ABSTRACT
Understanding and targeting functional RNA structures towards treatment of coronavirus infection can help us to prepare for novel variants of SARS-CoV-2 (the virus causing COVID-19), and any other coronaviruses that could emerge via human-to-human transmission or potential zoonotic (inter-species) events. Leveraging the fact that all coronaviruses use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to replicate, we apply algorithms to predict the most energetically favourable secondary structures (each nucleotide involved in at most one pairing) that may be involved in regulating the -1 PRF event in coronaviruses, especially SARS-CoV-2. We compute previously unknown most stable structure predictions for the frameshift site of coronaviruses via hierarchical folding, a biologically motivated framework where initial non-crossing structure folds first, followed by subsequent, possibly crossing (pseudoknotted), structures. Using mutual information from 181 coronavirus sequences, in conjunction with the algorithm KnotAli, we compute secondary structure predictions for the frameshift site of different coronaviruses. We then utilize the Shapify algorithm to obtain most stable SARS-CoV-2 secondary structure predictions guided by frameshift sequence-specific and genome-wide experimental data. We build on our previous secondary structure investigation of the singular SARS-CoV-2 68 nt frameshift element sequence, by using Shapify to obtain predictions for 132 extended sequences and including covariation information. Previous investigations have not applied hierarchical folding to extended length SARS-CoV-2 frameshift sequences. By doing so, we simulate the effects of ribosome interaction with the frameshift site, providing insight to biological function. We contribute in-depth discussion to contextualize secondary structure dual-graph motifs for SARS-CoV-2, highlighting the energetic stability of the previously identified 3 8 motif alongside the known dominant 3 3 and 3 6 (native-type) -1 PRF structures. Integrating experimental data within minimum free energy (MFE) hierarchical folding algorithms provides novel structure predictions to distill the relationship between RNA structure and function. In particular, fully categorizing most stable secondary structure predictions via hierarchical folding supports our identification of motif transitions and critical site targets for future therapeutic research. Author summaryFinding evolutionary connections between coronaviruses frameshift element RNA structures is a worthwhile goal in contributing to treatment development for afflicted human and animal populations. Predicting the most energetically favourable RNA secondary structures, and how they may form via the hierarchical folding hypothesis, is an efficient use of computational resources to shed light on RNA structure-function. We used the KnotAli algorithm to obtain mutual information from 181 coronaviruses frameshift RNA sequences. Guided by this evolutionary information, we computed secondary structure predictions to allow comparison of marked similarities and subtle differences between SARS-CoV-2 and other coronaviruses frameshift element RNA structures. In addition, we applied the Shapify algorithm to predict secondary structures for extended SARS-CoV-2 frameshift element sequences informed by SHAPE reactivity data. Here we critically expand the known landscape of most stable -1 PRF secondary structure conformations, isolating the location of key secondary structure motif transitions that can improve site targeting of viral therapeutics. Our application of hierarchical folding algorithms contributes novel predictions of functional RNA structures, enhancing discussion of how secondary structures unfold or refold to regulate frameshifting in coronaviruses.
Subject(s)
Coronavirus Infections , COVID-19ABSTRACT
Background: Multiple viruses including HIV, MERS-CoV (coronavirus responsible for Middle East Respiratory Syndrome, MERS), SARS-CoV (coronavirus responsible for SARS) and SARS-CoV-2 (coronavirus responsible for COVID-19) use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to successfully replicate. SARS-CoV-2 possesses a unique RNA pseudoknotted structure that stimulates -1 PRF. Recent experiments identified small molecules as antiviral agents that can bind to the pseudoknot and disrupt its stimulation of -1 PRF. Targeting -1 PRF in SARS-CoV-2 to impair viral replication can improve patients' prognoses.Crucial to developing these successful therapies is modeling the structure of the SARS-CoV-2 -1 PRF pseudoknot.Our goal is to expand knowledge of possible pseudoknot conformations. Results: : Following a structural alignment approach, we identify similarities in -1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. We introduce Shapify , a novel algorithm that given an RNA sequence incorporates structural reactivity (SHAPE) data and partial structure information to output an RNA secondary structure prediction within a biologically sound hierarchical folding approach. Shapify helps us to better understand non-native SARS-CoV-2 -1 PRF pseudoknot conformations that are relevant to structure function and may correlate with -1 PRF efficiency. We provide in-depth analysis by investigating the structural landscape for the SARS-CoV-2 -1 PRF pseudoknot, including reference and mutated sequences. To better understand the impact of mutations, we provide insight on SARS-CoV-2 -1 PRF pseudoknot sequence mutations and their effect on the resulting structure. Conclusion: We identify the consensus structure for SARS-CoV, SARS-CoV-2, and MERS-CoV -1 PRF pseudoknots; this similarity in functional RNA structures aids treatment preparation for existing and emergent viruses. Shapify predictions are guided both by SHAPE data and partial structure information. Applied to the SARS-CoV-2 -1 PRF pseudoknot, Shapify unveiled previously unknown pathways from initial stems to pseudoknotted secondary structures. Where SHAPE data is unavailable we provide predictions for noteworthy SARS-CoV-2 -1 PRF mutated pseudoknot sequences. By contextualizing our work with available experimental data, our structure predictions motivate future RNA structure-function research and can aid 3-D modeling of pseudoknots.
Subject(s)
COVID-19 , HIV Infections , TheileriasisABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the COVID-19 pandemic; a pandemic of a scale that has not been seen in the modern era. Despite over 29 million reported cases and over 900,000 deaths worldwide as of September 2020, herd immunity and widespread vaccination efforts by many experts are expected to be insufficient in addressing this crisis for the foreseeable future. Thus, there is an urgent need for treatments that can lessen the effects of SARS-CoV-2 in patients who become seriously affected. Many viruses including HIV, the common cold, SARS-CoV and SARS-CoV-2 use a unique mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to successfully replicate and infect cells in the human host. SARS-CoV (the coronavirus responsible for SARS) and SARS-CoV-2 possess a unique RNA structure, a three-stemmed pseudoknot, that stimulates -1 PRF. Recent experiments identified that small molecules can be introduced as antiviral agents to bind with the pseudoknot and disrupt its stimulation of -1 PRF. If successfully developed, small molecule therapy that targets -1 PRF in SARS-CoV-2 is an excellent strategy to improve patients' prognoses. Crucial to developing these successful therapies is modeling the structure of the SARS-CoV-2 -1 PRF pseudoknot. Following a structural alignment approach, we identify similarities in the -1 PRF pseudoknots of the novel coronavirus SARS-CoV-2, the original SARS-CoV, as well as a third coronavirus: MERS-CoV, the coronavirus responsible for Middle East Respiratory Syndrome (MERS). In addition, we provide a better understanding of the SARS-CoV-2 -1 PRF pseudoknot by comprehensively investigating the structural landscape using a hierarchical folding approach. Since understanding the impact of mutations is vital to long-term success of treatments that are based on predicted RNA functional structures, we provide insight on SARS-CoV-2 -1 PRF pseudoknot sequence mutations and their effect on the resulting structure and its function.