DSSR-enabled innovative schematics of 3D nucleic acid structures with PyMOL

Encodable DNA Hairpin Probes for Nanopore Multiplexed Target Detection

Owing to the co-occurrence of hazardous compounds, it is crucial to build multiple highly discriminative probe libraries for simultaneous determination. Drawing inspiration from nucleic acid barcodes, we developed a probe system that is exclusively based on the nucleic acid secondary structure's hairpin structure, which can be directly read by nanopores. The highly distinguishable hairpin probes were constructed, and a detailed explanation of the possible patterns in their design was provided. These probe-representative events measured through the α-hemolysin (α-HL) nanopores were both distinguished, either through visual observation or comparison of the nanopore parameters. Besides, the potential design pattern for probes with unique telegraphic switching between the two levels was also unveiled. Finally, these probes were utilized to realize simultaneous, ultrasensitive mycotoxin multiple-detection, and their prospective applications for the detection of proteins and microRNAs were presented, indicating their suitability for a wide range of sensing applications.

Machine learning-based prediction of DNA G-quadruplex folding topology with G4ShapePredictor

Deoxyribonucleic acid (DNA) is able to form non-canonical four-stranded helical structures with diverse folding patterns known as G-quadruplexes (G4s). G4 topologies are classified based on their relative strand orientation following the 5' to 3' phosphate backbone polarity. Broadly, G4 topologies are either parallel (4+0), antiparallel (2+2), or hybrid (3+1). G4s play crucial roles in biological processes such as DNA repair, DNA replication, transcription and have thus emerged as biological targets in drug design. While computational models have been developed to predict G4 formation, there is currently no existing model capable of predicting G4 folding topology based on its nucleic acid sequence. Therefore, we introduce G4ShapePredictor (G4SP), an application featuring a collection of multi-classification machine learning models that are trained on a custom G4 dataset combining entries from existing literature and in-house circular dichroism experiments. G4ShapePredictor is designed to accurately predict G4 folding topologies in potassium ( K + ) buffer based on its primary sequence and is able to incorporate a threshold optimization strategy allowing users to maximise precision. Furthermore, we have identified three topological sequence motifs that suggest specific G4 folding topologies of (4+0), (2+2) or (3+1) when utilising the decision-making mechanisms of G4ShapePredictor.

RNAMotifProfile: a graph-based approach to build RNA structural motif profiles

RNA structural motifs are the recurrent segments in RNA three-dimensional structures that play a crucial role in the functional diversity of RNAs. Understanding the similarities and variations within these recurrent motif groups is essential for gaining insights into RNA structure and function. While recurrent structural motifs are generally assumed to be composed of the same isosteric base interactions, this consistent pattern is not observed across all examples of these motifs. Existing methods for analyzing and comparing RNA structural motifs may overlook variations in base interactions and associated nucleotides. RNAMotifProfile is a novel profile-to-profile alignment algorithm that generates a comprehensive profile from a group of structural motifs, incorporating all base interactions and associated nucleotides at each position. By structurally aligning input motif instances using a guide-tree-based approach, RNAMotifProfile captures the similarities and variations within recurrent motif groups. Additionally, RNAMotifProfile can function as a motif search tool, enabling the identification of instances of a specific motif family by searching with the corresponding profile. The ability to generate accurate and comprehensive profiles for RNA structural motif families, and to search for these motifs, facilitates a deeper understanding of RNA structure-function relationships and potential applications in RNA engineering and therapeutic design.

Delta SARS-CoV-2 s2m Structure, Dynamics, and Entropy: Consequences of the G15U Mutation

Bioinformatic analysis of the Delta SARS-CoV-2 genome reveals a single nucleotide mutation (G15U) in the stem-loop II motif (s2m) relative to ancestral SARS-CoV-2. Despite sequence similarity, unexpected differences between SARS-CoV-2 and Delta SARS-CoV-2 s2m homodimerization experiments require the discovery of unknown structural and thermodynamic changes necessary to rationalize the data. Using our reported SARS-CoV-2 s2m model, we induced the G15U substitution and performed 3.5 microseconds of unbiased molecular dynamics simulation at 283 and 310 K. The resultant Delta s2m adopted a secondary structure consistent with our reported NMR data, resulting in significant deviations in the tertiary structure and dynamics from our SARS-CoV-2 s2m model. First, we find differences in the overall three-dimensional structure, where the characteristic 90° L-shaped kink of the SARS-CoV-2 s2m did not form in the Delta s2m resulting in a "linear" hairpin with limited bending dynamics. Delta s2m helical parameters are calculated to align closely with A-form RNA, effectively eliminating a hinge point to form the L-shape kink by correcting an upper stem defect in SARS-CoV-2 induced by a noncanonical and dynamic G:A base pair. Ultimately, the shape difference rationalizes the migration differences in reported electrophoresis experiments. Second, increased fluctuation of the Delta s2m palindromic sequence, within the terminal loop, compared to SARS-CoV-2 s2m results in an estimated increase of entropy of 6.8 kcal/mol at 310 K relative to the SARS-CoV-2 s2m. The entropic difference offers a unique perspective on why the Delta s2m homodimerizes less spontaneously, forming fewer kissing dimers and extended duplexes compared to SARS-CoV-2. In this work, both the L-shape reduction and palindromic entropic penalty provides an explanation of our reported in vitro electrophoresis homodimerization results. Ultimately, the structural, dynamical, and entropic differences between the SARS-CoV-2 s2m and Delta s2m serve to establish a foundation for future studies of the s2m function in the viral lifecycle.

G4Bank: A database of experimentally identified DNA G-quadruplex sequences

G-quadruplex (G4), a non-canonical nucleic acid structure, has been suggested to play a key role in important cellular processes including transcription, replication and cancer development. Recently, high-throughput sequencing approaches for G4 detection have provided a large amount of experimentally identified G4 data that reveal genome-wide G4 landscapes and enable the development of new methods for predicting potential G4s from sequences. Although several existing databases provide G4 experimental data and relevant biological information from different perspectives, there is no dedicated database to collect and analyze DNA G4 experimental data genome-widely. Here, we constructed G4Bank, a database of experimentally identified DNA G-quadruplex sequences. A total of 6,915,983 DNA G4s were collected from 13 organisms, and state-of-the-art prediction methods were performed to filter and analyze the G4 data. Therefore, G4Bank will facilitate users to access comprehensive G4 experimental data and enable sequence feature analysis of G4 for further investigation. The database of the experimentally identified DNA G-quadruplex sequences can be accessed at http://tubic.tju.edu.cn/g4bank/ .

Insights into the Differential Composition of Stem-Loop Structures of Nanoviruses and Their Impacts

Multipartite viruses package their genomic segments independently and mainly infect plants; few of them target animals. Nanoviridae is a family of multipartite single-stranded DNA (ssDNA) plant viruses that individually encapsidate ssDNAs of ~1 kb and transmit them through aphids without replication in aphid vectors, thereby causing important diseases in host plants, mainly leguminous crops. All of these components constitute an open reading frame to perform a specific role in nanovirus infection. All segments contain conserved inverted repeat sequences, potentially forming a stem-loop structure and a conserved nonanucleotide, TAGTATTAC, within a common region. This study investigated the variations in the stem-loop structure of nanovirus segments and their impact using molecular dynamics (MD) simulations and wet lab approaches. Although the accuracy of MD simulations is limited by force field approximations and simulation time scale, explicit solvent MD simulations were successfully used to analyze the important aspects of the stem-loop structure. This study involves the mutants' design, based on the variations in the stem-loop region and construction of infectious clones, followed by their inoculation and expression analysis, based on nanosecond dynamics of the stem-loop structure. The original stem-loop structures showed more conformational stability than mutant stem-loop structures. The mutant structures were expected to alter the neck region of the stem-loop by adding and switching nucleotides. Changes in conformational stability are suggested expression variations of the stem-loop structures found in host plants with nanovirus infection. However, our results can be a starting point for further structural and functional analysis of nanovirus infection. IMPORTANCE Nanoviruses comprise multiple segments, each with a single open reading frame to perform a specific function and an intergenic region with a conserved stem-loop region. The genome expression of a nanovirus has been an intriguing area but is still poorly understood. We attempted to investigate the variations in the stem-loop structure of nanovirus segments and their impact on viral expression. Our results show that the stem-loop composition is essential in controlling the virus segments' expression level.

Cellular mechanism of action of forsythiaside for the treatment of diabetic kidney disease

Background: Diabetic kidney disease (DKD) becomes the leading cause of death for end-stage renal disease, whereas the potential mechanism is unclear and effective therapy is still rare. Our study was designed to investigate the cellular mechanism of Forsythiaside against DKD. Materials and Methods: The targets of Forsythiaside and the DKD-related targets were obtained from databases. The overlapping targets in these two sets were regarded as potential targets for alleviation of DKD by Forsythiaside. The targets of diabetic podocytopathy and tubulopathy were also detected to clarify the mechanism of Forsythiaside ameliorating DKD from the cellular level. Results: Our results explored that PRKCA and RHOA were regarded as key therapeutic targets of Forsythiaside with excellent binding affinity for treating DKD podocytopathy. Enrichment analysis suggested the underlying mechanism was mainly focused on the oxidative stress and mTOR signaling pathway. The alleviated effects of Forsythiaside on the reactive oxidative species accumulation and PRKCA and RHOA proteins upregulation in podocytes were also confirmed. Conclusion: The present study elucidates that Forsythiaside exerts potential treatment against DKD which may act directly RHOA and PRKCA target by suppressing the oxidative stress pathway in podocytes. And Forsythiaside could be regarded as one of the candidate drugs dealing with DKD in future experimental or clinical researches.

Genetic characterization and evolution of H6N6 subtype avian influenza viruses

H6-subtype avian influenza virus (AIV) was prevalent in the world and could sporadically infect humans. Here, a new chicken-derived H6N6-subtype AIV strain A/chicken/Zhejiang/49/2021 (ZJ49) was isolated in Zhejiang Province, China in 2021. Phylogenetic analysis by Maximum likelihood methods showed that H6-subtype AIVs were classed into 13 groups according to HA gene. The ZJ49 strain belonged to the G12 group, which mainly consisted of strains from Asian and dominated in recent years. Based on NA gene, H6-subtype AIVs were divided into N6.1 and N6.2 clades according to the NA gene. The ZJ49 isolate was located in the N6.2e clade, which mainly consisted of the H5N6-subtype AIVs. Phylogenetic analysis by Bayesian methods showed that the effective quantity size of H6-subtype AIVs increased around 1990, reached a peak around 2015, declined after 2015, then kept in a stable level after 2018. The reassortment analysis predicted that the PB2, PA, and NA genes of ZJ49 may recombine with H5-subtype AIVs. The amino acid at 222 position of HA gene of ZJ49 strain mutated from A to V, suggesting that ZJ49 has a potential ability to cross species barriers. The four glycosylation sites were highly conserved, implying less impact on the fold and conception of HA stem structure. Our results revealed the complicated evolution, reassortment, and mutations of receptor binding sites of H6-subtype AIVs, which emphasize the importance to continuously monitor the epidemiology and evolution of H6-subtype AIVs.

Developing Community Resources for Nucleic Acid Structures

In this review, we describe the creation of the Nucleic Acid Database (NDB) at Rutgers University and how it became a testbed for the current infrastructure of the RCSB Protein Data Bank. We describe some of the special features of the NDB and how it has been used to enable research. Plans for the next phase as the Nucleic Acid Knowledgebase (NAKB) are summarized.

RNAStat: An Integrated Tool for Statistical Analysis of RNA 3D Structures

The 3D architectures of RNAs are essential for understanding their cellular functions. While an accurate scoring function based on the statistics of known RNA structures is a key component for successful RNA structure prediction or evaluation, there are few tools or web servers that can be directly used to make comprehensive statistical analysis for RNA 3D structures. In this work, we developed RNAStat, an integrated tool for making statistics on RNA 3D structures. For given RNA structures, RNAStat automatically calculates RNA structural properties such as size and shape, and shows their distributions. Based on the RNA structure annotation from DSSR, RNAStat provides statistical information of RNA secondary structure motifs including canonical/non-canonical base pairs, stems, and various loops. In particular, the geometry of base-pairing/stacking can be calculated in RNAStat by constructing a local coordinate system for each base. In addition, RNAStat also supplies the distribution of distance between any atoms to the users to help build distance-based RNA statistical potentials. To test the usability of the tool, we established a non-redundant RNA 3D structure dataset, and based on the dataset, we made a comprehensive statistical analysis on RNA structures, which could have the guiding significance for RNA structure modeling. The python code of RNAStat, the dataset used in this work, and corresponding statistical data files are freely available at GitHub (https://github.com/RNA-folding-lab/RNAStat).

ONQUADRO: a database of experimentally determined quadruplex structures

ONQUADRO is an advanced database system that supports the study of the structures of canonical and non-canonical quadruplexes. It combines a relational database that collects comprehensive information on tetrads, quadruplexes, and G4-helices; programs to compute structure parameters and visualise the data; scripts for statistical analysis; automatic updates and newsletter modules; and a web application that provides a user interface. The database is a self-updating resource, with new information arriving once a week. The preliminary data are downloaded from the Protein Data Bank, processed, annotated, and completed. As of August 2021, ONQUADRO contains 1,661 tetrads, 518 quadruplexes, and 30 G4-helices found in 467 experimentally determined 3D structures of nucleic acids. Users can view and download their description: sequence, secondary structure (dot-bracket, classical diagram, arc diagram), tertiary structure (ball-and-stick, surface or vdw-ball model, layer diagram), planarity, twist, rise, chi angle (value and type), loop characteristics, strand directionality, metal ions, ONZ, and Webba da Silva classification (the latter by loop topology and tetrad combination), origin structure ID, assembly ID, experimental method, and molecule type. The database is freely available at https://onquadro.cs.put.poznan.pl/. It can be used on both desktop computers and mobile devices.

A network pharmacology approach to explore and validate the potential targets of ginsenoside on osteoporosis

Background: Osteoporosis (OP) is determined as a chronic systemic bone disorder to increase the susceptibility to fracture. Ginsenosides have been found the anti-osteoporotic activity of in vivo and in vitro. However, its mechanism remains unknown.Methods: The potential mechanism of ginsenosides in anti-osteoporotic activity was identified by using network phamacology analysis. The active compounds of ginsenosides and their targets associated to OP were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Drug Bank, Pharmmapper, and Cytoscape. The Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis target genes were performed in String, Phenopedia, DisGeNET database, and Metascape software. The protein to protein interaction were created by String database and Cytoscape software. The molecular docking was used to investigate the interactions between active coumpounds and potential targets by utilizing SwissDock tool, UCSF Chimera, and Pymol software. Results: A total of eight important active ingredients and 17 potential targets related to OP treatment were subjected to analyze. GO analysis showed the anti-osteoporosis targets of ginsenoside mainly play a role in the response to steroid hormone. KEGG enrichment analysis indicated that ginsenoside treats OP by osteoblast differentiation signal pathway. Lastly, the molecular docking outcomes indicated that ginsenoside rh2 had a good binding ability with four target proteins IL1B, TNF, IFNG, and NFKBIA. Conclusion: IL1B, TNF, IFNG, and NFKBIA are the most important targets and osteoblast differentiation is the most valuable signaling pathways in ginsenoside for the treatment of OP, which might be beneficial to elucidate the mechanism concerned to the action of ginsenoside and might supply a better understanding of its anti-OP effects.

Investigation of the Complexes Formed between PARP1 Inhibitors and PARP1 G-Quadruplex at the Gene Promoter Region

DNA repair inhibitors are one of the latest additions to cancer chemotherapy. In general, chemotherapy produces DNA damage but tumoral cells may become resistant if enzymes involved in DNA repair are overexpressed and are able to reverse DNA damage. One of the most successful drugs based on modulating DNA repair are the poly(ADP-ribose) polymerase 1 (PARP1) inhibitors. Several PARP1 inhibitors have been recently developed and approved for clinical treatments. We envisaged that PARP inhibition could be potentiated by simultaneously modulating the expression of PARP 1 and the enzyme activity, by a two-pronged strategy. A noncanonical G-quadruplex-forming sequence within the PARP1 promoter has been recently identified. In this study, we explored the potential binding of clinically approved PARP1 inhibitors to the G-quadruplex structure found at the gene promoter region. The results obtained by NMR, CD, and fluorescence titration confirmed by molecular modeling demonstrated that two out the four PARP1 inhibitors studied are capable of forming defined complexes with the PARP1 G-quadruplex. These results open the possibility of exploring the development of better G-quadruplex binders that, in turn, may also inhibit the enzyme.

Graph Theoretical Methods and Workflows for Searching and Annotation of RNA Tertiary Base Motifs and Substructures

The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs and substructures. Such base arrangements and motifs have diverse roles that range from contributions to structural stability to more direct involvement in the molecule's functions, such as the sites for ligand binding and catalytic activity. We review the utility of computational approaches in annotating RNA tertiary base motifs in a dataset of PDB structures, particularly the use of graph theoretical algorithms that can search for such base motifs and annotate them or find and annotate clusters of hydrogen-bond-connected bases. We also demonstrate how such graph theoretical algorithms can be integrated into a workflow that allows for functional analysis and comparisons of base arrangements and sub-structures, such as those involved in ligand binding. The capacity to carry out such automatic curations has led to the discovery of novel motifs and can give new context to known motifs as well as enable the rapid compilation of RNA 3D motifs into a database.

PyVibMS: a PyMOL plugin for visualizing vibrations in molecules and solids

Visualizing vibrational motions calculated with different ab initio packages requires dedicated post-processing tools. Here, we present a PyMOL plugin called PyVibMS for visualizing the vibrational motions for both molecular and solid systems calculated by mainstream quantum chemical computer programs including Gaussian, Q-Chem, VASP, and CRYSTAL. Benefiting from the continuing development of the PyMOL platform, PyVibMS provides powerful functionalities and user-friendly interface. PyVibMS was written in Python and its open-source nature makes it flexible and sustainable. As an example, the motions of the Konkoli-Cremer local vibrational modes are shown in this work for the first time. PyVibMS is freely available at https://github.com/smutao/PyVibMS . Graphical abstract In this work, a PyMOL plugin named PyVibMS is developed to visualize molecular and lattice vibrations.

How bioinformatics resources work with G4 RNAs

Quadruplexes (G4s) are of interest, which increases with the number of identified G4 structures and knowledge about their biomedical potential. These unique motifs form in many organisms, including humans, where their appearance correlates with various diseases. Scientists store and analyze quadruplexes using recently developed bioinformatic tools—many of them focused on DNA structures. With an expanding collection of G4 RNAs, we check how existing tools deal with them. We review all available bioinformatics resources dedicated to quadruplexes and examine their usefulness in G4 RNA analysis. We distinguish the following subsets of resources: databases, tools to predict putative quadruplex sequences, tools to predict secondary structure with quadruplexes and tools to analyze and visualize quadruplex structures. We share the results obtained from processing specially created RNA datasets with these tools.

Contact: mszachniuk@cs.put.poznan.pl

Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.