scholarly journals Structural dynamics of the SARS-CoV-2 frameshift-stimulatory pseudoknot reveal topologically distinct conformers

2020 ◽  
Author(s):  
Krishna Neupane ◽  
Meng Zhao ◽  
Aaron Lyons ◽  
Sneha Munshi ◽  
Sandaru M Ileperuma ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Optical Tweezers ◽  
Structural Dynamics ◽  
Drug Target ◽  
Conformational Heterogeneity ◽  
Computational Simulations ◽  
Mechanical Tension ◽  
Stem Loop ◽  
Ribosomal Frameshifting ◽  
Rna Pseudoknot

The RNA pseudoknot that stimulates −1 programmed ribosomal frameshifting in SARS coronavirus-2 (SARS-CoV-2) is a possible drug target. To understand how this 3-stemmed pseudoknot responds to the mechanical tension applied by ribosomes during translation, which is thought to play a key role during frameshifting, we probed its structural dynamics under tension using optical tweezers. Unfolding curves revealed that the frameshift signal formed multiple different structures: at least two distinct pseudoknotted conformers with different unfolding forces and energy barriers, as well as alternative stem-loop structures. Refolding curves showed that stem 1 formed first in the pseudoknotted conformers, followed by stem 3 and then stem 2. By extending the handle holding the RNA to occlude the 5′ end of stem 1, the proportion of the different pseudoknot conformers could be altered systematically, consistent with structures observed in cryo-EM images and computational simulations that had distinct topologies: the 5′ end of the RNA threaded through the 3-helix junction to form a ring-knot, or unthreaded as in more standard H-type pseudoknots. These results resolve the folding mechanism of the frameshift signal in SARS-CoV-2 and highlight the dynamic conformational heterogeneity of this RNA, with important implications for structure-based drug-discovery efforts.

scholarly journals Structural dynamics of single SARS-CoV-2 pseudoknot molecules reveal topologically distinct conformers

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Krishna Neupane ◽  
Meng Zhao ◽  
Aaron Lyons ◽  
Sneha Munshi ◽  
Sandaru M. Ileperuma ◽  
...  
Keyword(s):  
Optical Tweezers ◽  
Structural Dynamics ◽  
Drug Target ◽  
The Other ◽  
Conformational Heterogeneity ◽  
Mechanical Tension ◽  
Stem Loop ◽  
Ribosomal Frameshifting ◽  
Multiple Structures ◽  
Rna Pseudoknot

AbstractThe RNA pseudoknot that stimulates programmed ribosomal frameshifting in SARS-CoV-2 is a possible drug target. To understand how it responds to mechanical tension applied by ribosomes, thought to play a key role during frameshifting, we probe its structural dynamics using optical tweezers. We find that it forms multiple structures: two pseudoknotted conformers with different stability and barriers, and alternative stem-loop structures. The pseudoknotted conformers have distinct topologies, one threading the 5′ end through a 3-helix junction to create a knot-like fold, the other with unthreaded 5′ end, consistent with structures observed via cryo-EM and simulations. Refolding of the pseudoknotted conformers starts with stem 1, followed by stem 3 and lastly stem 2; Mg2+ ions are not required, but increase pseudoknot mechanical rigidity and favor formation of the knot-like conformer. These results resolve the SARS-CoV-2 frameshift signal folding mechanism and highlight its conformational heterogeneity, with important implications for structure-based drug-discovery efforts.

scholarly journals Complex dynamics under tension in a high-efficiency frameshift stimulatory structure

2019 ◽  
Vol 116 (39) ◽  
pp. 19500-19505 ◽  
Author(s):  
Matthew T. J. Halma ◽  
Dustin B. Ritchie ◽  
Tonia R. Cappellano ◽  
Krishna Neupane ◽  
Michael T. Woodside
Keyword(s):  
Optical Tweezers ◽  
High Efficiency ◽  
Complex Dynamics ◽  
Conformational Heterogeneity ◽  
Force Extension ◽  
Ribosomal Frameshifting ◽  
Metastable Structures ◽  
Extension Curve ◽  
Length Changes ◽  
Very High

Specific structures in mRNA can stimulate programmed ribosomal frameshifting (PRF). PRF efficiency can vary enormously between different stimulatory structures, but the features that lead to efficient PRF stimulation remain uncertain. To address this question, we studied the structural dynamics of the frameshift signal from West Nile virus (WNV), which stimulates −1 PRF at very high levels and has been proposed to form several different structures, including mutually incompatible pseudoknots and a double hairpin. Using optical tweezers to apply tension to single mRNA molecules, mimicking the tension applied by the ribosome during PRF, we found that the WNV frameshift signal formed an unusually large number of different metastable structures, including all of those previously proposed. From force-extension curve measurements, we mapped 2 mutually exclusive pathways for the folding, each encompassing multiple intermediates. We identified the intermediates in each pathway from length changes and the effects of antisense oligomers blocking formation of specific contacts. Intriguingly, the number of transitions between the different conformers of the WNV frameshift signal was maximal in the range of forces applied by the ribosome during −1 PRF. Furthermore, the occupancy of the pseudoknotted conformations was far too low for static pseudoknots to account for the high levels of −1 PRF. These results support the hypothesis that conformational heterogeneity plays a key role in frameshifting and suggest that transitions between different conformers under tension are linked to efficient PRF stimulation.

scholarly journals Mitoxantrone dihydrochloride, an FDA approved drug, binds with SARS-CoV-2 NSP1 C-terminal

2021 ◽  
Author(s):  
Prateek Kumar ◽  
Taniya Bhardwaj ◽  
Rajanish Giri
Keyword(s):  
Structural Dynamics ◽  
Immune Evasion ◽  
Drug Target ◽  
Mrna Translation ◽  
Small Subunit ◽  
Therapeutic Strategies ◽  
Spectroscopic Technique ◽  
Terminal Region ◽  
Binding Assays ◽  
Computational Simulations

One of the major virulence factors of SARS-CoV-2, NSP1, is a vital drug target due to its role in host immune evasion through multiple pathways. NSP1 protein is associated with inhibiting host mRNA translation by binding to the small subunit of ribosome through its C-terminal region. Previously, we have shown the structural dynamics of NSP1 C-terminal region (NSP1-CTR) in different physiological environments. So, it would be very interesting to investigate the druggable compounds that could bind with NSP1-CTR. Here, in this article, we have performed the different spectroscopic technique-based binding assays of an anticancer drug Mitoxantrone dihydrochloride (MTX) against the NSP1-CTR. We have also performed molecular docking followed by computational simulations with two different forcefields up to one microsecond. Overall, our results have suggested good binding between NSP1-CTR and MTX and may have implications in developing therapeutic strategies targeting NSP1 protein of SARS-CoV-2.

scholarly journals Stem-loop structures can effectively substitute for an RNA pseudoknot in -1 ribosomal frameshifting

2011 ◽  
Vol 39 (20) ◽  
pp. 8952-8959 ◽  
Author(s):  
C.-H. Yu ◽  
M. H. Noteborn ◽  
C. W. A. Pleij ◽  
R. C. L. Olsthoorn
Keyword(s):  
Stem Loop ◽  
Ribosomal Frameshifting ◽  
Rna Pseudoknot

scholarly journals Regulators of Viral Frameshifting: More Than RNA Influences Translation Events

2020 ◽  
Vol 7 (1) ◽  
pp. 219-238
Author(s):  
Wesley D. Penn ◽  
Haley R. Harrington ◽  
Jonathan P. Schlebach ◽  
Suchetana Mukhopadhyay
Keyword(s):  
Messenger Rna ◽  
Protein Production ◽  
Productive Infection ◽  
Cis Elements ◽  
Stem Loop ◽  
Viral Translation ◽  
Ribosomal Frameshifting ◽  
Evolutionarily Conserved ◽  
Rna Pseudoknot ◽  
New Protein

Programmed ribosomal frameshifting (PRF) is a conserved translational recoding mechanism found in all branches of life and viruses. In bacteria, archaea, and eukaryotes PRF is used to downregulate protein production by inducing a premature termination of translation, which triggers messenger RNA (mRNA) decay. In viruses, PRF is used to drive the production of a new protein while downregulating the production of another protein, thus maintaining a stoichiometry optimal for productive infection. Traditionally, PRF motifs have been defined by the characteristics of two cis elements: a slippery heptanucleotide sequence followed by an RNA pseudoknot or stem-loop within the mRNA. Recently, additional cis and new trans elements have been identified that regulate PRF in both host and viral translation. These additional factors suggest PRF is an evolutionarily conserved process whose function and regulation we are just beginning to understand.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

2019 ◽  
Vol 25 (31) ◽  
pp. 3339-3349 ◽  
Author(s):  
Indrani Bera ◽  
Pavan V. Payghan
Keyword(s):  
Molecular Dynamics ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Drug Target ◽  
Structural Information ◽  
Drug Binding ◽  
Structure Based Drug Design ◽  
Drug Designing ◽  
Target Binding ◽  
Dynamics Simulations

Background: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. Objective: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. Method: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. Results: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. Conclusion: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

scholarly journals Stem–loop formation drives RNA folding in mechanical unzipping experiments

2022 ◽  
Vol 119 (3) ◽  
pp. e2025575119
Author(s):  
Paolo Rissone ◽  
Cristiano V. Bizarro ◽  
Felix Ritort
Keyword(s):  
Optical Tweezers ◽  
Rna Structure ◽  
Nearest Neighbor ◽  
Rna Folding ◽  
General Mechanism ◽  
Loop Formation ◽  
Stem Loop ◽  
Wide Range ◽  
Irreversible Effects ◽  
And Function

Accurate knowledge of RNA hybridization is essential for understanding RNA structure and function. Here we mechanically unzip and rezip a 2-kbp RNA hairpin and derive the 10 nearest-neighbor base pair (NNBP) RNA free energies in sodium and magnesium with 0.1 kcal/mol precision using optical tweezers. Notably, force–distance curves (FDCs) exhibit strong irreversible effects with hysteresis and several intermediates, precluding the extraction of the NNBP energies with currently available methods. The combination of a suitable RNA synthesis with a tailored pulling protocol allowed us to obtain the fully reversible FDCs necessary to derive the NNBP energies. We demonstrate the equivalence of sodium and magnesium free-energy salt corrections at the level of individual NNBP. To characterize the irreversibility of the unzipping–rezipping process, we introduce a barrier energy landscape of the stem–loop structures forming along the complementary strands, which compete against the formation of the native hairpin. This landscape correlates with the hysteresis observed along the FDCs. RNA sequence analysis shows that base stacking and base pairing stabilize the stem–loops that kinetically trap the long-lived intermediates observed in the FDC. Stem–loops formation appears as a general mechanism to explain a wide range of behaviors observed in RNA folding.

scholarly journals Open-source chemogenomic data-driven algorithms for predicting drug–target interactions

2018 ◽  
Vol 20 (4) ◽  
pp. 1465-1474 ◽  
Author(s):  
Ming Hao ◽  
Stephen H Bryant ◽  
Yanli Wang
Keyword(s):  
Drug Discovery ◽  
Human Genome ◽  
High Throughput Screening ◽  
Drug Target ◽  
Drug Targets ◽  
Drug Repositioning ◽  
Research Field ◽  
Data Driven ◽  
Source Codes ◽  
Novel Technologies

AbstractWhile novel technologies such as high-throughput screening have advanced together with significant investment by pharmaceutical companies during the past decades, the success rate for drug development has not yet been improved prompting researchers looking for new strategies of drug discovery. Drug repositioning is a potential approach to solve this dilemma. However, experimental identification and validation of potential drug targets encoded by the human genome is both costly and time-consuming. Therefore, effective computational approaches have been proposed to facilitate drug repositioning, which have proved to be successful in drug discovery. Doubtlessly, the availability of open-accessible data from basic chemical biology research and the success of human genome sequencing are crucial to develop effective in silico drug repositioning methods allowing the identification of potential targets for existing drugs. In this work, we review several chemogenomic data-driven computational algorithms with source codes publicly accessible for predicting drug–target interactions (DTIs). We organize these algorithms by model properties and model evolutionary relationships. We re-implemented five representative algorithms in R programming language, and compared these algorithms by means of mean percentile ranking, a new recall-based evaluation metric in the DTI prediction research field. We anticipate that this review will be objective and helpful to researchers who would like to further improve existing algorithms or need to choose appropriate algorithms to infer potential DTIs in the projects. The source codes for DTI predictions are available at: https://github.com/minghao2016/chemogenomicAlg4DTIpred.

COMPUTATIONAL APPROACHES FOR DRUG DISCOVERY FROM MEDICINAL PLANTS IN THE ERA OF DATA DRIVEN RESEARCH

INDIAN DRUGS ◽  
2021 ◽  
Vol 58 (08) ◽  
pp. 7-23
Author(s):  
Pratibha Pansari ◽  
Keyword(s):  
Drug Discovery ◽  
Medicinal Plants ◽  
In Silico ◽  
Drug Target ◽  
Target Gene ◽  
Scientific Work ◽  
Data Driven ◽  
Network Pharmacology ◽  
Gene Pathway ◽  
Topological Network

The significant scientific work on the development of bio-active compound databases, computational technologies, and the integration of Information Technology with Biotechnology has brought a revolution in the domain of drug discovery. These tools facilitate the medicinal plant-based in silico drug discovery, which has become the frontier of pharmacological science. In this review article, we elucidate the methodology of in silico drug discovery for the medicinal plants and present an outlook on recent tools and technologies. Further, we explore the multi-component, multi-target, and multi-pathway mechanism of the bio-active compounds with the help of Network Pharmacology, which enables us to create a topological network between drug, target, gene, pathway, and disease.

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