Binding interface and impact on protease cleavage for an RNA aptamer to HIV-1 reverse transcriptase

Prediction of aptamer affinity using an artificial intelligence approach

Aptamers are oligonucleotide sequences that can connect to particular target molecules, similar to monoclonal antibodies. They can be chosen by systematic evolution of ligands by exponential enrichment (SELEX), and are modifiable and can be synthesized. Even if the SELEX approach has been improved a lot, it is frequently challenging and time-consuming to identify aptamers experimentally. In particular, structure-based methods are the most used in computer-aided design and development of aptamers. For this purpose, numerous web-based platforms have been suggested for the purpose of forecasting the secondary structure and 3D configurations of RNAs and DNAs. Also, molecular docking and molecular dynamics (MD), which are commonly utilized in protein compound selection by structural information, are suitable for aptamer selection. On the other hand, from a large number of sequences, artificial intelligence (AI) may be able to quickly discover the possible aptamer candidates. Conversely, sophisticated machine and deep-learning (DL) models have demonstrated efficacy in forecasting the binding properties between ligands and targets during drug discovery; as such, they may provide a reliable and precise method for forecasting the binding of aptamers to targets. This research looks at advancements in AI pipelines and strategies for aptamer binding ability prediction, such as machine and deep learning, as well as structure-based approaches, molecular dynamics and molecular docking simulation methods.

Eliminating the HIV tissue reservoir: current strategies and challenges

BACKGROUND

Acquired immunodeficiency syndrome (AIDS) is still one of the most widespread and harmful infectious diseases in the world. The presence of reservoirs housing the human immunodeficiency virus (HIV) represents a significant impediment to the development of clinically applicable treatments on a large scale. The viral load in the blood can be effectively reduced to undetectable levels through antiretroviral therapy (ART), and a higher concentration of HIV is sequestered in various tissues throughout the body, forming the tissue reservoir - the source of viremia after interruption treatment.

METHODS

We take the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) as a guideline for this review. In June 2023, we used the Pubmed, Embase, and Scopus databases to search the relevant literature published in the last decade.

RESULTS

Here we review the current strategies and treatments for eliminating the HIV tissue reservoirs: early and intensive therapy, gene therapy (including ribozyme, RNA interference, RNA aptamer, zinc finger enzyme, transcriptional activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats/associated nuclease 9 (CRISPR/Cas9)), 'Shock and Kill', 'Block and lock', immunotherapy (including therapeutic vaccines, broadly neutralising antibodies (bNAbs), chimeric antigen receptor T-cell immunotherapy (CAR-T)), and haematopoietic stem cell transplantation (HSCT).

CONCLUSION

The existence of an HIV reservoir is the main obstacle to the complete cure of AIDS. Choosing the appropriate strategy to deplete the HIV reservoir and achieve a functional cure for AIDS is the focus and difficulty of current research. So far, there has been a lot of research and progress in reducing the HIV reservoir, but in general, the current research is still very preliminary. Much research is still needed to properly assess the reliability, effectiveness, and necessity of these strategies.

Virtual screening and site-directed mutagenesis-derived aptamers for precise Salmonella typhimurium prediction: emphasizing OmpD targeting and G-quadruplex stability

The efficient detection of the foodborne pathogen Salmonella typhimurium has historically been hampered by the constraints of traditional methods, characterized by protracted culture periods and intricate DNA extraction processes for PCR. To address this, our research innovatively focuses on the crucial and relatively uncharted virulence factor, the Outer Membrane Protein D (OmpD) in Salmonella typhimurium. By harmoniously integrating the power of virtual screening and site-directed mutagenesis, we unveiled aptamers exhibiting marked specificity for OmpD. Among these, aptamer 7ZQS stands out with its heightened binding affinity. Capitalizing on this foundation, we further engineered a repertoire of mutant aptamers, wherein APT6 distinguished itself, reflecting unmatched stability and specificity. Our rigorous validation, underpinned by cutting-edge bioinformatics tools, amplifies the prowess of APT6 in discerning and binding OmpD across an array of Salmonella typhimurium strains. This study illuminates a transformative approach to the prompt and accurate detection of Salmonella typhimurium, potentially redefining boundaries in applied analytical chemistry and bolstering diagnostic precision across diverse research and clinical domains.Communicated by Ramaswamy H. Sarma.

Design and Prediction of Aptamers Assisted by In Silico Methods

An aptamer is a single-stranded DNA or RNA that binds to a specific target with high binding affinity. Aptamers are developed through the process of systematic evolution of ligands by exponential enrichment (SELEX), which is repeated to increase the binding power and specificity. However, the SELEX process is time-consuming, and the characterization of aptamer candidates selected through it requires additional effort. Here, we describe in silico methods in order to suggest the most efficient way to develop aptamers and minimize the laborious effort required to screen and optimise aptamers. We investigated several methods for the estimation of aptamer-target molecule binding through conformational structure prediction, molecular docking, and molecular dynamic simulation. In addition, examples of machine learning and deep learning technologies used to predict the binding of targets and ligands in the development of new drugs are introduced. This review will be helpful in the development and application of in silico aptamer screening and characterization.

Endogenous G-quadruplex-forming RNAs inhibit the activity of SARS-CoV-2 RNA polymerase

Replication of RNA viruses is catalysed by virus-specific polymerases, which can be targets of therapeutic strategies. In this study, we used a selection strategy to identify endogenous RNAs from a transcriptome library derived from lung cells that interact with the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. Some of the selected RNAs weakened the activity of RdRp by forming G-quadruplexes. These results suggest that certain endogenous RNAs, which potentially form G-quadruplexes, can reduce the replication of viral RNAs.

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.

Ribonucleic Acid Folding Prediction Based on Iterative Multiscale Simulation

RNA folding prediction is a challenge. Currently, many RNA folding models are coarse-grained (CG) with the potential derived from the known RNA structures. However, this potential is not suitable for modified and entirely new RNA. It is also not suitable for the folding simulation of RNA in the real cellular environment, including many kinds of molecular interactions. In contrast, our proposed model has the potential to address these issues, which is a multiscale simulation scheme based on all-atom (AA) force fields. We fit the CG force field using the trajectories generated by the AA force field and then iteratively perform molecular dynamics (MD) simulations of the two scales. The all-atom molecular dynamics (AAMD) simulation is mainly responsible for the correction of RNA structure, and the CGMD simulation is mainly responsible for efficient conformational sampling. On the basis of this scheme, we can successfully fold three RNAs belonging to a hairpin, a pseudoknot, and a four-way junction.

Aptamers-Diagnostic and Therapeutic Solution in SARS-CoV-2

The SARS-CoV-2 virus is currently the most serious challenge to global public health. Its emergence has severely disrupted the functioning of health services and the economic and social situation worldwide. Therefore, new diagnostic and therapeutic tools are urgently needed to allow for the early detection of the SARS-CoV-2 virus and appropriate treatment, which is crucial for the effective control of the COVID-19 disease. The ideal solution seems to be the use of aptamers—short fragments of nucleic acids, DNA or RNA—that can bind selected proteins with high specificity and affinity. They can be used in methods that base the reading of the test result on fluorescence phenomena, chemiluminescence, and electrochemical changes. Exploiting the properties of aptamers will enable the introduction of rapid, sensitive, specific, and low-cost tests for the routine diagnosis of SARS-CoV-2. Aptamers are excellent candidates for the development of point-of-care diagnostic devices and are potential therapeutic tools for the treatment of COVID-19. They can effectively block coronavirus activity in multiple fields by binding viral proteins and acting as carriers of therapeutic substances. In this review, we present recent developments in the design of various types of aptasensors to detect and treat the SARS-CoV-2 infection.

A Defective Viral Particle Approach to COVID-19

The novel coronavirus SARS-CoV-2 has caused a pandemic resulting in millions of deaths worldwide. While multiple vaccines have been developed, insufficient vaccination combined with adaptive mutations create uncertainty for the future. Here, we discuss novel strategies to control COVID-19 relying on Defective Interfering Particles (DIPs) and related particles that arise naturally during an infection. Our intention is to encourage and to provide the basis for the implementation of such strategies by multi-disciplinary teams. We therefore provide an overview of SARS-CoV-2 for a multi-disciplinary readership that is specifically tailored to these strategies, we identify potential targets based on the current knowledge of the properties and functions of coronaviruses, and we propose specific strategies to engineer DIPs and other interfering or therapeutic nanoparticles.

Aptamer-Based Antibacterial and Antiviral Therapy against Infectious Diseases

Nucleic acid aptamers are single-stranded DNA or RNA molecules selected in vitro that can bind to a broad range of targets with high affinity and specificity. As promising alternatives to conventional anti-infective agents, aptamers have gradually revealed their potential in the combat against infectious diseases. This article provides an overview on the state-of-art of aptamer-based antibacterial and antiviral therapeutic strategies. Diverse aptamers targeting pathogen-related components or whole pathogenic cells are summarized according to the species of microorganisms. These aptamers exhibited remarkable in vitro and/or in vivo inhibitory effect for pathogenic invasion, enzymatic activities, or viral replication, even for some highly drug-resistant strains and biofilms. Aptamer-mediated drug delivery and controlled drug release strategies are also included herein. Critical technical barriers of therapeutic aptamers are briefly discussed, followed by some future perspectives for their implementation into clinical utility.

Modeling Noncanonical RNA Base Pairs by a Coarse-Grained IsRNA2 Model

Noncanonical base pairs contribute crucially to the three-dimensional architecture of large RNA molecules; however, how to accurately model them remains an open challenge in RNA 3D structure prediction. Here, we report a promising coarse-grained (CG) IsRNA2 model to predict noncanonical base pairs in large RNAs through molecular dynamics simulations. By introducing a five-bead per nucleotide CG representation to reserve the three interacting edges of nucleobases, IsRNA2 accurately models various base-pairing interactions, including both canonical and noncanonical base pairs. A benchmark test indicated that IsRNA2 achieves a comparable performance to the atomic model in de novo modeling of noncanonical RNA structures. In addition, IsRNA2 was able to refine the 3D structure predictions for large RNAs in RNA-puzzle challenges. Finally, the graphics processing unit acceleration was introduced to speed up the sampling efficiency in IsRNA2 for very large RNA molecules. Therefore, the CG IsRNA2 model reported here offers a reliable approach to predict the structures and dynamics of large RNAs.

Aptamer based surface plasma resonance assay for direct detection of neuron specific enolase and progastrin-releasing peptide (31-98)

Neuron specific enolase (NSE) and progastrin-releasing peptide (31-98) (ProGRP31-98) are considered as reliable biomarkers of small cell lung cancer (SCLC). Sensitive determinations of NSE and ProGRP31-98 show great significance in disease surveillance, clinical diagnosis, efficacy evaluation and prognostic judgment. However, the conventional detection methods have the disadvantages of poor stability, tedious operation, and being very time consuming. Herein, we developed an aptamer-based surface plasmon resonance (SPR) assay in a direct format for NSE and ProGRP31-98 detection. The aptamer was loaded on a sensor chip and used as an affinity ligand. With sample injection, SPR signals increased due to the association of the target to the aptamer coated chip. Further dissociation and regeneration allowed this aptamer sensor chip to be used for the next sample analysis. We achieved sensitive detection of NSE and ProGRP31-98 by measuring the affinity binding-induced SPR responses. The detection limits for NSE and ProGRP31-98 were 3.9 nM and 15.6 nM, respectively. The aptamer sensor chip is stable and reusable, and has potential for diluted human serum analysis. This assay presents strengths in simplicity, rapidity, low material consumption, real time analysis and ease of implementing high throughput and automatic detection. It is promising for application in clinical disease-related biomarkers analysis.

Systematic Evolution of Ligands by Exponential Enrichment Technologies and Aptamer-Based Applications: Recent Progress and Challenges in Precision Medicine of Infectious Diseases

Infectious diseases are considered as a pressing challenge to global public health. Accurate and rapid diagnostics tools for early recognition of the pathogen, as well as individualized precision therapy are essential for controlling the spread of infectious diseases. Aptamers, which were screened by systematic evolution of ligands by exponential enrichment (SELEX), can bind to targets with high affinity and specificity so that have exciting potential in both diagnosis and treatment of infectious diseases. In this review, we provide a comprehensive overview of the latest development of SELEX technology and focus on the applications of aptamer-based technologies in infectious diseases, such as targeted drug-delivery, treatments and biosensors for diagnosing. The challenges and the future development in this field of clinical application will also be discussed.

Oligonucleotide aptamers for pathogen detection and infectious disease control

During an epidemic or pandemic, the primary task is to rapidly develop precise diagnostic approaches and effective therapeutics. Oligonucleotide aptamer-based pathogen detection assays and control therapeutics are promising, as aptamers that specifically recognize and block pathogens can be quickly developed and produced through simple chemical synthesis. This work reviews common aptamer-based diagnostic techniques for communicable diseases and summarizes currently available aptamers that target various pathogens, including the SARS-CoV-2 virus. Moreover, this review discusses how oligonucleotide aptamers might be leveraged to control pathogen propagation and improve host immune system responses. This review offers a comprehensive data source to the further develop aptamer-based diagnostics and therapeutics specific for infectious diseases.

Aptamers for Anti-Viral Therapeutics and Diagnostics

Viral infections cause a host of fatal diseases and seriously affect every form of life from bacteria to humans. Although most viral infections can receive appropriate treatment thereby limiting damage to life and livelihood with modern medicine and early diagnosis, new types of viral infections are continuously emerging that need to be properly and timely treated. As time is the most important factor in the progress of many deadly viral diseases, early detection becomes of paramount importance for effective treatment. Aptamers are small oligonucleotide molecules made by the systematic evolution of ligands by exponential enrichment (SELEX). Aptamers are characterized by being able to specifically bind to a target, much like antibodies. However, unlike antibodies, aptamers are easily synthesized, modified, and are able to target a wider range of substances, including proteins and carbohydrates. With these advantages in mind, many studies on aptamer-based viral diagnosis and treatments are currently in progress. The use of aptamers for viral diagnosis requires a system that recognizes the binding of viral molecules to aptamers in samples of blood, serum, plasma, or in virus-infected cells. From a therapeutic perspective, aptamers target viral particles or host cell receptors to prevent the interaction between the virus and host cells or target intracellular viral proteins to interrupt the life cycle of the virus within infected cells. In this paper, we review recent attempts to use aptamers for the diagnosis and treatment of various viral infections.

Artificial Intelligence in Aptamer-Target Binding Prediction

Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer-target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer-target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization.

Extended Interactions between HIV-1 Viral RNA and tRNALys3 Are Important to Maintain Viral RNA Integrity

The reverse transcription of the human immunodeficiency virus 1 (HIV-1) initiates upon annealing of the 3′-18-nt of tRNA^Lys3 onto the primer binding site (PBS) in viral RNA (vRNA). Additional intermolecular interactions between tRNA^Lys3 and vRNA have been reported, but their functions remain unclear. Here, we show that abolishing one potential interaction, the A-rich loop: tRNA^Lys3 anticodon interaction in the HIV-1 MAL strain, led to a decrease in viral infectivity and reduced the synthesis of reverse transcription products in newly infected cells. In vitro biophysical and functional experiments revealed that disruption of the extended interaction resulted in an increased affinity for reverse transcriptase (RT) and enhanced primer extension efficiency. In the absence of deoxyribose nucleoside triphosphates (dNTPs), vRNA was degraded by the RNaseH activity of RT, and the degradation rate was slower in the complex with the extended interaction. Consistently, the loss of vRNA integrity was detected in virions containing A-rich loop mutations. Similar results were observed in the HIV-1 NL4.3 strain, and we show that the nucleocapsid (NC) protein is necessary to promote the extended vRNA: tRNA^Lys3 interactions in vitro. In summary, our data revealed that the additional intermolecular interaction between tRNA^Lys3 and vRNA is likely a conserved mechanism among various HIV-1 strains and protects the vRNA from RNaseH degradation in mature virions.

Methods and Applications of In Silico Aptamer Design and Modeling

Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphates, nucleobases, amino acids, and drugs. During nucleic acid modeling and in silico design, a full set of in silico methods can be applied, such as docking, molecular dynamics (MD), and statistical analysis. The typical modeling workflow starts with structure prediction. Then, docking of target and aptamer is performed. Next, MD simulations are performed, which allows for an evaluation of the stability of aptamer/ligand complexes and determination of the binding energies with higher accuracy. Then, aptamer/ligand interactions are analyzed, and mutations of studied aptamers made. Subsequently, the whole procedure of molecular modeling can be reiterated. Thus, the interactions between aptamers and their ligands are complex and difficult to understand using only experimental approaches. Docking and MD are irreplaceable when aptamers are studied in silico.

2'-fluoro-modified pyrimidines enhance affinity of RNA oligonucleotides to HIV-1 reverse transcriptase

Nucleic acid aptamers can be chemically modified to enhance function, but modifying previously selected aptamers can have nontrivial structural and functional consequences. We present a reselection strategy to evaluate the impact of several modifications on preexisting aptamer pools. RNA aptamer libraries with affinity to HIV-1 reverse transcriptase (RT) were retranscribed with 2'-F, 2'-OMe, or 2'-NH₂ pyrimidines and subjected to three additional selection cycles. RT inhibition was observed for representative aptamers from several structural families identified by high-throughput sequencing when transcribed with their corresponding modifications. Thus, reselection identified specialized subsets of aptamers that tolerated chemical modifications from unmodified preenriched libraries. Inhibition was the strongest with the 2'-F-pyrimidine (2'-FY) RNAs, as compared to inhibition by the 2'-OMeY and 2'-NH₂Y RNAs. Unexpectedly, a diverse panel of retroviral RTs were strongly inhibited by all 2'-FY-modified transcripts, including sequences that do not inhibit those RTs as unmodified RNA. The magnitude of promiscuous RT inhibition was proportional to mole fraction 2'-FY in the transcript. RT binding affinity by 2'-FY transcripts was more sensitive to salt concentration than binding by unmodified transcripts, indicating that interaction with retroviral RTs is more ionic in character for 2'-FY RNA than for unmodified 2'-OH RNA. These surprising features of 2'-FY-modified RNA may have general implications for applied aptamer technologies.

Integrative structural biology studies of HIV-1 reverse transcriptase binding to a high-affinity DNA aptamer

The high-resolution crystal structure of HIV-1 reverse transcriptase (RT) bound to a 38-mer DNA hairpin aptamer with low pM affinity was previously described. The high-affinity binding aptamer contained 2'-O-methyl modifications and a seven base-pair GC-rich tract and the structure of the RT-aptamer complex revealed specific contacts between RT and the template strand of the aptamer. Similar to all crystal structures of RT bound to nucleic acid template-primers, the aptamer bound RT with a bend in the duplex DNA. To understand the structural basis for the ultra-high-affinity aptamer binding, an integrative structural biology approach was used. Hydrogen-deuterium exchange coupled to liquid chromatography-mass spectrometry (HDX-MS) was used to examine the structural dynamics of RT alone and in the presence of the DNA aptamer. RT was selectively labeled with 15N to unambiguously identify peptides from each subunit. HDX of unliganded RT shows a mostly stable core. The p66 fingers and thumb subdomains, and the RNase H domain are relatively dynamic. HDX indicates that both the aptamer and a scrambled version significantly stabilize regions of RT that are dynamic in the absence of DNA. No substantial differences in RT dynamics are observed between aptamer and scrambled aptamer binding, despite a large difference in binding affinity. Small-angle X-ray scattering and circular dichroism spectroscopy were used to investigate the aptamer conformation in solution and revealed a pre-bent DNA that possesses both A- and B-form helical character. Both the 2'-O-methyl modifications and the GC tract appear to contribute to an energetically favorable conformation for binding to RT that contributes to the aptamer's ultra-high affinity for RT. The X-ray structure of RT with an RNA/DNA version of the aptamer at 2.8 Å resolution revealed a potential role of the hairpin positioning in affinity. Together, the data suggest that both the 2'-O-methyl modifications and the GC tract contribute to an energetically favorable conformation for high-affinity binding to RT.