RNA Structure Research Articles

Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions.

Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNAand Vfold2, excluding web-based tools due to intellectual property concerns. We focus on reproducing the RNA structure existing in RNA-small molecule complexes, particularly on the ability to model ligand binding sites. Using a comprehensive set of RNA structures from the PDB, which includes diverse structural elements, we found that machine learning (ML)-based methods effectively predict global RNA folds but are less accurate with local interactions. Conversely, non-ML-based methods demonstrate higher precision in modeling intramolecular interactions, particularly with secondary structure restraints. Importantly, ligand-binding site accuracy can remain sufficiently high for practical use, even if the overall model quality is not optimal. With the recent release of AlphaFold 3, we included this advanced method in our tests. Benchmark subsets containing new structures, not used in the training of the tested ML methods, show that AlphaFold 3's performance was comparable to other ML-based methods, albeit with some challenges in accurately modeling ligand binding sites. This study underscores the importance of enhancing binding site prediction accuracy and the challenges in modeling RNA-ligand interactions accurately.

Small molecule telomerase inhibitors are also potent inhibitors of telomeric C-strand synthesis.

Telomere replication is essential for continued proliferation of human cells, such as stem cells and cancer cells. Telomerase lengthens the telomeric G-strand, while C-strand replication is accomplished by CST-polymerase α-primase (CST-PP). Replication of both strands is inhibited by formation of G-quadruplex (GQ) structures in the G-rich single-stranded DNA. TMPyP4 and pyridostatin (PDS), which stabilize GQ structures in both DNA and RNA, inhibit telomerase in vitro, and in human cells they cause telomere shortening that has been attributed to telomerase inhibition. Here, we show that TMPyP4 and PDS also inhibit C-strand synthesis by stabilizing DNA secondary structures and thereby preventing CST-PP from binding to telomeric DNA. We also show that these small molecules inhibit CST-PP binding to a DNA sequence containing no consecutive guanine residues, which is unlikely to form GQs. Thus, while these "telomerase inhibitors" indeed inhibit telomerase, they are also robust inhibitors of telomeric C-strand synthesis. Furthermore, given their binding to GQ RNA and their limited specificity for GQ structures, they may disrupt many other protein-nucleic acid interactions in human cells.

Zika virus non-coding RNAs antagonize antiviral responses by PKR-mediated translational arrest.

Zika virus (ZIKV) is an emerging mosquito-borne flavivirus that causes severe outbreaks in human populations. ZIKV infection leads to the accumulation of small non-coding viral RNAs (known as sfRNAs) that are crucial for evasion of antiviral responses and for viral pathogenesis. However, the mechanistic understanding of how sfRNAs function remains incomplete. Here, we use recombinant ZIKVs and ribosome profiling of infected human cells to show that sfRNAs block translation of antiviral genes. Mechanistically, we demonstrate that specific RNA structures present in sfRNAs trigger PKR activation, which instead of limiting viral replication, enhances viral particle production. Although ZIKV infection induces mRNA expression of antiviral genes, translation efficiency of type I interferon and interferon stimulated genes were significantly downregulated by PKR activation. Our results reveal a novel viral adaptation mechanism mediated by sfRNAs, where ZIKV increases its fitness by repurposing the antiviral role of PKR into a proviral factor.

Human lncRNAs harbor conserved modules embedded in different sequence contexts

We analyzed the structure of human long non-coding RNA (lncRNAs) genes to investigate whether the non-coding transcriptome is organized in modular domains, as is the case for protein-coding genes. To this aim, we compared all known human lncRNA exons and identified 340 pairs of exons with high sequence and/or secondary structure similarity but embedded in a dissimilar sequence context. We grouped these pairs in 106 clusters based on their reciprocal similarities. These shared modules are highly conserved between humans and the four great ape species, display evidence of purifying selection and likely arose as a result of recent segmental duplications. Our analysis contributes to the understanding of the mechanisms driving the evolution of the non-coding genome and suggests additional strategies towards deciphering the functional complexity of this class of molecules.

NMR structures of small molecules bound to a model of an RNA CUG repeat expansion.

Trinucleotide repeat expansions fold into long, stable hairpins and cause a variety of incurable RNA gain-of-function diseases such as Huntington's disease, the myotonic dystrophies, and spinocerebellar ataxias. One approach for treating these diseases is to bind small molecules to the structured RNAs. Both Huntington's disease-like 2 (HDL2) and myotonic dystrophy type 1 (DM1) are caused by a r(CUG) repeat expansion, or r(CUG)exp. The RNA folds into a hairpin structure with a periodic array of 1×1 nucleotide UU loops (5'CUG/3'GUC; where the underlined nucleotides indicate the Us in the internal loop) that sequester various RNA-binding proteins (RBP) and hence the source of its gain-of-function. Here, we report NMR-refined structures of single 5'CUG/3'GUC motifs in complex with three different small molecules, a di-guandinobenzoate (1), a derivative of 1 where the guanidino groups have been exchanged for imidazole (2), and a quinoline with improved drug-like properties (3). These structures were determined using nuclear magnetic resonance (NMR) spectroscopy and simulated annealing with restrained molecular dynamics (MD). Compounds 1, 2, and 3 formed stacking and hydrogen bonding interactions with the 5'CUG/3'GUC motif. Compound 3 also formed van der Waals interactions with the internal loop. The global structure of each RNA-small molecule complexes retains an A-form conformation, while the internal loops are still dynamic but to a lesser extent compared to the unbound form. These results aid our understanding of ligand-RNA interactions and enable structure-based design of small molecules with improved binding affinity for and biological activity against r(CUG)exp. As the first ever reported structures of RNA r(CUG) repeats bound to ligands, these structures can enable virtual screening campaigns combined with machine learning assisted de novo design.

Potent anti-coronaviral activity of pateamines and new insights into their mode of action

Pateamines, derived from the sponge Mycale hentscheli, function as inhibitors of the RNA helicase eIF4A and exhibit promising antiviral and anticancer properties. eIF4A plays a pivotal role in unwinding stable RNA structures within the 5′-UTR of selected mRNAs, facilitating the binding of the 43S preinitiation complex during translation initiation. Pateamines function by clamping RNA substrates onto the eIF4A surface, effectively preventing eIF4A from carrying out the unwinding step. Rocaglates, a compound class isolated from plants of the genus Aglaia, target the same binding pocket on eIF4A, and based on structural data, a similar mode of action has been proposed for pateamines and rocaglates. In this study, we conducted a detailed characterization of pateamines' binding mode and assessed their antiviral activity against human pathogenic coronaviruses (human coronavirus 229E (HCoV-229E), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)). Our findings reveal significant differences in the binding behavior of pateamines compared to rocaglates when interacting with an eIF4A-RNA complex. We also observed that pateamines do not depend on the presence of a polypurine tract in the RNA substrate for efficient RNA clamping, as it is the case for rocaglates. Most notably, pateamines demonstrate potent antiviral activity against coronaviruses in the low nanomolar range. Consequently, pateamines broaden our toolbox for combating viruses that rely on the host enzyme eIF4A to conduct their viral protein synthesis, indicating a possible future treatment strategy against new or re-emerging pathogenic viruses.

Knotted artifacts in predicted 3D RNA structures.

Unlike proteins, RNAs deposited in the Protein Data Bank do not contain topological knots. Recently, admittedly, the first trefoil knot and some lasso-type conformations have been found in experimental RNA structures, but these are still exceptional cases. Meanwhile, algorithms predicting 3D RNA models have happened to form knotted structures not so rarely. Interestingly, machine learning-based predictors seem to be more prone to generate knotted RNA folds than traditional methods. A similar situation is observed for the entanglements of structural elements. In this paper, we analyze all models submitted to the CASP15 competition in the 3D RNA structure prediction category. We show what types of topological knots and structure element entanglements appear in the submitted models and highlight what methods are behind the generation of such conformations. We also study the structural aspect of susceptibility to entanglement. We suggest that predictors take care of an evaluation of RNA models to avoid publishing structures with artifacts, such as unusual entanglements, that result from hallucinations of predictive algorithms.

Acyl Phosphates as Chemically Fueled Building Blocks for Self‐Sustaining Protocells

AbstractLipids spontaneously assemble into vesicle‐forming membranes. Such vesicles serve as compartments for even the simplest living systems. Vesicles have been extensively studied for constructing synthetic cells or as models for protocells—the cells hypothesized to have existed before life. These compartments exist almost always close to equilibrium. Life, however, exists out of equilibrium. In this work, we studied vesicle‐based compartments regulated by a non‐equilibrium chemical reaction network that converts activating agents. In this way, the compartments require a constant or periodic supply of activating agents to sustain themselves. Specifically, we use activating agents to condense carboxylates and phosphate esters into acyl phosphate‐based lipids that form vesicles. These vesicles can only be sustained when condensing agents are present; without them, they decay. We demonstrate that the chemical reaction network can operate on prebiotic activating agents, opening the door to prebiotically plausible, self‐sustainable protocells that compete for resources. In future work, such protocells should be endowed with a genotype, e.g., self‐replicating RNA structures, to alter the protocell's behavior. Such protocells could enable Darwinian evolution in a prebiotically plausible chemical system.

Acyl Phosphates as Chemically Fueled Building Blocks for Self-Sustaining Protocells.

Lipids spontaneously assemble into vesicle-forming membranes. Such vesicles serve as compartments for even the simplest living systems. Vesicles have been extensively studied for constructing synthetic cells or as models for protocells-the cells hypothesized to have existed before life. These compartments exist almost always close to equilibrium. Life, however, exists out of equilibrium. In this work, we studied vesicle-based compartments regulated by a non-equilibrium chemical reaction network that converts activating agents. In this way, the compartments require a constant or periodic supply of activating agents to sustain themselves. Specifically, we use activating agents to condense carboxylates and phosphate esters into acyl phosphate-based lipids that form vesicles. These vesicles can only be sustained when condensing agents are present; without them, they decay. We demonstrate that the chemical reaction network can operate on prebiotic activating agents, opening the door to prebiotically plausible, self-sustainable protocells that compete for resources. In future work, such protocells should be endowed with a genotype, e.g., self-replicating RNA structures, to alter the protocell's behavior. Such protocells could enable Darwinian evolution in a prebiotically plausible chemical system.

Understanding the Thermodynamics of Magnesium Binding to RNA Structural Motifs.

Divalent magnesium ions (Mg2+) serve a vital role in defining the structural and catalytic chemistry of a wide array of RNA molecules. The body of structural information on RNA motifs continues to expand and, in turn, the functional importance of Mg2+ is revealed. A combination of prior work on the structural characterization of magnesium binding ligands with inner- and outer-sphere coordination modes, with recorded experimental binding energies for inner- and outer-sphere contacts, demonstrates the relative affinity and thermodynamic hierarchy for these sites. In turn, these can be correlated with cellular concentrations of free available magnesium ions, allowing the prioritization of populating important functional sites and a correlation with physiological function. This paper summarizes some of the key results of that analysis and provides predictive rules for the affinity and role of newly identified Mg binding sites on complex RNA structures. The influence of crystal packing on magnesium binding to RNA motifs, relative to their solution form, is addressed and caveats made.

FRET-guided modeling of nucleic acids.

The functional diversity of RNAs is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule Förster resonance energy transfer (FRET) measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling, we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the reaction coordinates. Using multiple accessible-contact volumes as a post hoc scoring method for fragment assembly in Rosetta, we demonstrate that FRET can be used to filter a de novo RNA structure prediction ensemble by refuting models that are not compatible with in vitro FRET measurement. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch displayed by the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions.

Modeling the structure and DAP5-binding site of the FGF-9 5'-UTR RNA utilized in cap-independent translation.

Cap-independent or eukaryotic initiation factor (eIF) 4E-independent, translation initiation in eukaryotes requires scaffolding protein eIF4G or its homolog, death-associated protein 5 (DAP5). eIF4G associates with the 40S ribosomal subunit, recruiting the ribosome to the RNA transcript. A subset of RNA transcripts, such as fibroblast growth factor 9 (FGF-9), contain 5' untranslated regions (5' UTRs) that directly bind DAP5 or eIF4GI. For viral mRNA, eIF recruitment usually utilizes RNA structure, such as a pseudoknot or stem-loops, and the RNA-helicase eIF4A is required for DAP5- or 4G-mediated translation, suggesting these 5' UTRs are structured. However, for cellular IRES-like translation, no consensus RNA structures or sequences have yet been identified for eIF binding. However, the DAP5-binding site within the FGF-9 5' UTR is unknown. Moreover, DAP5 binds to other, dissimilar 5' UTRs, some of which require an unpaired, accessible 5' end to stimulate cap-independent translation. Using SHAPE-seq, we modeled the 186 nt FGF-9 5'-UTR RNA's complex secondary structure in vitro. Further, DAP5 footprinting, toeprinting, and UV cross-linking experiments identify DAP5-RNA interactions. Modeling of FGF-9 5'-UTR tertiary structure aligns DAP5-interacting nucleotides on one face of the predicted structure. We propose that RNA structure involving tertiary folding, rather than a conserved sequence or secondary structure, acts as a DAP5-binding site. DAP5 appears to contact nucleotides near the start codon. Our findings offer a new perspective in the hunt for cap-independent translational enhancers. Structural, rather than sequence-specific, eIF-binding sites may act as attractive chemotherapeutic targets or as dosage tools for mRNA-based therapies.

Genomic Evolution Strategy in SARS-CoV-2 Lineage B: Coevolution of Cis Elements.

In the SARS-CoV-2 lineage, RNA elements essential for its viral life cycle, including genome replication and gene expression, have been identified. Still, the precise structures and functions of these RNA regions in coronaviruses remain poorly understood. This lack of knowledge points out the need for further research to better understand these crucial aspects of viral biology and, in time, prepare for future outbreaks. In this research, the in silico analysis of the cis RNA structures that act in the alpha-, beta-, gamma-, and deltacoronavirus genera has provided a detailed view of the presence and adaptation of the structures of these elements in coronaviruses. The results emphasize the importance of these cis elements in viral biology and their variability between different viral variants. Some coronavirus variants in some groups, depending on the cis element (stem-loop1 and -2; pseudoknot stem-loop1 and -2, and s2m), exhibited functional adaptation. Additionally, the conformation flexibility of the s2m element in the SARS variants was determined, suggesting a coevolution of this element in this viral group. The variability in secondary structures suggests genomic adaptations that may be related to replication processes, genetic regulation, as well as the specific pathogenicity of each variant. The results suggest that RNA structures in coronaviruses can adapt and evolve toward different viral variants, which has important implications for viral adaptation, pathogenicity, and future therapeutic strategies.

Evaluating Performance of Different RNA Secondary Structure Prediction Programs Using Self-cleaving Ribozymes.

Accurate identification of the correct, biologically relevant RNA structures is critical to understanding various aspects of RNA biology since proper folding represents the key to the functionality of all types of RNA molecules and plays pivotal roles in many essential biological processes. Thus, a plethora of approaches have been developed to predict, identify, or solve RNA structures based on various computational, molecular, genetic, chemical, or physicochemical strategies. Purely computational approaches hold distinct advantages over all other strategies in terms of the ease of implementation, time, speed, cost, and throughput, but they strongly underperform in terms of accuracy that significantly limits their broader application. Nonetheless, the advantages of these methods led to a steady development of multiple in silico RNA secondary structure prediction approaches including recent deep learning-based programs. Here, we compared the accuracy of predictions of biologically relevant secondary structures of dozens of self-cleaving ribozyme sequences using seven in silico RNA folding prediction tools with tasks of varying complexity. We found that while many programs performed well in relatively simple tasks, their performance varied significantly in more complex RNA folding problems. However, in general, a modern deep learning method outperformed the other programs in the complex tasks in predicting the RNA secondary structures, at least based on the specific class of sequences tested, suggesting that it may represent the future of RNA structure prediction algorithms.

The binding of diruthenium (II,III) and dirhodium (II,II) paddlewheel complexes at DNA/RNA nucleobases: Computational evidences of an appreciable selectivity toward the AU base pairs

Multiple medicinal strategies involve modifications of the structure of DNA or RNA, which disrupt their correct functioning. Metal complexes with medicinal effects, also known as metallodrugs, are among the agents intended specifically for the attack onto nucleosides. The diruthenium (II,III) and dirhodium (II,II) paddlewheel complexes constitute promising dual acting drugs due to their ability to release the therapeutically active bridging ligands upon their substitution by endogenous ligands. In this paper, we study the structure and the stability of the complexes formed by the diruthenium (II,III) and dirhodium (II,II) paddlewheel complexes coordinated in axial positions with the DNA/RNA nucleobases or base pairs, assuming the attainable metalation at all the accessible pyridyl nitrogens. Dirhodium complexes coordinate at the pyridyl nitrogens more strongly than the diruthenium complexes. On the other hand, we found that the diruthenium scaffold binds more selectively to nucleobase targets. Furthermore, we reveal a tighter coordination of diruthenium complex at the adenine-uracil base pair, compared to adenine-thymine, hence constituting a scarce instance of RNA-selectivity. We envision that the here reported computational outcomes may pace future experiments addressing the binding of diruthenium and dirhodium paddlewheel complexes at either single nucleobases or DNA/RNA fragments.

ANT2 functions as a translocon for mitochondrial cross-membrane translocation of RNAs.

Bidirectional transcription of mammalian mitochondrial DNA generates overlapping transcripts that are capable of forming double-stranded RNA (dsRNA) structures. Release of mitochondrial dsRNA into the cytosol activates the dsRNA-sensing immune signaling, which is a defense mechanism against microbial and viral attack and possibly cancer, but could cause autoimmune diseases when unchecked. A better understanding of the process is vital in therapeutic application of this defense mechanism and treatment of cognate human diseases. In addition to exporting dsRNAs, mitochondria also export and import a variety of non-coding RNAs. However, little is known about how these RNAs are transported across mitochondrial membranes. Here we provide direct evidence showing that adenine nucleotide translocase-2 (ANT2) functions as a mammalian RNA translocon in the mitochondrial inner membrane, independent of its ADP/ATP translocase activity. We also show that mitochondrial dsRNA efflux through ANT2 triggers innate immunity. Inhibiting this process alleviates inflammation in vivo, providing a potential therapeutic approach for treating autoimmune diseases.

Xinyang flavivirus, from Haemaphysalis flava ticks in Henan Province, China, defines a basal, likely tick-only Orthoflavivirus clade.

Tick-borne orthoflaviviruses (TBFs) are classified into three conventional groups based on genetics and ecology: mammalian, seabird and probable-TBF group. Recently, a fourth basal group has been identified in Rhipicephalus ticks from Africa: Mpulungu flavivirus (MPFV) in Zambia and Ngoye virus (NGOV) in Senegal. Despite attempts, isolating these viruses in vertebrate and invertebrate cell lines or intracerebral injection of newborn mice with virus-containing homogenates has remained unsuccessful. In this study, we report the discovery of Xinyang flavivirus (XiFV) in Haemaphysalis flava ticks from Xìnyáng, Henan Province, China. Phylogenetic analysis shows that XiFV was most closely related to MPFV and NGOV, marking the first identification of this tick orthoflavivirus group in Asia. We developed a reverse transcriptase quantitative PCR assay to screen wild-collected ticks and egg clutches, with absolute infection rates of 20.75 % in adult females and 15.19 % in egg clutches, suggesting that XiFV could be potentially spread through transovarial transmission. To examine potential host range, dinucleotide composition analyses revealed that XiFV, MPFV and NGOV share a closer composition to classical insect-specific orthoflaviviruses than to vertebrate-infecting TBFs, suggesting that XiFV could be a tick-only orthoflavivirus. Additionally, both XiFV and MPFV lack a furin cleavage site in the prM protein, unlike other TBFs, suggesting these viruses might exist towards a biased immature particle state. To examine this, chimeric Binjari virus with XIFV-prME (bXiFV) was generated, purified and analysed by SDS-PAGE and negative-stain transmission electron microscopy, suggesting prototypical orthoflavivirus size (~50 nm) and bias towards uncleaved prM. In silico structural analyses of the 3'-untranslated regions show that XiFV forms up to five pseudo-knot-containing stem-loops and a prototypical orthoflavivirus dumbbell element, suggesting the potential for multiple exoribonuclease-resistant RNA structures.

ANNaMo: Coarse-grained modeling for folding and assembly of RNA and DNA systems.

The folding of RNA and DNA strands plays crucial roles in biological systems and bionanotechnology. However, studying these processes with high-resolution numerical models is beyond current computational capabilities due to the timescales and system sizes involved. In this article, we present a new coarse-grained model for investigating the folding dynamics of nucleic acids. Our model represents three nucleotides with a patchy particle and is parameterized using well-established nearest-neighbor models. Thanks to the reduction of degrees of freedom and to a bond-swapping mechanism, our model allows for simulations at timescales and length scales that are currently inaccessible to more detailed models. To validate the performance of our model, we conducted extensive simulations of various systems: We examined the thermodynamics of DNA hairpins, capturing their stability and structural transitions, the folding of an MMTV pseudoknot, which is a complex RNA structure involved in viral replication, and also explored the folding of an RNA tile containing a k-type pseudoknot. Finally, we evaluated the performance of the new model in reproducing the melting temperatures of oligomers and the dependence on the toehold length of the displacement rate in toehold-mediated displacement processes, a key reaction used in molecular computing. All in all, the successful reproduction of experimental data and favorable comparisons with existing coarse-grained models validate the effectiveness of the new model.

RNA adapts its flexibility to efficiently fold and resist unfolding.

Recent studies have demonstrated that the mechanisms through which biopolymers like RNA interconvert between multiple folded structures are critical for their cellular functions. A major obstacle to elucidating these mechanisms is the lack of experimental approaches that can resolve these interconversions between functionally relevant biomolecular structures. Here, using a nano-electronic device with microsecond time resolution, we dissect the complete set of structural rearrangements executed by an ultra-stable RNA, the UUCG stem-loop, at the single-molecule level. We show that the stem-loop samples at least four conformations along two folding pathways leading to two distinct folded structures, only one of which has been previously observed. By modulating its flexibility, the stem-loop can adaptively select between these pathways, enabling it to both fold rapidly and resist unfolding. This paradigm of stabilization through compensatory changes in flexibility broadens our understanding of stable RNA structures and is expected to serve as a general strategy employed by all biopolymers.

Knotify_V2.0: Deciphering RNA Secondary Structures with H-Type Pseudoknots and Hairpin Loops.

Accurately predicting the pairing order of bases in RNA molecules is essential for anticipating RNA secondary structures. Consequently, this task holds significant importance in unveiling previously unknown biological processes. The urgent need to comprehend RNA structures has been accentuated by the unprecedented impact of the widespread COVID-19 pandemic. This paper presents a framework, Knotify_V2.0, which makes use of syntactic pattern recognition techniques in order to predict RNA structures, with a specific emphasis on tackling the demanding task of predicting H-type pseudoknots that encompass bulges and hairpins. By leveraging the expressive capabilities of a Context-Free Grammar (CFG), the suggested framework integrates the inherent benefits of CFG and makes use of minimum free energy and maximum base pairing criteria. This integration enables the effective management of this inherently ambiguous task. The main contribution of Knotify_V2.0 compared to earlier versions lies in its capacity to identify additional motifs like bulges and hairpins within the internal loops of the pseudoknot. Notably, the proposed methodology, Knotify_V2.0, demonstrates superior accuracy in predicting core stems compared to state-of-the-art frameworks. Knotify_V2.0 exhibited exceptional performance by accurately identifying both core base pairing that form the ground truth pseudoknot in 70% of the examined sequences. Furthermore, Knotify_V2.0 narrowed the performance gap with Knotty, which had demonstrated better performance than Knotify and even surpassed it in Recall and F1-score metrics. Knotify_V2.0 achieved a higher count of true positives (tp) and a significantly lower count of false negatives (fn) compared to Knotify, highlighting improvements in Prediction and Recall metrics, respectively. Consequently, Knotify_V2.0 achieved a higher F1-score than any other platform. The source code and comprehensive implementation details of Knotify_V2.0 are publicly available on GitHub.