scalability for large calculations, and achieve dramatic speedups when calculating diverse physical quantities over complex and test tube ensembles, we introduce a unified dynamic programming framework that combines three ingredients: (1) recursions that specify the dependencies between subproblems and incorporate the details of the structural ensemble and the free energy model, (2) evaluation algebras that define the mathematical form of each subproblem, (3) operation orders that specify the computational trajectory through the dependency graph of subproblems. The physical model is enhanced using new recursions that operate over the complex ensemble including coaxial and dangle stacking subensembles. The recursions are coded generically and then compiled with a quantity-specific evaluation algebra and operation order to generate an executable for each physical quantity: partition function, equilibrium base-pairing probabilities, MFE energy and proxy structure, suboptimal proxy structures, and Boltzmann sampled structures. For large complexes (e.g., 30 000 nt), scalability is achieved for partition function calculations using an overflow-safe evaluation algebra, and for equilibrium base-pairing probabilities using a backtrack-free operation order. A new blockwise operation order that treats subcomplex blocks for the complex species in a test tube ensemble enables dramatic speedups (e.g., 20-120× ) using vectorization and caching. With these performance enhancements, equilibrium analysis of substantial test tube ensembles can be performed in ≤ 1 min on a single computational core (e.g., partition function and equilibrium concentration for all complex species of up to six strands formed from two strand species of 300 nt each, or for all complex species of up to two strands formed from 80 strand species of 100 nt each). A new sampling algorithm simultaneously samples multiple structures from the complex ensemble to yield speedups of an order of magnitude or more as the number of structures increases above ≈10³. These advances are available within the NUPACK 4.0 code base (www.nupack.org) which can be flexibly scripted using the all-new NUPACK Python module.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

Development of a Novel Class of Self-Assembling dsRNA Cancer Therapeutics: A Proof-of-Concept Investigation

Cancer has proven to be an extremely difficult challenge to treat. Several fundamental issues currently underlie cancer treatment, including differentiating self from nonself, functional coupling of the recognition and therapeutic components of various therapies, and the propensity of cancerous cells to develop resistance to common treatment modalities via evolutionary pressure. Given these limitations, there is an increasing need to develop an all-encompassing therapeutic that can uniquely target malignant cells, decouple recognition from treatment, and overcome evolutionarily driven cancer resistance. We describe herein a new class of programmable self-assembling double-stranded RNA (dsRNA)-based cancer therapeutics that uniquely targets aberrant genetic sequences and in a functionally decoupled manner, undergoes oncogenic RNA-activated displacement (ORAD), initiating a therapeutic cascade that induces apoptosis and immune activation. As a proof of concept, we show that RNA strands targeting the EWS/Fli1 fusion gene in Ewing sarcoma cells that are end blocked with phosphorothioate bonds and additionally sealed with a 2'-deoxyuridine (2'-U)-modified DNA protector can be used to induce specific and potent killing of cells containing the target oncogenic sequence but not wild type.

Developments of Riboswitches and Toehold Switches for Molecular Detection-Biosensing and Molecular Diagnostics

Riboswitches and toehold switches are considered to have potential for implementation in various fields, i.e., biosensing, metabolic engineering, and molecular diagnostics. The specific binding, programmability, and manipulability of these RNA-based molecules enable their intensive deployments in molecular detection as biosensors for regulating gene expressions, tracking metabolites, or detecting RNA sequences of pathogenic microorganisms. In this review, we will focus on the development of riboswitches and toehold switches in biosensing and molecular diagnostics. This review introduces the operating principles and the notable design features of riboswitches as well as toehold switches. Moreover, we will describe the advances and future directions of riboswitches and toehold switches in biosensing and molecular diagnostics.

Salt effect on thermodynamics and kinetics of a single RNA base pair

Due to the polyanionic nature of RNAs, the structural folding of RNAs are sensitive to solution salt conditions, while there is still lack of a deep understanding of the salt effect on the thermodynamics and kinetics of RNAs at a single base-pair level. In this work, the thermodynamic and the kinetic parameters for the base-pair AU closing/opening at different salt concentrations were calculated by 3-µsec all-atom molecular dynamics (MD) simulations at different temperatures. It was found that for the base-pair formation, the enthalpy change [Formula: see text] is nearly independent of salt concentration, while the entropy change [Formula: see text] exhibits a linear dependence on the logarithm of salt concentration, verifying the empirical assumption based on thermodynamic experiments. Our analyses revealed that such salt concentration dependence of the entropy change mainly results from the dependence of ion translational entropy change for the base pair closing/opening on salt concentration. Furthermore, the closing rate increases with the increasing of salt concentration, while the opening rate is nearly independent of salt concentration. Additionally, our analyses revealed that the free energy surface for describing the base-pair opening and closing dynamics becomes more rugged with the decrease of salt concentration.

Precise and Programmable Detection of Mutations Using Ultraspecific Riboregulators

The ability to identify single-nucleotide mutations is critical for probing cell biology and for precise detection of disease. However, the small differences in hybridization energy provided by single-base changes makes identification of these mutations challenging in living cells and complex reaction environments. Here, we report a class of de novo-designed prokaryotic riboregulators that provide ultraspecific RNA detection capabilities in vivo and in cell-free transcription-translation reactions. These single-nucleotide-specific programmable riboregulators (SNIPRs) provide over 100-fold differences in gene expression in response to target RNAs differing by a single nucleotide in E. coli and resolve single epitranscriptomic marks in vitro. By exploiting the programmable SNIPR design, we implement an automated design algorithm to develop riboregulators for a range of mutations associated with cancer, drug resistance, and genetic disorders. Integrating SNIPRs with portable paper-based cell-free reactions enables convenient isothermal detection of cancer-associated mutations from clinical samples and identification of Zika strains through unambiguous colorimetric reactions.

Boundaries in metagenomic screenings using lacZα-based vectors

Metagenomics approaches have been of high relevance for providing enzymes used in diverse industrial applications. In the current study, we have focused on the prospection of protease and glycosyl hydrolase activities from a soil sample by using the lacZα -based plasmid pSEVA232. For this, we used a functional screen based on skimmed milk agar and a pH indicator dye for detection of both enzymes, as previously reported in literature. Although we effectively identified positive clones in the screenings, subsequent experiments revealed that this phenotype was not because of the hydrolytic activity encoded in the metagenomic fragments, but rather due to the insertion of small metagenomic DNA fragments in frame within the coding region of the lacZ gene present in the original vector. Analyses of the thermodynamic stability of mRNA secondary structures indicated that recovering of positive clones was probably due to higher expression levels of the chimeric lacZα-genes in respect to the original from empty vector. We concluded that this method has a higher tendency for recovery false positive clones, when used in combination with a lacZα-based vector. As these vectors are massively used in functional metagenomic screenings, we highlight the importance of reporting boundaries in established metagenomic screenings methodologies.

An efficient simulated annealing algorithm for the RNA secondary structure prediction with Pseudoknots

BACKGROUND

RNA pseudoknot structures play an important role in biological processes. However, existing RNA secondary structure prediction algorithms cannot predict the pseudoknot structure efficiently. Although random matching can improve the number of base pairs, these non-consecutive base pairs cannot make contributions to reduce the free energy.

RESULT

In order to improve the efficiency of searching procedure, our algorithm take consecutive base pairs as the basic components. Firstly, our algorithm calculates and archive all the consecutive base pairs in triplet data structure, if the number of consecutive base pairs is greater than given minimum stem length. Secondly, the annealing schedule is adapted to select the optimal solution that has minimum free energy. Finally, the proposed algorithm is evaluated with the real instances in PseudoBase.

CONCLUSION

The experimental results have been demonstrated to provide a competitive and oftentimes better performance when compared against some chosen state-of-the-art RNA structure prediction algorithms.

De novo-designed translation-repressing riboregulators for multi-input cellular logic

Efforts to construct synthetic biological circuits with more complex functions have often been hindered by the idiosyncratic behavior, limited dynamic range, and crosstalk of commonly utilized parts. Here, we employ de novo RNA design to develop two high-performance translational repressors with sensing and logic capabilities. These synthetic riboregulators, termed toehold repressors and three-way junction (3WJ) repressors, detect transcripts with nearly arbitrary sequences, repress gene expression by up to 300-fold, and yield orthogonal sets of up to 15 devices. Automated forward engineering is used to improve toehold repressor dynamic range and SHAPE-Seq is applied to confirm the designed switching mechanism of 3WJ repressors in living cells. We integrate the modular repressors into biological circuits that execute universal NAND and NOR logic and evaluate the four-input expression NOT ((A1 AND A2) OR (B1 AND B2)) in Escherichia coli. These capabilities make toehold and 3WJ repressors valuable new tools for biotechnological applications.

A Polymer Physics Framework for the Entropy of Arbitrary Pseudoknots

The accurate prediction of RNA secondary structure from primary sequence has had enormous impact on research from the past 40 years. Although many algorithms are available to make these predictions, the inclusion of non-nested loops, termed pseudoknots, still poses challenges arising from two main factors: 1) no physical model exists to estimate the loop entropies of complex intramolecular pseudoknots, and 2) their NP-complete enumeration has impeded their study. Here, we address both challenges. First, we develop a polymer physics model that can address arbitrarily complex pseudoknots using only two parameters corresponding to concrete physical quantities-over an order of magnitude fewer than the sparsest state-of-the-art phenomenological methods. Second, by coupling this model to exhaustive enumeration of the set of possible structures, we compute the entire free energy landscape of secondary structures resulting from a primary RNA sequence. We demonstrate that for RNA structures of ∼80 nucleotides, with minimal heuristics, the complete enumeration of possible secondary structures can be accomplished quickly despite the NP-complete nature of the problem. We further show that despite our loop entropy model's parametric sparsity, it performs better than or on par with previously published methods in predicting both pseudoknotted and non-pseudoknotted structures on a benchmark data set of RNA structures of ≤80 nucleotides. We suggest ways in which the accuracy of the model can be further improved.

Conditional Guide RNAs: Programmable Conditional Regulation of CRISPR/Cas Function in Bacterial and Mammalian Cells via Dynamic RNA Nanotechnology

A guide RNA (gRNA) directs the function of a CRISPR protein effector to a target gene of choice, providing a versatile programmable platform for engineering diverse modes of synthetic regulation (edit, silence, induce, bind). However, the fact that gRNAs are constitutively active places limitations on the ability to confine gRNA activity to a desired location and time. To achieve programmable control over the scope of gRNA activity, here we apply principles from dynamic RNA nanotechnology to engineer conditional guide RNAs (cgRNAs) whose activity is dependent on the presence or absence of an RNA trigger. These cgRNAs are programmable at two levels, with the trigger-binding sequence controlling the scope of the effector activity and the target-binding sequence determining the subject of the effector activity. We demonstrate molecular mechanisms for both constitutively active cgRNAs that are conditionally inactivated by an RNA trigger (ON → OFF logic) and constitutively inactive cgRNAs that are conditionally activated by an RNA trigger (OFF → ON logic). For each mechanism, automated sequence design is performed using the reaction pathway designer within NUPACK to design an orthogonal library of three cgRNAs that respond to different RNA triggers. In E. coli expressing cgRNAs, triggers, and silencing dCas9 as the protein effector, we observe a median conditional response of ≈4-fold for an ON → OFF "terminator switch" mechanism, ≈15-fold for an ON → OFF "splinted switch" mechanism, and ≈3-fold for an OFF → ON "toehold switch" mechanism; the median crosstalk within each cgRNA/trigger library is <2%, ≈2%, and ≈20% for the three mechanisms. To test the portability of cgRNA mechanisms prototyped in bacteria to mammalian cells, as well as to test generalizability to different effector functions, we implemented the terminator switch in HEK 293T cells expressing inducing dCas9 as the protein effector, observing a median ON → OFF conditional response of ≈4-fold with median crosstalk of ≈30% for three orthogonal cgRNA/trigger pairs. By providing programmable control over both the scope and target of protein effector function, cgRNA regulators offer a promising platform for synthetic biology.

Structural prediction of RNA switches using conditional base-pair probabilities

An RNA switch triggers biological functions by toggling between two conformations. RNA switches include bacterial riboswitches, where ligand binding can stabilize a bound structure. For RNAs with only one stable structure, structural prediction usually just requires a straightforward free energy minimization, but for an RNA switch, the prediction of a less stable alternative structure is often computationally costly and even problematic. The current sampling-clustering method predicts stable and alternative structures by partitioning structures sampled from the energy landscape into two clusters, but it is very time-consuming. Instead, we predict the alternative structure of an RNA switch from conditional probability calculations within the energy landscape. First, our method excludes base pairs related to the most stable structure in the energy landscape. Then, it detects stable stems (“seeds”) in the remaining landscape. Finally, it folds an alternative structure prediction around a seed. While having comparable riboswitch classification performance, the conditional-probability computations had fewer adjustable parameters, offered greater predictive flexibility, and were more than one thousand times faster than the sampling step alone in sampling-clustering predictions, the competing standard. Overall, the described approach helps traverse thermodynamically improbable energy landscapes to find biologically significant substructures and structures rapidly and effectively.

Topological Constraints and Their Conformational Entropic Penalties on RNA Folds

Functional RNAs can fold into intricate structures using a number of different secondary and tertiary structural motifs. Many factors contribute to the overall free energy of the target fold. This study aims at quantifying the entropic costs coming from the loss of conformational freedom when the sugar-phosphate backbone is subjected to constraints imposed by secondary and tertiary contacts. Motivated by insights from topology theory, we design a diagrammatic scheme to represent different types of RNA structures so that constraints associated with a folded structure may be segregated into mutually independent subsets, enabling the total conformational entropy loss to be easily calculated as a sum of independent terms. We used high-throughput Monte Carlo simulations to simulate large ensembles of single-stranded RNA sequences in solution to validate the assumptions behind our diagrammatic scheme, examining the entropic costs for hairpin initiation and formation of many multiway junctions. Our diagrammatic scheme aids in the factorization of secondary/tertiary constraints into distinct topological classes and facilitates the discovery of interrelationships among multiple constraints on RNA folds. This perspective, which to our knowledge is novel, leads to useful insights into the inner workings of some functional RNA sequences, demonstrating how they might operate by transforming their structures among different topological classes.

Contribution of 3'T and 3'TT overhangs to the thermodynamic stability of model siRNA duplexes

Herein, we report comprehensive thermodynamic studies on 36 RNA/DNA duplexes designed as siRNA mimics to determine the energetic contribution of 3'T and 3'TT dangling ends. The thermodynamic effect induced by the presence of 3'T overhangs on the stability of RNA duplexes ranges from -0.28 to -0.92 kcal/mol and strongly depends on the type and orientation of the adjacent base pair. Further extension of the 3'-dangling end length, by a second T residue, results in additional stabilization of 0.14 to 0.21 kcal/mol. The results revealed that the thermodynamic contribution of 3'-dangling T and TT on RNA duplexes differs from the influence of 3'-dangling U and UU on RNA duplexes and 3'-dangling T and TT on DNA duplexes. This data suggests that using the contribution of 3'-dangling T values for RNA duplexes, instead of 3'-dangling T values for DNA duplexes or 3'-dangling U values for RNA duplexes, would improve the prediction of the stability of siRNA duplexes.

Molecular Mechanism for Folding Cooperativity of Functional RNAs in Living Organisms

A diverse set of organisms has adapted to live under extreme conditions. The molecular origin of the stability is unclear, however. It is not known whether the adaptation of functional RNAs, which have intricate tertiary structures, arises from strengthening of tertiary or secondary structure. Herein we evaluate effects of sequence changes on the thermostability of tRNAphe using experimental and computational approaches. To separate out effects of secondary and tertiary structure on thermostability, we modify base pairing strength in the acceptor stem, which does not participate in tertiary structure. In dilute solution conditions, strengthening secondary structure leads to non-two-state thermal denaturation curves and has small effects on thermostability, or the temperature at which tertiary structure and function are lost. In contrast, under cellular conditions with crowding and Mg2+-chelated amino acids, where two-state cooperative unfolding is maintained, strengthening secondary structure enhances thermostability. Investigation of stabilities of each tRNA stem across 44 organisms with a range of optimal growing temperatures revealed that organisms that grow in warmer environments have more stable stems. We also used Shannon entropies to identify positions of higher and lower information content, or sequence conservation, in tRNAphe and found that secondary structures have modest information content allowing them to drive thermal adaptation, while tertiary structures have maximal information content hindering them from participating in thermal adaptation. Base-paired regions with no tertiary structure and modest information content thus offer a facile evolutionary route to enhancing the thermostability of functional RNA by the simple molecular rules of base pairing.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Design of Adjacent Transcriptional Regions to Tune Gene Expression and Facilitate Circuit Construction

Polycistronic architecture is common for synthetic gene circuits, however, it remains unknown how expression of one gene is affected by the presence of other genes/noncoding regions in the operon, termed adjacent transcriptional regions (ATR). Here, we constructed synthetic operons with a reporter gene flanked by different ATRs, and we found that ATRs with high GC content, small size, and low folding energy lead to high gene expression. Based on these results, we built a model of gene expression and generated a metric that takes into account ATRs. We used the metric to design and construct logic gates with low basal expression and high sensitivity and nonlinearity. Furthermore, we rationally designed synthetic 5'ATRs with different GC content and sizes to tune protein expression levels over a 300-fold range and used these to build synthetic toggle switches with varying basal expression and degrees of bistability. Our comprehensive model and gene expression metric could facilitate the future engineering of more complex synthetic gene circuits.

Predicting Ion Effects in an RNA Conformational Equilibrium

We develop a partial charge-based tightly bound ion (PCTBI) model for the ion effects in RNA folding. On the basis of the Monte Carlo tightly bound ion (MCTBI) approach, the model can account for ion fluctuation and correlation effects, and can predict the ion distribution around the RNA. Furthermore, unlike the previous coarse-grained RNA charge models, where negative charges are placed on the phosphates only, the current new model considers the detailed all-atom partial charge distribution on the RNA. Thus, the model not only keeps the advantage of the MCTBI model, but also has the potential to provide important detailed information unattainable by the previous MCTBI models. For example, the model predicts the reduction in ion binding upon protein binding and ion-induced conformational switches. For hepatitis C virus genomic RNA, the model predicts a Mg²⁺-induced stabilization of a kissing motif for a cis-acting regulatory element in the genomic RNA. Extensive theory-experiment comparisons support the reliability of the theoretical predictions. Therefore, the model may serve as a robust starting point for further development of an accurate method for ion effects in an RNA conformational equilibrium and RNA-cofactor interactions.

The Importance of Being Modified: The Role of RNA Modifications in Translational Fidelity

The posttranscriptional modifications of tRNA's anticodon stem and loop (ASL) domain represent a third level, a third code, to the accuracy and efficiency of translating mRNA codons into the correct amino acid sequence of proteins. Modifications of tRNA's ASL domain are enzymatically synthesized and site specifically located at the anticodon wobble position-34 and 3'-adjacent to the anticodon at position-37. Degeneracy of the 64 Universal Genetic Codes and the limitation in the number of tRNA species require some tRNAs to decode more than one codon. The specific modification chemistries and their impact on the tRNA's ASL structure and dynamics enable one tRNA to decode cognate and "wobble codons" or to expand recognition to synonymous codons, all the while maintaining the translational reading frame. Some modified nucleosides' chemistries prestructure tRNA to read the two codons of a specific amino acid that shares a twofold degenerate codon box, and other chemistries allow a different tRNA to respond to all four codons of a fourfold degenerate codon box. Thus, tRNA ASL modifications are critical and mutations in genes for the modification enzymes and tRNA, the consequences of which is a lack of modification, lead to mistranslation and human disease. By optimizing tRNA anticodon chemistries, structure, and dynamics in all organisms, modifications ensure translational fidelity of mRNA transcripts.

Influence of two bulge loops on the stability of RNA duplexes

Fifty-three RNA duplexes containing two single nucleotide bulge loops were optically melted in 1 M NaCl in order to determine the thermodynamic parameters ΔH°, ΔS°, ΔG°₃₇, and T_M for each duplex. Because of the large number of possible combinations and lack of sequence effects observed previously, we limited our initial investigation to adenosine bulges, the most common naturally occurring bulge. For example, the following duplexes were investigated: 5'GGCAXYAGGC/3'CCG YX CCG, 5'GGCAXY GCC/3'CCG YXACGG, and 5'GGC XYAGCC/3'CCGAYX CGG. The identity of XY (where XY are Watson-Crick base pairs) and the total number of base pairs in the terminal and central stems were varied. As observed for duplexes with a single bulge loop, the effect of the two bulge loops on duplex stability is primarily influenced by non-nearest neighbor interactions. In particular, the stability of the stems influences the destabilization of the duplex by the inserted bulge loops. The model proposed to predict the influence of multiple bulge loops on duplex stability suggests that the destabilization of each bulge is related to the stability of the adjacent stems. A database of RNA secondary structures was examined to determine the naturally occurring abundance of duplexes containing multiple bulge loops. Of the 2000 examples found in the database, over 65% of the two bulge loops occur within 3 base pairs of each other. A database of RNA three-dimensional structures was examined to determine the structure of duplexes containing two single nucleotide bulge loops. The structures of the bulge loops are described.

On the conformational stability of the smallest RNA kissing complexes maintained through two G·C base pairs

Two identical 5'GACG3' tetra-loop motifs with different stem sequences (called H2 and H3) are found in the 5' end region of Moloney Murine Leukemia Virus (MMLV) genomic RNA. They play important roles in RNA dimerization and encapsidation through two identical tetra-loops (5'GACG3') forming a loop-to-loop kissing complex, the smallest RNA kissing complex ever found in nature. We examined the effects of a loop-closing base pair as well as a stem sequence on the conformational stability of the kissing complex. UV melting analysis and gel electrophoresis were performed on eight RNA sequences mimicking the H2 and H3 hairpin tetra-loops with variation in loop-closing base pairs. Our results show that changing the loop-closing base pair from the wildtype (5'A·U3' for H3, 5'U·A3' for H2) to 5'G·C3'/5'C·G3' has significant effect on the stability of the kissing complexes: the substitution to 5'C·G3' significantly decreases both thermal and mechanical stability, while switching to the 5'G·C3' significantly increases the mechanical stability only. The kissing complexes with the wildtype loop-closing base pairs (5'A·U3' for H3 and 5'U·A3' for H2) show different stability when attached to a different stem sequence (H2 stem vs. H3 stem). This suggests that not only the loop-closing base pair itself, but also the stem sequence, affects the conformational stability of the RNA kissing complex.

Chemical Tools for Dissecting the Role of lncRNAs in Epigenetic Regulation

Proper control and maintenance of gene expression is critical for cellular identity and maintenance. Transcription of RNA from the genome is intimately controlled by post-translational chemical modification of histone tails and DNA. Recent studies have demonstrated that chromatin-remodeling complexes seek out their target genomic loci through the help of noncoding RNA molecules. Within this Review, we will outline how the use of biochemical techniques has shed light on the mechanisms employed by RNA to guide these complexes and therefore control gene expression.

Blind tests of RNA nearest-neighbor energy prediction

The predictive modeling and design of biologically active RNA molecules requires understanding the energetic balance among their basic components. Rapid developments in computer simulation promise increasingly accurate recovery of RNA's nearest-neighbor (NN) free-energy parameters, but these methods have not been tested in predictive trials or on nonstandard nucleotides. Here, we present, to our knowledge, the first such tests through a RECCES-Rosetta (reweighting of energy-function collection with conformational ensemble sampling in Rosetta) framework that rigorously models conformational entropy, predicts previously unmeasured NN parameters, and estimates these values' systematic uncertainties. RECCES-Rosetta recovers the 10 NN parameters for Watson-Crick stacked base pairs and 32 single-nucleotide dangling-end parameters with unprecedented accuracies: rmsd of 0.28 kcal/mol and 0.41 kcal/mol, respectively. For set-aside test sets, RECCES-Rosetta gives rmsd values of 0.32 kcal/mol on eight stacked pairs involving G-U wobble pairs and 0.99 kcal/mol on seven stacked pairs involving nonstandard isocytidine-isoguanosine pairs. To more rigorously assess RECCES-Rosetta, we carried out four blind predictions for stacked pairs involving 2,6-diaminopurine-U pairs, which achieved 0.64 kcal/mol rmsd accuracy when tested by subsequent experiments. Overall, these results establish that computational methods can now blindly predict energetics of basic RNA motifs, including chemically modified variants, with consistently better than 1 kcal/mol accuracy. Systematic tests indicate that resolving the remaining discrepancies will require energy function improvements beyond simply reweighting component terms, and we propose further blind trials to test such efforts.

Monte Carlo Tightly Bound Ion Model: Predicting Ion-Binding Properties of RNA with Ion Correlations and Fluctuations

Experiments have suggested that ion correlation and fluctuation effects can be potentially important for multivalent ions in RNA folding. However, most existing computational methods for the ion electrostatics in RNA folding tend to ignore these effects. The previously reported tightly bound ion (TBI) model can treat ion correlation and fluctuation but its applicability to biologically important RNAs is severely limited by the low computational efficiency. Here, on the basis of Monte Carlo sampling for the many-body ion distribution, we develop a new computational model, the Monte Carlo tightly bound ion (MCTBI) model, for ion-binding properties around an RNA. Because of an enhanced sampling algorithm for ion distribution, the model leads to a significant improvement in computational efficiency. For example, for a 160-nt RNA, the model causes a more than 10-fold increase in the computational efficiency, and the improvement in computational efficiency is more pronounced for larger systems. Furthermore, unlike the earlier model that describes ion distribution using the number of bound ions around each nucleotide, the current MCTBI model is based on the three-dimensional coordinates of the ions. The higher efficiency of the model allows us to treat the ion effects for medium to large RNA molecules, RNA-ligand complexes, and RNA-protein complexes. This new model together with proper RNA conformational sampling and the energetics model may serve as a starting point for further development for the ion effects in RNA folding and conformational changes and for large nucleic acid systems.

Salt contribution to the flexibility of single-stranded nucleic acid offinite length

Nucleic acids are negatively charged macromolecules and their structure properties are strongly coupled to metal ions in solutions. In this article, the salt effects on the flexibility of single-stranded (ss) nucleic acid chain ranging from 12 to 120 nucleotides are investigated systematically by the coarse-grained Monte Carlo simulations where the salt ions are considered explicitly and the ss chain is modeled with the virtual-bond structural model. Our calculations show that, the increase of ion concentration causes the structural collapse of ss chain and multivalent ions are much more efficient in causing such collapse, and both trivalent/small divalent ions can induce more compact state than a random relaxation state. We found that monovalent, divalent, and trivalent ions can all overcharge ss chain, and the dominating source for such overcharging changes from ion-exclusion-volume effect to ion Coulomb correlations. In addition, the predicted Na(+) and Mg(2+)-dependent persistence length l(p)'s of ss nucleic acid are in accordance with the available experimental data, and through systematic calculations, we obtained the empirical formulas for l(p) as a function of [Na(+)], [Mg(2+)] and chain length.

Atomistic Free Energy Model for Nucleic Acids: Simulations of Single-Stranded DNA and the Entropy Landscape of RNA Stem-Loop Structures

While single-stranded (ss) segments of DNAs and RNAs are ubiquitous in biology, details about their structures have only recently begun to emerge. To study ssDNA and RNAs, we have developed a new Monte Carlo (MC) simulation using a free energy model for nucleic acids that has the atomisitic accuracy to capture fine molecular details of the sugar-phosphate backbone. Formulated on the basis of a first-principle calculation of the conformational entropy of the nucleic acid chain, this free energy model correctly reproduced both the long and short length-scale structural properties of ssDNA and RNAs in a rigorous comparison against recent data from fluorescence resonance energy transfer, small-angle X-ray scattering, force spectroscopy and fluorescence correlation transport measurements on sequences up to ∼100 nucleotides long. With this new MC algorithm, we conducted a comprehensive investigation of the entropy landscape of small RNA stem-loop structures. From a simulated ensemble of ∼10(6) equilibrium conformations, the entropy for the initiation of different size RNA hairpin loops was computed and compared against thermodynamic measurements. Starting from seeded hairpin loops, constrained MC simulations were then used to estimate the entropic costs associated with propagation of the stem. The numerical results provide new direct molecular insights into thermodynaimc measurement from macroscopic calorimetry and melting experiments.

Sequence Design for a Test Tube of Interacting Nucleic Acid Strands

We describe an algorithm for designing the equilibrium base-pairing properties of a test tube of interacting nucleic acid strands. A target test tube is specified as a set of desired "on-target" complexes, each with a target secondary structure and target concentration, and a set of undesired "off-target" complexes, each with vanishing target concentration. Sequence design is performed by optimizing the test tube ensemble defect, corresponding to the concentration of incorrectly paired nucleotides at equilibrium evaluated over the ensemble of the test tube. To reduce the computational cost of accepting or rejecting mutations to a random initial sequence, the structural ensemble of each on-target complex is hierarchically decomposed into a tree of conditional subensembles, yielding a forest of decomposition trees. Candidate sequences are evaluated efficiently at the leaf level of the decomposition forest by estimating the test tube ensemble defect from conditional physical properties calculated over the leaf subensembles. As optimized subsequences are merged toward the root level of the forest, any emergent defects are eliminated via ensemble redecomposition and sequence reoptimization. After successfully merging subsequences to the root level, the exact test tube ensemble defect is calculated for the first time, explicitly checking for the effect of the previously neglected off-target complexes. Any off-target complexes that form at appreciable concentration are hierarchically decomposed, added to the decomposition forest, and actively destabilized during subsequent forest reoptimization. For target test tubes representative of design challenges in the molecular programming and synthetic biology communities, our test tube design algorithm typically succeeds in achieving a normalized test tube ensemble defect ≤1% at a design cost within an order of magnitude of the cost of test tube analysis.

Physics-based RNA structure prediction

Despite the success of RNA secondary structure prediction for simple, short RNAs, the problem of predicting RNAs with long-range tertiary folds remains. Furthermore, RNA 3D structure prediction is hampered by the lack of the knowledge about the tertiary contacts and their thermodynamic parameters. Low-resolution structural modeling enables us to estimate the conformational entropies for a number of tertiary folds through rigorous statistical mechanical calculations. The models lead to 3D tertiary folds at coarse-grained level. The coarse-grained structures serve as the initial structures for all-atom molecular dynamics refinement to build the final all-atom 3D structures. In this paper, we present an overview of RNA computational models for secondary and tertiary structures’ predictions and then focus on a recently developed RNA statistical mechanical model—the Vfold model. The main emphasis is placed on the physics behind the models, including the treatment of the non-canonical interactions in secondary and tertiary structure modelings, and the correlations to RNA functions.