In silico design and validation of high-affinity RNA aptamers targeting epithelial cellular adhesion molecule dimers

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.

In silico selection of aptamers against SARS-CoV-2

Aptamers are molecular recognition elements that have been extensively deployed in a wide array of applications ranging from diagnostics to therapeutics. Due to their unique properties as compared to antibodies, aptamers were also largely isolated during the COVID-19 pandemic for multiple purposes. Typically generated by conventional SELEX, the inherent drawbacks of the process including the time-consuming, cumbersome and resource-intensive nature catalysed the move to adopt in silico approaches to isolate aptamers. Impressive performances of these in silico-derived aptamers in their respective assays have been documented thus far, bearing testimony to the huge potential of the in silico approaches, akin to the traditional SELEX in isolating aptamers. In this study, we provide an overview of the in silico selection of aptamers against SARS-CoV-2 by providing insights into the basic steps involved, which comprise the selection of the initial single-stranded nucleic acids, determination of the secondary and tertiary structures and in silico approaches that include both rigid docking and molecular dynamics simulations. The different approaches involving aptamers against SARS-CoV-2 were illuminated and the need to verify these aptamers by experimental validation was also emphasized. Cognizant of the need to continuously improve aptamers, the strategies embraced thus far for post-in silico selection modifications were enumerated. Shedding light on the steps involved in the in silico selection can set the stage for further improvisation to augment the functionalities of the aptamers in the future.

A Multifunctional Aptamer Decorated Lipid Nanoparticles for the Delivery of EpCAM-targeted CRISPR/Cas9 Plasmid for Efficacious In Vivo Tumor Regression

Epithelial cell adhesion molecule (EpCAM) gene encodes a type-I trans-membrane glycoprotein that is overexpressed in many cancerous epithelial cells and promotes tumor progression by regulating the expression of several oncogenes like c-myc and other cyclins. Because of this tumorigenic association, the EpCAM gene has been a potential target for anti-cancer therapy in recent days. Herein, it is attempted to knockout the proto-oncogenic EpCAM expression by efficiently delivering an all-in-one Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) plasmid via a lipid nanoparticle system made out of synthetic stimuli-sensitive lipids. The plasmid possesses the necessary information in the form of a guide RNA targeted to the EpCAM gene. The aptamer decorated system selectively targets EpCAM overexpressed cells and efficiently inhibits the genetic expression. It has explored the pH-responsive property of the developed lipid nanoparticles and monitored their efficacy in various cancer cell lines of different origins with elevated EpCAM levels. The phenomenon has further been validated in vivo in non-immunocompromised mouse tumor models. Overall, the newly developed aptamer decorated lipid nanoparticle system has been proven to be efficacious for the delivery of EpCAM-targeted CRISPR/Cas9 plasmid.

Aptamer Screening: Current Methods and Future Trend towards Non-SELEX Approach

Aptamers are nucleic acid sequences that specifically bind with target molecules and are vital to applications such as biosensing, drug development, disease diagnostics, etc. The traditional selection procedure of aptamers is based on the Systematic Evolution of Ligands by an Exponential Enrichment (SELEX) process, which relies on repeating cycles of screening and amplification. With the rapid development of aptamer applications, RNA and XNA aptamers draw more attention than before. But their selection is troublesome due to the necessary reverse transcription and transcription process (RNA) or low efficiency and accuracy of enzymes for amplification (XNA). In light of this, we review the recent advances in aptamer selection methods and give an outlook on future development in a non-SELEX approach, which simplifies the procedure and reduces the experimental costs. We first provide an overview of the traditional SELEX methods mostly designed for screening DNA aptamers to introduce the common tools and methods. Then a section on the current screening methods for RNA and XNA is prepared to demonstrate the efforts put into screening these aptamers and the current difficulties. We further predict that the future trend of aptamer selection lies in non-SELEX methods that do not require nucleic acid amplification. We divide non-SELEX methods into an immobilized format and non-immobilized format and discuss how high-resolution partitioning methods could facilitate the further improvement of selection efficiency and accuracy.

NF2 regulates IP3R-mediated Ca2+ signal and apoptosis in meningiomas

Meningiomas are the most common primary intracranial tumors and account for nearly 30% of all nervous system tumors. Approximately half of meningioma patients exhibit neurofibromin 2 (NF2) gene inactivation. Here, NF2 was shown to interact with the endoplasmic reticulum (ER) calcium (Ca2+) channel inositol 1,4,5-trisphosphate receptor 1 (IP3R1) in IOMM-Lee, a high-grade malignant meningioma cell line, and the F1 subdomain of NF2 plays a critical role in this interaction. Functional assays indicated that NF2 promotes the phosphorylation of IP3R (Ser 1756) and IP3R-mediated endoplasmic reticulum (ER) Ca2+ release by binding to IP3R1, which results in Ca2+-dependent apoptosis. Knockout of NF2 decreased Ca2+ release and promoted resistance to apoptosis, which was rescued by wild-type NF2 overexpression but not by F1 subdomain deletion truncation overexpression. The effects of NF2 defects on the development of tumors were further studied in mouse models. The decreased expression level of NF2 caused by NF2 gene knockout or mutation affects the activity of the IP3R channel, which reduces Ca2+-dependent apoptosis, thereby promoting the development of tumors. We elucidated the interaction patterns of NF2 and IP3R1, revealed the molecular mechanism through which NF2 regulates IP3R1-mediated Ca2+ release, and elucidated the new pathogenic mechanism of meningioma-related NF2 variants. Our study broadens the current understanding of the biological function of NF2 and provides ideas for drug screening of NF2-associated meningioma.

Inhibition of DEF-p65 Interactions as a Potential Avenue to Suppress Tumor Growth in Pancreatic Cancer

The limited success of current targeted therapies for pancreatic cancer underscores an urgent demand for novel treatment modalities. The challenge in mitigating this malignancy can be attributed to the digestive organ expansion factor (DEF), a pivotal yet underexplored factor in pancreatic tumorigenesis. The study uses a blend of in vitro and in vivo approaches, complemented by the theoretical analyses, to propose DEF as a promising anti-tumor target. Analysis of clinical samples reveals that high expression of DEF is correlated with diminished survival in pancreatic cancer patients. Crucially, the depletion of DEF significantly impedes tumor growth. The study further discovers that DEF binds to p65, shielding it from degradation mediated by the ubiquitin-proteasome pathway in cancer cells. Based on these findings and computational approaches, the study formulates a DEF-mimicking peptide, peptide-031, designed to disrupt the DEF-p65 interaction. The effectiveness of peptide-031 in inhibiting tumor proliferation has been demonstrated both in vitro and in vivo. This study unveils the oncogenic role of DEF while highlighting its prognostic value and therapeutic potential in pancreatic cancer. In addition, peptide-031 is a promising therapeutic agent with potent anti-tumor effects.

Multiplexed In Vivo Screening Using Barcoded Aptamer Technology to Identify Oligonucleotide-Based Targeting Reagents

Recent FDA approvals of mRNA vaccines, short-interfering RNAs, and antisense oligonucleotides highlight the success of oligonucleotides as therapeutics. Aptamers are excellent affinity reagents that can selectively label protein biomarkers, but their clinical application has lagged. When formulating a given aptamer for in vivo use, molecular design details can determine biostability and biodistribution; therefore, extensive postselection manipulation is often required for each new design to identify clinically useful reagents harboring improved pharmacokinetic properties. Few methods are available to comprehensively screen such aptamers, especially in vivo, constituting a significant bottleneck in the field. In this study, we introduce barcoded aptamer technology (BApT) for multiplexed screening of predefined aptamer formulations in vitro and in vivo. We demonstrate this technology by simultaneously investigating 20 aptamer formulations, each harboring different molecular designs, for targeting Non-Small Cell Lung Cancer cells and tumors. Screening in vitro identified a 45 kDa bispecific formulation as the best cancer cell targeting reagent, whereas screening in vivo identified a 30 kDa monomeric formulation as the best tumor-specific targeting reagent. The multiplexed analysis pipeline also identified biodistribution phenotypes shared among formulations with similar molecular architectures. The BApT approach we describe here has the potential for broad application to fields where oligonucleotide-based targeting reagents are desired.

Design single-stranded DNA aptamer of cluster of differentiation 47 protein by stochastic tunnelling-basin hopping-discrete molecular dynamics method

The formation of the Cluster of Differentiation 47 (CD47, PDB code: 2JJT)/signal regulatory protein α (SIRPα) complex is very important as it protects healthy cells from immune clearance while promoting macrophage phagocytosis for tumour elimination. Although several antibodies have been developed for cancer therapy, new function-blocking aptamers are still under development. This study aims to design the aptamer AptCD47, which can block the formation of the CD47/SIRPα complex. This study employs the MARTINI coarse-grained (CG) force field and the stochastic tunnelling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method to identify the most stable AptCD47/CD47 complexes. Coarse-grained molecular dynamics (CGMD) simulations were used to obtain root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) analyses. The results demonstrate that the formation of AptCD47/CD47 complexes renders the CD47 structure more stable than the single CD47 molecule in a water environment. The minimum energy pathway (MEP) obtained by the nudged elastic band (NEB) method indicates that the binding processes of 5'-ATTCAATTCC-3' and 5'-AGTGCAATCT-3' to CD47 are barrierless, which is much lower than the binding barrier of SIRPα to CD47 of about 14.23 kcal/mol. Therefore, these two AptCD47/CD47 complexes can create a high spatial binding barrier for SIRPα, preventing the formation of a stable CD47/SIRPα complex. The proposed numerical process with the MARTINI CG force field can be used to design CD47 aptamers that efficiently block SIRPα from binding to CD47.Communicated by Ramaswamy H. Sarma.

The Deinococcus protease PprI senses DNA damage by directly interacting with single-stranded DNA

Bacteria have evolved various response systems to adapt to environmental stress. A protease-based derepression mechanism in response to DNA damage was characterized in Deinococcus, which is controlled by the specific cleavage of repressor DdrO by metallopeptidase PprI (also called IrrE). Despite the efforts to document the biochemical, physiological, and downstream regulation of PprI-DdrO, the upstream regulatory signal activating this system remains unclear. Here, we show that single-stranded DNA physically interacts with PprI protease, which enhances the PprI-DdrO interactions as well as the DdrO cleavage in a length-dependent manner both in vivo and in vitro. Structures of PprI, in its apo and complexed forms with single-stranded DNA, reveal two DNA-binding interfaces shaping the cleavage site. Moreover, we show that the dynamic monomer-dimer equilibrium of PprI is also important for its cleavage activity. Our data provide evidence that single-stranded DNA could serve as the signal for DNA damage sensing in the metalloprotease/repressor system in bacteria. These results also shed light on the survival and acquired drug resistance of certain bacteria under antimicrobial stress through a SOS-independent pathway.

Induction of binding sites for RecA aptamers by differentiated-competition capillary Electrophoresis-SELEX

The binding site-oriented SELEX strategy is an effective way to promote the functional evolution of aptamers. Here we report a novel aptamer screening strategy (Differentiated-competition Capillary Electrophoresis-SELEX), which enables candidate aptamers to be directionally induced to bind to different active sites of RecA. In this strategy, we introduce two competing binding factors into the "binding - dissociation" dynamic equilibrium system of RecA and ssDNA libraries. Due to the completely different binding mechanism of the competitive factor and the ssDNA library, it exerts different interference on the binding of RecA and the ssDNA library, which directed the binding site of aptamer candidates during the SELEX process. Multifunctional aptamers with high affinity and specificity were found to inhibit RecA activity by binding to different active sites. In conclusion, the SELEX method developed in our current study have identified a variety of biologically functional aptamers with relatively well-defined binding sites that regulate RecA protein activity, which has potential applications and future prospects for accurate screening of biological functional aptamers.

Aptamer-Protein Interactions: From Regulation to Biomolecular Detection

Serving as the basis of cell life, interactions between nucleic acids and proteins play essential roles in fundamental cellular processes. Aptamers are unique single-stranded oligonucleotides generated by in vitro evolution methods, possessing the ability to interact with proteins specifically. Altering the structure of aptamers will largely modulate their interactions with proteins and further affect related cellular behaviors. Recently, with the in-depth research of aptamer-protein interactions, the analytical assays based on their interactions have been widely developed and become a powerful tool for biomolecular detection. There are some insightful reviews on aptamers applied in protein detection, while few systematic discussions are from the perspective of regulating aptamer-protein interactions. Herein, we comprehensively introduce the methods for regulating aptamer-protein interactions and elaborate on the detection techniques for analyzing aptamer-protein interactions. Additionally, this review provides a broad summary of analytical assays based on the regulation of aptamer-protein interactions for detecting biomolecules. Finally, we present our perspectives regarding the opportunities and challenges of analytical assays for biological analysis, aiming to provide guidance for disease mechanism research and drug discovery.

In vitro selection of aptamers and their applications

The introduction of the in-vitro evolution method known as SELEX (Systematic Evolution of Ligands by Exponential enrichment) more than 30 years ago led to the conception of versatile synthetic receptors known as aptamers. Offering many benefits such as low cost, high stability and flexibility, aptamers have sparked innovation in molecular diagnostics, enabled advances in synthetic biology and have facilitated new therapeutic approaches. The SELEX method itself is inherently adaptable and offers near limitless possibilities in yielding functional nucleic acid ligands. This Primer serves to provide guidance on experimental design and highlight new growth areas for this impactful technology.

De Novo Evolution of an Antibody-Mimicking Multivalent Aptamer via a DNA Framework

Multivalent interactions can often endow ligands with more efficient binding performance toward target molecules. Generally speaking, a multivalent aptamer can be constructed via post-assembly based on chemical structural information of target molecules and pre-identified monovalent aptamers derived from traditional systematic evolution of ligands by exponential enrichment (SELEX) technology. However, many target molecules may not have known matched aptamer partners, thus a de novo evolution will be highly desired as an alternative strategy for directed selection of a high-avidity, multivalent aptamer. Here, inspired by the superiority of multivalent interactions between antibodies and antigens, a direct SELEX strategy with a preorganized DNA framework library for an "Antibody-mimicking multivalent aptamer" (Amap) selection to epithelial cell adhesion molecule (EpCAM), a model target protein is reported. The Amap presents a relatively good binding affinity through both aptamer moieties concurrently binding to EpCAM, which has been confirmed by affinity analysis and molecular modeling. Furthermore, dynamic interactions between Amap and EpCAM are directly visualized by magnetic tweezers at the single-molecule level. A nice binding affinity of Amap to EpCAM-positive cancer cells has also been verified, which hints that their Amap-SELEX strategy has the potential to be a new route for de novo evolution of multivalent aptamers.

In Silico Approaches for the Identification of Aptamer Binding Interactions to Leptospira spp. Cell Surface Proteins

Aptamers are nucleic acids that can bind with high affinity and specificity to a range of target molecules. However, their functionality relies on their secondary and tertiary structures such that the combination of nucleotides determines their three-dimensional conformation. In this study, the binding mechanisms of candidate aptamers and their interactions with selected target proteins found in the cell surface of Leptospira were predicted to select high-affinity aptamers. Four aptamers were evaluated through molecular modeling and docking using available software and web-based tools, following the workflow previously designed for in silico evaluation of DNA aptamers. The most predominant and highly conserved surface-exposed proteins among pathogenic Leptospira species were used as aptamer targets. The highest number of interactions was seen in aptamers AP5 and AP1. Hydrogen bonds, along with a few hydrophobic interactions, occur in most aptamer-protein complexes. Further analysis revealed serine, threonine, glutamine, and lysine as main protein residues. H-bond interactions occur mostly with polar amino acids, as reflected in the predicted interaction profiles of aptamer-protein complexes. In silico strategies allowed the identification of key residues crucial in aptamer-target interaction during aptamer screening. Such information can be used in aptamer modification for improved binding affinity and accuracy for diagnostics application.

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.

Molecular Dynamics Study of the Curvature-Driven Interactions between Carbon-Based Nanoparticles and Amino Acids

We researched the interaction between six representative carbon-based nanoparticles (CBNs) and 20 standard amino acids through all-atom molecular dynamics simulations. The six carbon-based nanoparticles are fullerene(C60), CNT55L3, CNT1010L3, CNT1515L3, CNT2020L3, and two-dimensional graphene (graphene33). Their curvatures decrease sequentially, and all of the CNTs are single-walled carbon nanotubes. We observed that as the curvature of CBNs decreases, the adsorption effect of the 20 amino acids with them has an increasing trend. In addition, we also used multi-dimensional clustering to analyze the adsorption effects of 20 amino acids on six carbon-based nanoparticles. We observed that the π-π interaction still plays an extremely important role in the adsorption of amino acids on carbon-based nanoparticles. Individual long-chain amino acids and "Benzene-like" Pro also have a strong adsorption effect on carbon-based nanoparticles.

SARS-CoV-2 Delta Variant: Interplay between Individual Mutations and Their Allosteric Synergy

Since its first appearance in April 2021, B.1.617.2, also termed variant Delta, catalyzed one major worldwide wave dominating the second year of coronavirus disease 2019 (COVID-19) pandemic. Despite its quick disappearance worldwide, the strong virulence caused by a few point mutations remains an unsolved problem largely. Along with the other two sublineages, the Delta variant harbors an accumulation of Spike protein mutations, including the previously identified L452R, E484Q, and the newly emerged T478K on its receptor binding domain (RBD). We used molecular dynamics (MD) simulations, in combination with free energy perturbation (FEP) calculations, to examine the effects of two combinative mutation sets, L452R + E484Q and L452R + T478K. Our dynamic trajectories reveal an enhancement in binding affinity between mutated RBD and the common receptor protein angiotensin converting enzyme 2 (ACE2) through a net increase in the buried molecular surface area of the binary complex. This enhanced binding, mediated through Gln493, sets the same stage for all three sublineages due to the presence of L452R mutation. The other mutation component, E484Q or T478K, was found to impact the RBD-ACE2 binding and help the variant to evade several monoclonal antibodies (mAbs) in a distinct manner. Especially for L452R + T478K, synergies between mutations are mediated through a complex residual and water interaction network and further enhance its binding to ACE2. Taking together, this study demonstrates that new variants of SARS-CoV-2 accomplish both "attack" (infection) and "defense" (antibody neutralization escape) with the same "polished sword" (mutated Spike RBD).

Epithelial Cell Adhesion Molecule (EpCAM) Expression Can Be Modulated via NFκB

The epithelial cell adhesion molecule (EpCAM) is considered an essential proliferation signature in cancer. In the current research study, qPCR induced expression of EpCAM was noted in acute lymphoblastic leukemia (ALL) cases. Costunolide, a sesquiterpene lactone found in crepe ginger and lettuce, is a medicinal herb with anticancer properties. Expression of EpCAM and its downstream target genes (Myc and TERT) wasdownregulated upon treatment with costunolide in Jurkat cells. A significant change in the telomere length of Jurkat cells was not noted at 72 h of costunolide treatment. An in silico study revealed hydrophobic interactions between EpCAM extracellular domain and Myc bHLH with costunolide. Reduced expression of NFκB, a transcription factor of EpCAM, Myc, and TERT in costunolide-treated Jurkat cells, suggested that costunolide inhibits gene expression by targeting NFκB and its downstream targets. Overall, the study proposes that costunolide could be a promising therapeutic biomolecule for leukemia.

Inhibition of Autophagy Promotes the Elimination of Liver Cancer Stem Cells by CD133 Aptamer-Targeted Delivery of Doxorubicin

Doxorubicin is the most frequently used chemotherapeutic agent for the treatment of hepatocellular carcinoma. However, one major obstacle to the effective management of liver cancer is the drug resistance derived from the cancer stem cells. Herein, we employed a CD133 aptamer for targeted delivery of doxorubicin into liver cancer stem cells to overcome chemoresistance. Furthermore, we explored the efficacy of autophagy inhibition to sensitize liver cancer stem cells to the treatment of CD133 aptamer-doxorubicin conjugates based on the previous observation that doxorubicin contributes to the survival of liver cancer stem cells by activating autophagy. The kinetics and thermodynamics of aptamer-doxorubicin binding, autophagy induction, cell apoptosis, and self-renewal of liver cancer stem cells were studied using isothermal titration calorimetry, Western blot analysis, annexin V assay, and tumorsphere formation assay. The aptamer-cell binding andintracellular accumulation of doxorubicin were quantified via flow cytometry. CD133 aptamer-guided delivery of doxorubicin resulted in a higher doxorubicin concentration in the liver cancer stem cells. The combinatorial treatment strategy of CD133 aptamer-doxorubicin conjugates and an autophagy inhibitor led to an over 10-fold higher elimination of liver cancer stem cells than that of free doxorubicin in vitro. Future exploration of cancer stem cell-targeted delivery of doxorubicin in conjunction with autophagy inhibition in vivo may well lead to improved outcomes in the treatment of hepatocellular carcinoma.

Computationally Designed Anti-LuxP DNA Aptamer Suppressed Flagellar Assembly- and Quorum Sensing-Related Gene Expression in Vibrio parahaemolyticus

(1) Background: Quorum sensing (QS) is the chemical communication between bacteria that sense chemical signals in the bacterial population to control phenotypic changes through the regulation of gene expression. The inhibition of QS has various potential applications, particularly in the prevention of bacterial infection. QS can be inhibited by targeting the LuxP, a periplasmic receptor protein that is involved in the sensing of the QS signaling molecule known as the autoinducer 2 (AI-2). The sensing of AI-2 by LuxP transduces the chemical information through the inner membrane sensor kinase LuxQ protein and activates the QS cascade. (2) Methods: An in silico approach was applied to design DNA aptamers against LuxP in this study. A method combining molecular docking and molecular dynamics simulations was used to select the oligonucleotides that bind to LuxP, which were then further characterized using isothermal titration calorimetry. Subsequently, the bioactivity of the selected aptamer was examined through comparative transcriptome analysis. (3) Results: Two aptamer candidates were identified from the ITC, which have the lowest dissociation constants (Kd) of 0.2 and 0.5 micromolar. The aptamer with the lowest Kd demonstrated QS suppression and down-regulated the flagellar-assembly-related gene expression. (4) Conclusions: This study developed an in silico approach to design an aptamer that possesses anti-QS properties.

Optimization of Gonyautoxin1/4-Binding G-Quadruplex Aptamers by Label-Free Surface-Enhanced Raman Spectroscopy

Nucleic acids with G-quadruplex (G4) structures play an important role in physiological function, analysis and detection, clinical diagnosis and treatment, and new drug research and development. Aptamers obtained using systematic evolution of ligands via exponential enrichment (SELEX) screening technology do not always have the best affinity or binding specificity to ligands. Therefore, the establishment of a structure-oriented experimental method is of great significance. To study the potential of surface-enhanced Raman spectroscopy (SERS) in aptamer optimization, marine biotoxin gonyautoxin (GTX)1/4 and its G4 aptamer obtained using SELEX were selected. The binding site and the induced fit of the aptamer to GTX1/4 were confirmed using SERS combined with two-dimensional correlation spectroscopy. The intensity of interaction between GTX1/4 and G4 was also quantified by measuring the relative intensity of SERS bands corresponding to intramolecular hydrogen bonds. Furthermore, the interaction between GTX1/4 and optimized aptamers was analyzed. The order of intensity change in the characteristic bands of G4 aptamers was consistent with the order of affinity calculated using microscale thermophoresis and molecular dynamics simulations. SERS provides a rapid, sensitive, and economical post-SELEX optimization of aptamers. It is also a reference for future research on other nucleic acid sequences containing G4 structures.

Thermodynamic Swings: How Ideal Complex of Cas9-RNA/DNA Forms

Most processes of the recognition and formation of specific complexes in living systems begin with collisions in solutions or quasi-solutions. Then, the thermodynamic regulation of complex formation and fine tuning of complexes come into play. Precise regulation is very important in all cellular processes, including genome editing using the CRISPR-Cas9 tool. The Cas9 endonuclease is an essential component of the CRISPR-Cas-based genome editing systems. The attainment of high-specificity and -efficiency Cas9 during targeted DNA cleavage is the main problem that limits the practical application of the CRISPR-Cas9 system. In this study, we analyzed the thermodynamics of interaction of a complex's components of Cas9-RNA/DNA through experimental and computer simulation methods. We found that there is a small energetic preference during Cas9-RNA/DNA formation from the Cas9-RNA and DNA/DNA duplex. The small difference in binding energy is relevant for biological interactions and could be part of the sequence-specific recognition of double-stranded DNA by the CRISPR-Cas9 system.

Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming procedures. In silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools, a rational design of aptamers is demonstrated. This “smart” SELEX method is experimentally proved by choosing the best five aptamer candidates obtained from the design process and applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of five different aptamers leads to a significant difference in the sensor’s response. This can be explained by considering the aptamers’ conformational change due to their interaction with the target molecule. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were used to confirm the high selectivity of the designed aptamers. The proposed in silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers and potentially be applied to any target molecule.

Probing TDP-43 condensation using an in silico designed aptamer

Aptamers are artificial oligonucleotides binding to specific molecular targets. They have a promising role in therapeutics and diagnostics but are often difficult to design. Here, we exploited the catRAPID algorithm to generate aptamers targeting TAR DNA-binding protein 43 (TDP-43), whose aggregation is associated with Amyotrophic Lateral Sclerosis. On the pathway to forming insoluble inclusions, TDP-43 adopts a heterogeneous population of assemblies, many smaller than the diffraction-limit of light. We demonstrated that our aptamers bind TDP-43 and used the tightest interactor, Apt-1, as a probe to visualize TDP-43 condensates with super-resolution microscopy. At a resolution of 10 nanometers, we tracked TDP-43 oligomers undetectable by standard approaches. In cells, Apt-1 interacts with both diffuse and condensed forms of TDP-43, indicating that Apt-1 can be exploited to follow TDP-43 phase transition. The de novo generation of aptamers and their use for microscopy opens a new page to study protein condensation.

Generative aptamer discovery using RaptGen

Nucleic acid aptamers are generated by an in vitro molecular evolution method known as systematic evolution of ligands by exponential enrichment (SELEX). Various candidates are limited by actual sequencing data from an experiment. Here we developed RaptGen, which is a variational autoencoder for in silico aptamer generation. RaptGen exploits a profile hidden Markov model decoder to represent motif sequences effectively. We showed that RaptGen embedded simulation sequence data into low-dimensional latent space on the basis of motif information. We also performed sequence embedding using two independent SELEX datasets. RaptGen successfully generated aptamers from the latent space even though they were not included in high-throughput sequencing. RaptGen could also generate a truncated aptamer with a short learning model. We demonstrated that RaptGen could be applied to activity-guided aptamer generation according to Bayesian optimization. We concluded that a generative method by RaptGen and latent representation are useful for aptamer discovery.

Electrochemical Aptasensors for Antibiotics Detection: Recent Achievements and Applications for Monitoring Food Safety

Antibiotics are often used in human and veterinary medicine for the treatment of bacterial diseases. However, extensive use of antibiotics in agriculture can result in the contamination of common food staples such as milk. Consumption of contaminated products can cause serious illness and a rise in antibiotic resistance. Conventional methods of antibiotics detection such are microbiological assays chromatographic and mass spectroscopy methods are sensitive; however, they require qualified personnel, expensive instruments, and sample pretreatment. Biosensor technology can overcome these drawbacks. This review is focused on the recent achievements in the electrochemical biosensors based on nucleic acid aptamers for antibiotic detection. A brief explanation of conventional methods of antibiotic detection is also provided. The methods of the aptamer selection are explained, together with the approach used for the improvement of aptamer affinity by post-SELEX modification and computer modeling. The substantial focus of this review is on the explanation of the principles of the electrochemical detection of antibiotics by aptasensors and on recent achievements in the development of electrochemical aptasensors. The current trends and problems in practical applications of aptasensors are also discussed.

Recent advances in aptamer applications for analytical biochemistry

Aptamers are typically defined as relatively short (20-60 nucleotides) single-stranded DNA or RNA molecules that bind with high affinity and specificity to various types of targets. Aptamers are frequently referred to as "synthetic antibodies" but are easier to obtain, less expensive to produce, and in several ways more versatile than antibodies. The beginnings of aptamers date back to 1990, and since then there has been a continual increase in aptamer publications. The intent of the present account was to focus on recent original research publications, i.e., those appearing in 2019 through April 2020, when this account was written. A Google Scholar search of this recent literature was performed for relevance-ranking of articles. New methods for selection of aptamers were not included. Nine categories of applications were organized and representative examples of each are given. Finally, an outlook is offered focusing on "faster, better, cheaper" application performance factors as key drivers for future innovations in aptamer applications.

Recent advances in the selection of cancer-specific aptamers for the development of biosensors

An early diagnosis has the potential to greatly decrease cancer mortality. For that purpose, specific cancer biomarkers have been molecularly targeted by aptamer sequences to enable an accurate and rapid detection. Aptamer-based biosensors for cancer diagnostics are a promising alternative to those using antibodies, due to their high affinity and specificity to the target molecules and advantageous production. Synthetic nucleic acid aptamers are generated by in vitro Systematic Evolution of Ligands by Exponential enrichment (SELEX) methodologies that have been improved over the years to enhance the efficacy and to shorten the selection process. Aptamers have been successfully applied in electrochemical, optical, photoelectrochemical and piezoelectrical-based detection strategies. These aptasensors comprise a sensitive, accurate and inexpensive option for cancer detection being used as point-of-care devices. This review highlights the recent advances in cancer biomarkers, achievements and optimizations made in aptamer selection, as well as the different aptasensors developed for the detection of several cancer biomarkers.

Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. This study aims to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

Cell-SELEX-based selection of ssDNA aptamers for specifically targeting BRAF V600E-mutated melanoma

Malignant melanoma is regarded as the most aggressive form of skin cancer, and is responsible for most death caused by skin cancer. BRAF mutations occur in approximately 40-50% of melanomas, with V600E being the most common mutation. Testing for BRAF mutations and targeted therapy have markedly improved long-term survival for patients with BRAF-mutated melanoma. Here, we report two aptamers, CH1 and CH5 generated by Cell-SELEX, against BRAF V600E-mutated human melanoma cells A375. The two aptamers exhibited high affinity to target cells with low dissociation constants (K_d) in the nanomolar range. Furthermore, the binding of two aptamers to target cells was independent of incubation temperature, and their molecular targets were demonstrated to be membrane proteins on the cell surface. We also demonstrated that aptamer CH1 was able to bind to metastatic colorectal cancer cells harboring BRAF V600E mutation, indicating a relationship between aptamer CH1 and BRAF V600E-related metastatic cancer. Owing to the structure stability and high selectivity to BRAF V600E-mutated targeting cells, aptamer CH1 holds great potential as a molecular probe for the detection of BRAF V600E-mutated metastatic melanoma.

A Novel Strategy Conjugating PD-L1 Polypeptide With Doxorubicin Alleviates Chemotherapeutic Resistance and Enhances Immune Response in Colon Cancer

Background

Modifying the structure of anti-tumor chemotherapy drug is of significance to enhance the specificity and efficacy of drug-delivery. A novel proteolysis resistant PD-L1-targeted peptide (PPA1) has been reported to bind to PD-L1 and disrupt the PD-1/PD-L1 interaction, thus appearing as an outstanding tumor-targeting modification of synergistic drug conjugate for effective anti-tumor treatment. However, the combination regimen of coupling PD-L1 polypeptide with chemotherapeutic drug in tumoricidal treatment has not been reported thus far.

Methods

We developed a novel synergistic strategy by conjugating PPA1 to doxorubicin (DOX) with a pH sensitive linker that can trigger the release of DOX near acidic tumor tissues. The binding affinity of PPA1-DOX with PD-L1 and the acid-sensitive cleavage of PPA1-DOX were investigated. A mouse xenograft model of colon cancer was used to evaluate the biodistribution, cytotoxicity and anti-tumor activity of PPA1-DOX.

Results

PPA1-DOX construct showed high binding affinity with PD-L1 in vitro and specifically enriched within tumor when administered in vivo. PPA1-DOX exhibited a significantly lower toxicity and a remarkably higher antitumor activity in vivo, as compared with free PPA1, random polypeptide-DOX conjugate, DOX, or 5-FU, respectively. Moreover, increased infiltration of both CD4⁺ and CD8⁺ T cells was found in tumors from PPA1-DOX treated mice.

Conclusions

We describe here for the first time that the dual-functional conjugate PPA1-DOX, which consist of the PD-L1-targeted polypeptide that renders both the tumor-specific drug delivery and inhibitory PD-1/PD-L1 immune checkpoint inhibition, and a cytotoxic agent that is released and kills tumor cells once reaching tumor tissues, thus representing a promising therapeutic option for colon cancer with improved efficacy and reduced toxicity.

Dynamics-Based Peptide-MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen-major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

Molecular Dynamics Simulations of the Aptamer Domain of Guanidinium Ion Binding Riboswitch ykkC-III: Structural Insights into the Discrimination of Cognate and Alternate Ligands

Guanidinium ion is a toxic cellular metabolite. The ykkC-III riboswitch, an mRNA stretch, regulates the gene expression by undergoing a conformational change in response to the binding of a free guanidinium ion and thereby plays a potentially important role in alleviating guanidinium toxicity in cells. An experimental crystal structure of the guanidinium-bound aptamer domain of the riboswitch from Thermobifida Fusca revealed the overall RNA architecture and mapped the specific noncovalent interactions that stabilize the ligand within the binding pocket aptamer. However, details of how the aptamer domain discriminates the cognate ligand from its closest structurally analogous physiological metabolites (arginine and urea), and how the binding of cognate ligand arrays information from the aptamer domain to the expression platform for regulating the gene expression, are not well understood. To fill this void, we perform a cumulative of 2 μs all-atom explicit-solvent molecular dynamics (MD) simulations on the full aptamer domain, augmented with quantum-chemical calculations on the ligand-binding pocket, to compare the structural and dynamical details of the guanidinium-bound state with the arginine or urea bound states, as well as the unbound (open) state. Analysis of the ligand-binding pocket reveals that due to unfavorable interactions with the binding-pocket residues, urea cannot bind the aptamer domain and thereby cannot alter the gene expression. Although interaction of the guanidyl moiety of arginine within the binding pocket is either comparable or stronger than the guanidinium ion, additional non-native hydrogen-bonding networks, as well as differences in the dynamical details of the arginine-bound state, explain why arginine cannot transmit the information from the aptamer domain to the expression platform. Based on our simulations, we propose a mechanism of how the aptamer domain communicates with the expression platform. Overall, our work provides interesting insights into the ligand recognition by a specific class of riboswitches and may hopefully inspire future studies to further understand the gene regulation by riboswitches.

Multiple myeloma: therapeutic delivery of antibodies and aptamers

Multiple myeloma is the second most common hematological malignancy in adults, accounting for 2% of all cancer-related deaths in the UK. Current chemotherapy-based regimes are insufficient, as most patients relapse and develop therapy resistance. This review focuses on current novel antibody- and aptamer-based therapies aiming to overcome current therapy limitations, as well as their respective limitations and areas of improvement. The use of computer modeling methods, as a tool to study and improve ligand-receptor alignments for the use of novel therapy development will also be discussed, as it has become a rapid, reliable and comparatively inexpensive method of investigation.

E2EDNA: Simulation Protocol for DNA Aptamers with Ligands

We present E2EDNA, a simulation protocol and accompanying code for the molecular biophysics and materials science communities. This protocol is both easy to use and sufficiently efficient to simulate single-stranded (ss)DNA and small analyte systems that are important to cellular processes and nanotechnologies such as DNA aptamer-based sensors. Existing computational tools used for aptamer design focus on cost-effective secondary structure prediction and motif analysis in the large data sets produced by SELEX experiments. As a rule, they do not offer flexibility with respect to the choice of the theoretical engine or direct access to the simulation platform. Practical aptamer optimization often requires higher accuracy predictions for only a small subset of sequences suggested, e.g., by SELEX experiments, but in the absence of a streamlined procedure, this task is extremely time and expertise intensive. We address this gap by introducing E2EDNA, a computational framework that accepts a DNA sequence in the FASTA format and the structures of the desired ligands and performs approximate folding followed by a refining step, analyte complexation, and molecular dynamics sampling at the desired level of accuracy. As a case study, we simulate a DNA-UTP (uridine triphosphate) complex in water using the state-of-the-art AMOEBA polarizable force field. The code is available at https://github.com/InfluenceFunctional/E2EDNA.

Evolution of Thyroglobulin Loop Kinetics in EpCAM

Epithelial cell-activating molecule (EpCAM) is an important cancer biomarker and therapeutic target given its elevated expression in epithelial cancers. EpCAM is a type I transmembrane protein that forms cis-dimers along the thyroglobulin type-1A-like domain (TYD) in the extracellular region. The thyroglobulin loop (TY loop) within the TYD is structurally dynamic in the monomer state of human EpCAM, binding reversibly to a TYD site. However, it is not known if this flexibility is prevalent across different species. Here, we conduct over 17 μs of all-atom molecular dynamics simulations to study EpCAM TY loop kinetics of five different species, including human, mouse, chicken, frog, and fish. We find that the TY loop remains dynamic across evolution. In addition to the TYD binding site, we discover a second binding site for the TY loop in the C-terminal domain (CTD). Calculations of the dissociation rate constants from the simulation trajectories suggest a differential binding pattern of fish EpCAM and other organisms. Whereas fish TY loop has comparable binding for both TYD and CTD sites, the TY loops of other species preferably bind the TYD site. A hybrid construct of fish EpCAM with human TY loop restores the TYD binding preference, suggesting robust effects of the TY loop sequence on its dynamic behavior. Our findings provide insights into the structural dynamics of EpCAM and its implication in physiological functions.

Label free structure-switching fluorescence polarization detection of chloramphenicol with truncated aptamer

In this study, the original chloramphenicol aptamer containing 80 bases was truncated to 30 bases with high affinity by the SYBR Green I assay. It was found that the ionic strength and type affect the recognition of aptamers, especially magnesium ion played a vital role in the binding process. Furthermore, the binding performance of aptamer, including binding mode, key binding sites and conformational changes were further investigated by circular dichroism spectroscopy, UV-vis absorption spectrum and molecular docking. Based on these research data, we inferred that chloramphenicol bound to the minor groove region in the aptamer double helix. Finally, the optimized aptamer LLR10 was used to develop a novel label free fluorescence polarization assay to detect chloramphenicol within SYBR Green I as the source of fluorescence polarization signal. Under optimal conditions, the designed method showed a linear detection range of 0.1-10 nM with a detection limit of 0.06 nM. Additionally, the aptasensor exhibited a high accuracy to the detection of chloramphenicol in milk samples with a recovery rate from 93.7% to 98.4%. Therefore, the developed label free fluorescence polarization aptasensor provides a new idea for the rapid, reliable and sensitive detection of chloramphenicol, which can be applied to food safety control.

Appraisal of the Role of In silico Methods in Pyrazole Based Drug Design

Pyrazole and its derivatives are a pharmacologically and significantly active scaffolds that have innumerable physiological and pharmacological activities. They can be very good targets for the discovery of novel anti-bacterial, anti-cancer, anti-inflammatory, anti-fungal, anti-tubercular, antiviral, antioxidant, antidepressant, anti-convulsant and neuroprotective drugs. This review focuses on the importance of in silico manipulations of pyrazole and its derivatives for medicinal chemistry. The authors have discussed currently available information on the use of computational techniques like molecular docking, structure-based virtual screening (SBVS), molecular dynamics (MD) simulations, quantitative structure activity relationship (QSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to drug design using pyrazole moieties. Pyrazole based drug design is mainly dependent on the integration of experimental and computational approaches. The authors feel that more studies need to be done to fully explore the pharmacological potential of the pyrazole moiety and in silico method can be of great help.

Exploring the most stable aptamer/target molecule complex by the stochastic tunnelling-basin hopping-discrete molecular dynamics method

The stochastic tunnelling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method was applied to the search for the most stable biomolecular complexes in water by using the MARTINI coarse-grained (CG) model. The epithelial cell adhesion molecule (EpCAM, PDB code: 4MZV) was used as an EpCAM adaptor for an EpA (Apt_EpA) benchmark target molecule. The effects of two adsorption positions on the EpCAM were analysed, and it is found that the Apt_EpA adsorption configuration located within the EpCAM pocket-like structure is more stable and the energy barrier is lower due to the interaction with water. By the root mean square deviation (RMSD), the configuration of EpCAM in water is more conservative when the Apt_EpA binds to EpCAM by attaching to the pocket space of the EpCAM dimer. For Apt_EpA, the root mean square fluctuation (RMSF) analysis result indicates Nucleobase 1 and Nucleobase 2 display higher flexibility during the CGMD simulation. Finally, from the binding energy contour maps and histogram plots of EpCAM and each Apt_EpA nucleobase, it is clear that the binding energy adsorbed to the pocket-like structure is more continuous than that energy not adsorbed to the pocket-like structure. This study has proposed a new numerical process for applying the STUN-BH-DMD with the CG model, which can reduce computational details and directly find a more stable Apt_EpA/EpCAM complex in water.

Applications of isothermal titration calorimetry in pure and applied research from 2016 to 2020

The last 5 years have seen a series of advances in the application of isothermal titration microcalorimetry (ITC) and interpretation of ITC data. ITC has played an invaluable role in understanding multiprotein complex formation including proteolysis-targeting chimeras (PROTACS), and mitochondrial autophagy receptor Nix interaction with LC3 and GABARAP. It has also helped elucidate complex allosteric communication in protein complexes like trp RNA-binding attenuation protein (TRAP) complex. Advances in kinetics analysis have enabled the calculation of kinetic rate constants from pre-existing ITC data sets. Diverse strategies have also been developed to study enzyme kinetics and enzyme-inhibitor interactions. ITC has also been applied to study small molecule solvent and solute interactions involved in extraction, separation, and purification applications including liquid-liquid separation and extractive distillation. Diverse applications of ITC have been developed from the analysis of protein instability at different temperatures, determination of enzyme kinetics in suspensions of living cells to the adsorption of uremic toxins from aqueous streams.

Nucleic acid ligands act as a PAM and agonist depending on the intrinsic ligand binding state of P2RY2

Discovery of ligands for G protein–coupled receptors (GPCRs) is of importance in receptor biology and pharmacology but is still a challenging issue. Here, we propose a method for the discovery of ligands against GPCRs by employing a virus-like particle (VLP) and show unique properties of identified nucleic acid aptamers for GPCR. One aptamer raised against purinergic receptor P2Y2 (P2RY2), a GPCR, behaves like a partial agonist to unliganded receptor, whereas it exhibits a positive allosteric modulator (PAM) activity to liganded receptor. We demonstrate the validity of our aptamer screening method targeting VLP-stabilized GPCR and a unique aptamer with dual function, agonist and PAM, for GPCR, depending on whether the intrinsic ligand is prebound to the receptor.

G protein–coupled receptors (GPCRs) play diverse roles in physiological processes, and hence the ligands to modulate GPCRs have served as important molecules in biological and pharmacological approaches. However, the exploration of novel ligands for GPCR still remains an arduous challenge. In this study, we report a method for the discovery of nucleic acid ligands against GPCRs by an advanced RNA aptamer screening technology that employs a virus-like particle (VLP), exposing the GPCR of interest. An array of biochemical analyses coupled with a cell-based assay revealed that one of the aptamers raised against purinergic receptor P2Y2 (P2RY2), a GPCR, exhibits an activation potency to unliganded receptor and prohibits a further receptor activation by endogenous ligand, behaving like a partial agonist. However, the aptamer enhances the activity of intrinsic ligand-binding P2RY2, thereby acting as a positive allosteric modulator (PAM) to liganded receptor. Our findings demonstrate that the nucleic acid aptamer conditionally exerts PAM and agonist effects on GPCRs, depending on their intrinsic ligand binding state. These results indicate the validity of our VLP-based aptamer screening targeting GPCR and reemphasize the great potential of nucleic acid ligands for exploring the GPCR activation mechanism and therapeutic applications.

Considering both small and large scale motions of vascular endothelial growth factor (VEGF) is crucial for reliably predicting its binding affinities to DNA aptamers

Considering both small and large scale motions of VEGF is crucial to predict its relative binding affinities to DNA aptamer variants with docking.

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.

De novo post-SELEX optimization of a G-quadruplex DNA aptamer binding to marine toxin gonyautoxin 1/4

Ligand-binding aptamers obtained by SELEX (Systematic Evolution of Ligands by EXponential enrichment) often have low affinity or/and specificity, and post-SELEX optimization is usually needed. Due to experimental difficulty in determining three-dimensional (3D) structures of aptamer-ligand complexes, there are few structure-guided methods for rational post-SELEX optimization. Here, we employed a de novo optimization approach to engineer high-affinity variants for a G-quadruplex (GQ) aptamer (GO18-T-d) that specifically binds to marine toxin gonyautoxin 1/4 (GTX1/4). First, temperature-dependent modeling was carried out to predict the atomic structure of GO18-T-d. Then, to identify key bases for the optimization, spontaneous binding simulations were performed to reveal the complex structure of GO18-T-d with GTX1/4. Finally, binding energy analysis was conducted to evaluate the designed variants for high affinity. We predicted that GO18-T-d has the typical parallel GQ topology, consistent with circular dichroism (CD) measurements. Our simulations showed that the 5′-end of GO18-T-d hinders the GTX1/4 movement toward the binding pocket, leading to a designed variant that removes the first 5 nucleotides at the 5′-end. Microscale thermophoresis (MST) experiments verified that the binding affinity of the engineered aptamer increases by ~20 folds. Thus, this study not only provides a high-affinity variant of GO18-T-d, but also suggests that our computational approach is useful for the structure-guided optimization of GQ aptamers.

Nucleic acid therapeutics: a focus on the development of aptamers

INTRODUCTION

Aptamers provide exciting opportunities for the development of specific and targeted therapeutic approaches.

AREAS COVERED

In this review, the authors discuss different therapeutic options available with nucleic acids, including aptamers, focussing on similarities and differences between them. The authors concentrate on case studies with specific aptamers, which exemplify their distinct advantages. The reasons for failure, wherever available, are deliberated upon. Attempts to accelerate the in vitro selection process have been discussed. Challenges with aptamers in terms of their specificity and targeted delivery and strategies to overcome these are described. Examples of precise regulation of systemic half-life of aptamers using antidotes are discussed.

EXPERT OPINION

Despite their nontoxic nature, a variety of reasons limit the therapeutic potential of aptamers in the clinic. The analysis of adverse effects observed with the pegnivacogin/anivamersen pair has highlighted the need to screen for preexisting PEG antibodies in any clinical trial involving pegylated molecules. Surprisingly, and promisingly, the ability of nucleic acid therapeutics to breach the blood brain barrier seems achievable. The recognition of specific motifs, e.g. G-quadruplex in thrombin-binding aptamers, or a 'nucleation' zone while designing aptamer-antidote pairs, is likely to accelerate the discovery of therapeutically efficacious molecules.