Secondary Structure Design Research Articles

Bio-Inspired Secondary Levitation Structure Design for High-Temperature Superconducting Maglev Train

Bio-Inspired Secondary Levitation Structure Design for High-Temperature Superconducting Maglev Train

Towards a High-Affinity Peptidomimetic Targeting Proliferating Cell Nuclear Antigen from Aspergillus fumigatus.

Invasive fungal infections (IFIs) are prevalent in immunocompromised patients. Due to alarming levels of increasing resistance in clinical settings, new drugs targeting the major fungal pathogen Aspergillus fumigatus are required. Attractive drug targets are those involved in essential processes like DNA replication, such as proliferating cell nuclear antigens (PCNAs). PCNA has been previously studied in cancer research and presents a viable target for antifungals. Human PCNA interacts with the p21 protein, outcompeting binding proteins to halt DNA replication. The affinity of p21 for hPCNA has been shown to outcompete other associating proteins, presenting an attractive scaffold for peptidomimetic design. p21 has no A. fumigatus homolog to our knowledge, yet our group has previously demonstrated that human p21 can interact with A. fumigatus PCNA (afumPCNA). This suggests that a p21-based inhibitor could be designed to outcompete the native binding partners of afumPCNA to inhibit fungal growth. Here, we present an investigation of extensive structure-activity relationships between designed p21-based peptides and afumPCNA and the first crystal structure of a p21 peptide bound to afumPCNA, demonstrating that the A. fumigatus replication model uses a PIP-box sequence as the method for binding to afumPCNA. These results inform the new optimized secondary structure design of a potential peptidomimetic inhibitor of afumPCNA.

DNA Structure Design Is Improved Using an Artificially Expanded Alphabet of Base Pairs Including Loop and Mismatch Thermodynamic Parameters.

We show that in silico design of DNA secondary structures is improved by extending the base pairing alphabet beyond A-T and G-C to include the pair between 2-amino-8-(1'-β-d-2'-deoxyribofuranosyl)-imidazo-[1,2-a]-1,3,5-triazin-(8H)-4-one and 6-amino-3-(1'-β-d-2'-deoxyribofuranosyl)-5-nitro-(1H)-pyridin-2-one, abbreviated as P and Z. To obtain the thermodynamic parameters needed to include P-Z pairs in the designs, we performed 47 optical melting experiments and combined the results with previous work to fit free energy and enthalpy nearest neighbor folding parameters for P-Z pairs and G-Z wobble pairs. We find G-Z pairs have stability comparable to that of A-T pairs and should therefore be included as base pairs in structure prediction and design algorithms. Additionally, we extrapolated the set of loop, terminal mismatch, and dangling end parameters to include the P and Z nucleotides. These parameters were incorporated into the RNAstructure software package for secondary structure prediction and analysis. Using the RNAstructure Design program, we solved 99 of the 100 design problems posed by Eterna using the ACGT alphabet or supplementing it with P-Z pairs. Extending the alphabet reduced the propensity of sequences to fold into off-target structures, as evaluated by the normalized ensemble defect (NED). The NED values were improved relative to those from the Eterna example solutions in 91 of 99 cases in which Eterna-player solutions were provided. P-Z-containing designs had average NED values of 0.040, significantly below the 0.074 of standard-DNA-only designs, and inclusion of the P-Z pairs decreased the time needed to converge on a design. This work provides a sample pipeline for inclusion of any expanded alphabet nucleotides into prediction and design workflows.

Thermodynamic Basis for the Stabilization of Helical Peptoids by Chiral Sidechains.

Peptoids are a class of highly customizable biomimetic foldamers that retain properties from both proteins and polymers. It has been shown that peptoids can adopt peptide-like secondary structures through the careful selection of sidechain chemistries, but the underlying conformational landscapes that drive these assemblies at the molecular level remain poorly understood. Given the high flexibility of the peptoid backbone, it is essential that methods applied to study peptoid secondary structure formation possess the requisite sensitivity to discriminate between structurally similar yet energetically distinct microstates. In this work, a generalizable simulation scheme is used to robustly sample the complex folding landscape of various 12mer polypeptoids, resulting in a predictive model that links sidechain chemistry with preferential assembly into one of 12 accessible backbone motifs. Using a variant of the metadynamics sampling method, four peptoid dodecamers are simulated in water: sarcosine, N-(1-phenylmethyl)glycine (Npm), (S)-N-(1-phenylethyl)glycine (Nspe), and (R)-N-(1-phenylethyl)glycine (Nrpe)─to determine the underlying entropic and energetic impacts of hydrophobic and chiral peptoid sidechains on secondary structure formation. Our results indicate that the driving forces to assemble Nrpe and Nspe sequences into polyproline type-I helices in water are found to be enthalpically driven, with small benefits from an entropic gain for isomerization and steric strain due to the presence of the chiral center. The minor entropic gains from bulky chiral sidechains in Nrpe- and Nspe-containing peptoids can be explained through increased configurational entropy in the cis state. However, overall assembly into a helix is found to be overall entropically unfavorable. These results highlight the importance of considering the many various competing interactions in the rational design of peptoid secondary structure building blocks.

Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model

We report two generative deep learning models that predict amino acid sequences and 3D protein structures based on secondary structure design objectives via either overall content or per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity as they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in conditional generative design of various biological or engineering systems. Future work may include additional conditioning, and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.

Numerical analysis of the primary and secondary structural dynamic interaction effects on elastic floor response spectra

In modern seismic design, the assessment of seismic behavior in secondary structures relies on the evaluation of the primary structure's acceleration at the support of the secondary structure. To enable effective secondary structure design, a thorough understanding of the interaction between the primary and secondary structures is essential. This article conducts an analysis based on parametric data, delving into the dynamic interaction between these structures. In this study, both the elastic primary and secondary structures are represented as single-degree-of-freedom systems. The governing equations of motion for both the coupled and uncoupled systems are derived and solved using the numerical method. Subsequently, the floor response spectrum (FRS) is computed for both coupled and uncoupled configurations. This investigation focuses on the impact of three crucial parameters: the tuning ratio (T_r), the mass ratio (μ), and the damping ratio (ξ_s) on the FRS. The analytical findings reveal that dynamic interaction does not significantly affect the FRS when the mass ratio is very low, at 0.1%. However, for a range of 0.8 ≤ T_r ≤ 1.2, dynamic interaction has a substantial influence on the FRS. Additionally, this study underscores that lower damping ratios in the secondary structure result in a more pronounced coupling effect on the FRS.

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.

Theoretical basis for stabilizing messenger RNA through secondary structure design.

RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term ‘superfolder’ mRNAs. These designs exhibit a wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity. Furthermore, their folding is robust to temperature, computer modeling method, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1 and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.

A Proline Mimetic for the Design of New Stable Secondary Structures: Solvent-Dependent Amide Bond Isomerization of (S)-Indoline-2-carboxylic Acid Derivatives.

A thorough experimental and computational study on the conformational properties of (S)-indoline-2-carboxylic acid derivatives has been conducted. Methyl (S)-1-acetylindoline-2-carboxylate, both a mimetic of proline and phenylalanine, shows a remarkable tendency toward the cis amide isomer when dissolved in polar solvents. This behavior is opposite to the general preference of proline for the trans isomer, making indoline-2-carboxylic acid a good candidate for the design of different secondary structures and new materials.

Safety Issues in the Seismic Design of Secondary Frameless Glass Structures

Glass is largely used in buildings, in the form of an innovative and versatile material. Both for novel and existing constructions, secondary glass systems are frequently realized to interact with primary components of different materials. In most cases, the structural challenge deriving from the intrinsic brittleness and vulnerability of glass is efficiently controlled via laminated (LG) multi-layer sections. However, further potential risks for people should be properly minimized, like for example, in the presence of extreme loads. This is the case of seismic regions, where dedicated calculation methods are required to accommodate displacement and resistance demands, but design specifications are rarely provided by existing standards for earthquake resistant buildings. Even more attention is needed for frameless glass systems in which the bracing members (i.e., continuous frames, cable-nets, etc.) are reduced to a minimum, in favour of metal point connections (i.e., bolts and mechanical fixings, friction clamps, etc.). This paper aims at discussing the current design requirements for the seismic performance assessment of these relatively simple but challenging structural solutions, with careful consideration for the Italian scenario, where a practical support for design can be found in the CNR-DT 210/2013 technical document. Based on a case-study system, major issues, open questions and uncertainties or critical aspects for the seismic analysis and design of secondary frameless glass assemblies are thus emphasized.

EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame.

Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold into specific base-pairing patterns, but computational algorithms generally remain inadequate for these secondary structure design tasks. The Eterna project has crowdsourced RNA design to human video game players in the form of puzzles that reach extraordinary difficulty. Here, we demonstrate that Eterna participants’ moves and strategies can be leveraged to improve automated computational RNA design. We present an eternamoves-large repository consisting of 1.8 million of player moves on 12 of the most-played Eterna puzzles as well as an eternamoves-select repository of 30,477 moves from the top 72 players on a select set of more advanced puzzles. On eternamoves-select, we present a multilayer convolutional neural network (CNN) EternaBrain that achieves test accuracies of 51% and 34% in base prediction and location prediction, respectively, suggesting that top players’ moves are partially stereotyped. Pipelining this CNN’s move predictions with single-action-playout (SAP) of six strategies compiled by human players solves 61 out of 100 independent puzzles in the Eterna100 benchmark. EternaBrain-SAP outperforms previously published RNA design algorithms and achieves similar or better performance than a newer generation of deep learning methods, while being largely orthogonal to these other methods. Our study provides useful lessons for future efforts to achieve human-competitive performance with automated RNA design algorithms.

Accelerated RNA secondary structure design using preselected sequences for helices and loops.

Nucleic acids can be designed to be nano-machines, pharmaceuticals, or probes. RNA secondary structures can form the basis of self-assembling nanostructures. There are only four natural RNA bases, therefore it can be difficult to design sequences that fold to a single, specified structure because many other structures are often possible for a given sequence. One approach taken by state-of-the-art sequence design methods is to select sequences that fold to the specified structure using stochastic, iterative refinement. The goal of this work is to accelerate design. Many existing iterative methods select and refine sequences one base pair and one unpaired nucleotide at a time. Here, the hypothesis that sequences can be preselected in order to accelerate design was tested. To this aim, a database was built of helix sequences that demonstrate thermodynamic features found in natural sequences and that also have little tendency to cross-hybridize. Additionally, a database was assembled of RNA loop sequences with low helix-formation propensity and little tendency to cross-hybridize with either the helices or other loops. These databases of preselected sequences accelerate the selection of sequences that fold with minimal ensemble defect by replacing some of the trial and error of current refinement approaches. When using the database of preselected sequences as compared to randomly chosen sequences, sequences for natural structures are designed 36 times faster, and random structures are designed six times faster. The sequences selected with the aid of the database have similar ensemble defect as those sequences selected at random. The sequence database is part of RNAstructure package at http://rna.urmc.rochester.edu/RNAstructure.html.

Rational design of hierarchical ZnO@Carbon nanoflower for high performance lithium ion battery anodes

The rational structure design and strong interfacial bonding are crucially desired for high performance zinc oxide (ZnO)/carbon composite electrodes. In this context, micro-nano secondary structure design and strong dopamine coating strategies are adopted for the fabrication of flower-like ZnO/carbon (ZnO@C nanoflowers) composite electrodes. The results show the ZnO@C nanoflowers (2–6 μm) are assembled by hierarchical ZnO nanosheets (∼27 nm) and continuous carbon framework. The micro-nano secondary architecture can facilitate the penetration of electrolyte, shorten lithium ions diffusion length, and hinder the aggregation of the nanosheets. Moreover, the strong chemical interaction between ZnO and coating carbon layer via C-Zn bond improves structure stability as well as the electronic conductivity. As a synergistic result, when evaluated as lithium ion batteries (LIBs) anode, the ZnO@C nanoflower electrodes show high reversible capacity of ca. 1200 mA h g−1 at 0.1 A g−1 after 80 cycles. As well as good long-cycling stability (638 and 420 mA h g−1 at 1 and 5 A g−1 after 500 cycles, respectively) and excellent rate capability. Therefore, this rational design of ZnO@C nanoflowers electrode is a promising anode for high-performance LIBs.

Principles for Predicting RNA Secondary Structure Design Difficulty

Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess “designability” of single RNA structures, as well as of switches for in vitro and in vivo applications.

Review of Approaches for Analysing Secondary Structures in Earthquakes and Evaluation of Floor Response Spectrum Approach

Secondary structures are the members that are not part of the primary load-bearing components in a structural system. Although not intended to bear loads, secondary structures could be subjected to earthquake loading that may lead to failures. Damage to secondary structures could pose significant threats to life safety, prevent buildings from functioning and result in major economic loss. During past decades, a considerable amount of research efforts has been dedicated to develop rational approaches for seismic analysis of secondary structures. This paper aimed to assess these developments to today's knowledge as a reference for more accurate design. The review began with a brief description of the response characteristics of secondary structure under seismic loading, especially focusing on the factors that influence the responses. An appraisal of current numerical and experimental analysis methods of secondary structure is presented. Results from experimental work are used to validate the reliability of floor response spectrum and current design provision. Finally, an outlook of future possible research direction for more realistic design of secondary structures is given.

RNA-Redesign: a web server for fixed-backbone 3D design of RNA.

RNA is rising in importance as a design medium for interrogating fundamental biology and for developing therapeutic and bioengineering applications. While there are several online servers for design of RNA secondary structure, there are no tools available for the rational design of 3D RNA structure. Here we present RNA-Redesign (http://rnaredesign.stanford.edu), an online 3D design tool for RNA. This resource utilizes fixed-backbone design to optimize the sequence identity and nucleobase conformations of an RNA to match a desired backbone, analogous to fundamental tools that underlie rational protein engineering. The resulting sequences suggest thermostabilizing mutations that can be experimentally verified. Further, sequence preferences that differ between natural and computationally designed sequences can suggest whether natural sequences possess functional constraints besides folding stability, such as cofactor binding or conformational switching. Finally, for biochemical studies, the designed sequences can suggest experimental tests of 3D models, including concomitant mutation of base triples. In addition to the designs generated, detailed graphical analysis is presented through an integrated and user-friendly environment.

Sequence and conformational preferences at termini of α-helices in membrane proteins: role of the helix environment.

α-Helices are amongst the most common secondary structural elements seen in membrane proteins and are packed in the form of helix bundles. These α-helices encounter varying external environments (hydrophobic, hydrophilic) that may influence the sequence preferences at their N and C-termini. The role of the external environment in stabilization of the helix termini in membrane proteins is still unknown. Here we analyze α-helices in a high-resolution dataset of integral α-helical membrane proteins and establish that their sequence and conformational preferences differ from those in globular proteins. We specifically examine these preferences at the N and C-termini in helices initiating/terminating inside the membrane core as well as in linkers connecting these transmembrane helices. We find that the sequence preferences and structural motifs at capping (Ncap and Ccap) and near-helical (N' and C') positions are influenced by a combination of features including the membrane environment and the innate helix initiation and termination property of residues forming structural motifs. We also find that a large number of helix termini which do not form any particular capping motif are stabilized by formation of hydrogen bonds and hydrophobic interactions contributed from the neighboring helices in the membrane protein. We further validate the sequence preferences obtained from our analysis with data from an ultradeep sequencing study that identifies evolutionarily conserved amino acids in the rat neurotensin receptor. The results from our analysis provide insights for the secondary structure prediction, modeling and design of membrane proteins.

Dynamics in Sequence Space for RNA Secondary Structure Design.

We have implemented a method for the design of RNA sequences that should fold to arbitrary secondary structures. A popular energy model allows one to take the derivative with respect to composition, which can then be interpreted as a force and used for Newtonian dynamics in sequence space. Combined with a negative design term, one can rapidly sample sequences which are compatible with a desired secondary structure via simulated annealing. Results for 360 structures were compared with those from another nucleic acid design program using measures such as the probability of the target structure and an ensemble-weighted distance to the target structure.

α/β-Peptide foldamers: state of the art

Interplay between proteins, nucleic acids, carbohydrates and/or lipids is involved in almost every process in life on earth. As a consequence, a wide range of diseases results from abnormal interactions of such biomolecules. The main motivation of foldamer science is the development of scaffolds that are capable of adopting defined structures, mimicking parts of biological protagonists in their function. Among the most fundamental interactions in living beings are those between proteins, the so called protein--protein interactions (PPIs). Therefore, peptidic foldamers bear the promise to be an important tool for the inhibition of PPIs, as they are structurally most similar to the original proteins. The great number of possible permutations given by the combination of proteinogenic α-amino acid residues along with β-amino acids opens the door for a larger pool of accessible structures with potential applications. Despite the increasing amount of new secondary structure motifs, only few examples for tertiary and quaternary structure design, as well as inhibition of PPIs, have been realized so far. In this review, we summarize the current knowledge and recent progress made in the field of α/β-peptide foldamers beginning from secondary structure design up to highly sophisticated biological applications, such as protein surface recognition and inhibition of HIV cell entry.

Design of Ferrocene-Dipeptide Bioorganometallic Conjugates To Induce Chirality-Organized Structures

The highly ordered molecular assemblies in proteins can have a variety of functions, as observed in enzymes, receptors, and the like. Synthetic scientists are constructing bioinspired systems by harnessing the self-assembling properties of short peptides. Secondary structures such as alpha-helices, beta-sheets, and beta-turns are important in protein folding, which is mostly directed and stabilized by hydrogen bonding and the hydrophobic interactions of side chains. The design of secondary structure mimics that are composed of short peptides has attracted much attention, both for gaining fundamental insight into the factors affecting protein folding and for developing pharmacologically useful compounds, artificial receptors, asymmetric catalysts, and new materials. Ferrocenes are an organometallic scaffold with a central reverse-turn unit based on the inter-ring spacing of about 3.3 A, which is a suitable distance for hydrogen bonding between attached peptide strands. The conjugation of organometallic compounds with biomolecules such as amino acids, peptides, and DNA should provide novel systems that reflect properties of both the ferrocene and the biologically derived moieties. In this Account, we focus on recent advances in the design of ferrocene-peptide bioconjugates, which help illustrate the peptidomimetic basis for protein folding and the means of constructing highly ordered molecular assemblies. Ferrocene-peptide bioconjugates are constructed to form chirality-organized structures in both solid and solution states. The ferrocene serves as a reliable organometallic scaffold for the construction of protein secondary structures via intramolecular hydrogen bonding: the attached dipeptide strands are constrained within the appropriate dimensions. The introduction of the chiral dipeptide chains into the ferrocene scaffold induces the conformational enantiomerization of the ferrocenyl moiety; the chirality-organized structure results from intramolecular hydrogen bonding. The configuration and sequence of the amino acids are instrumental in the process. Regulation of the directionality and specificity of hydrogen bonding is a key component in the design of various molecular assemblies. Ferrocene-peptide bioconjugates also have a strong tendency to self-assemble through the contributions of available hydrogen-bonding donors in the solid state. Some ferrocene-peptide bioconjugates bearing only one dipeptide chain exhibit a helically ordered molecular assembly through a network of intermolecular (rather than intramolecular) hydrogen bonds. The propensity to form the chiral helicity appears to be controlled by the chirality of the dipeptide chains. Organization of host molecules is a useful strategy for forming artificial receptors. The conformationally regulated ferrocene-peptide bioconjugate provides the chirality-organized binding site for size-selective and chiral recognition of dicarboxylic acids through multipoint hydrogen bonds. Metal ions serve a variety of purposes in proteins, including structural stabilization for biological function. The complexation of ferrocene-peptide bioconjugates with palladium(II) compounds not only stabilizes the chirality conformational regulation but also induces conformational regulation of the dipeptide chain through complexation and intramolecular chirality organization. Construction of the chirality-organized ferrocene-peptide bioconjugates is also achieved by metal-directed assembly. These varied examples amply demonstrate the value of ferrocene-peptide bioconjugates in asserting architectural control over highly ordered molecular assemblies.