Structural Insights into the Osteopontin-Aptamer Complex by Molecular Dynamics Simulations

Analysis of aptamer-target binding and molecular mechanisms by thermofluorimetric analysis and molecular dynamics simulation

Introduction: Aptamers are valuable for bioassays, but aptamer-target binding is susceptible to reaction conditions. In this study, we combined thermofluorimetric analysis (TFA) and molecular dynamics (MD) simulations to optimize aptamer-target binding, explore underlying mechanisms and select preferred aptamer. Methods: Alpha-fetoprotein (AFP) aptamer AP273 (as the model) was incubated with AFP under various experimental conditions, and melting curves were measured in a real-time PCR system to select the optimal binding conditions. The intermolecular interactions of AP273-AFP were analysed by MD simulations with these conditions to reveal the underlying mechanisms. A comparative study between AP273 and control aptamer AP-L3-4 was performed to validate the value of combined TFA and MD simulation in selecting preferred aptamers. Results: The optimal aptamer concentration and buffer system were easily determined from the dF/dT peak characteristics and the melting temperature (Tm) values on the melting curves of related TFA experiments, respectively. A high Tm value was found in TFA experiments performed in buffer systems with low metal ion strength. The molecular docking and MD simulation analyses revealed the underlying mechanisms of the TFA results, i.e., the binding force and stability of AP273 to AFP were affected by the number of binding sites, frequency and distance of hydrogen bonds, and binding free energies; these factors varied in different buffer and metal ion conditions. The comparative study showed that AP273 was superior to the homologous aptamer AP-L3-4. Conclusion: Combining TFA and MD simulation is efficient for optimizing the reaction conditions, exploring underlying mechanisms, and selecting aptamers in aptamer-target bioassays.

Metal Ion Binding in Wild-Type and Mutated Frataxin: A Stability Study

This work studies the stability of wild-type frataxin and some of its variants found in cancer tissues upon Co2+ binding. Although the physiologically involved metal ion in the frataxin enzymatic activity is Fe2+, as it is customarily done, Co2+ is most often used in experiments because Fe2+ is extremely unstable owing to the fast oxidation reaction Fe2+ → Fe3+. Protein stability is monitored following the conformational changes induced by Co2+ binding as measured by circular dichroism, fluorescence spectroscopy, and melting temperature measurements. The stability ranking among the wild-type frataxin and its variants obtained in this way is confirmed by a detailed comparative analysis of the XAS spectra of the metal-protein complex at the Co K-edge. In particular, a fit to the EXAFS region of the spectrum allows positively identifying the frataxin acidic ridge as the most likely location of the metal-binding sites. Furthermore, we can explain the surprising feature emerging from a detailed analysis of the XANES region of the spectrum, showing that the longer 81-210 frataxin fragment has a smaller propensity for Co2+ binding than the shorter 90-210 one. This fact is explained by the peculiar role of the N-terminal disordered tail in modulating the protein ability to interact with the metal.

Aggregates Sealed by Ions

The chapter draws a line connecting some recent results where the role of ions is found essential in sealing more or less pre-organized assemblies of macromolecules. We draw some dots along the line that starts from the effect of the ionic atmosphere and ends with the chemical bonds formed by multivalent ions acting as bridges between macromolecules. Many of these dots involve structurally disordered peptides and disordered regions of proteins. A broad perspective of the role of multivalent ions in assisting the assembly process, shifting population in polymorphic states, and sealing protein aggregates, is suggested.

Study on the binding mode of aptamer to ampicillin and its electrochemical response behavior in two different reaction media

A study was carried out to investigate the binding mode of aptamer to ampicillin (AMP) and its electrochemical response behavior. The binding mode was confirmed using the molecular dynamics (MD) simulation method to obtain the corresponding binding dynamic change process. Following the confirmed binding mode, a qualitative elucidation was provided on the electrochemical response characteristics of a single-probe aptamer-based folding sensor. The results show that there exist two different binding modes in two different solution systems, Phys2 and H₂O (0.1 M NaCl). These two binding modes can respectively induce two different contraction changes, thereby driving the methylene blue (MB)-modified aptamer probe to show a "close-to-interface" convergence behavior with different degrees on the actual electrode surface, which validates two apparently different electrochemical response behavior characteristics of "signal-on" for the sensor. By contrast, H₂O (0.1 M NaCl) as the reaction medium is more conducive to the formation of a stable aptamer/AMP complex and the development of a high-sensitivity analytical method with a low detection limit of 0.033 μM. The simulation results effectively support the experimental results, which is helpful in gaining a deeper understanding of the relationship between the signaling mechanism and practical analytical performance for aptamer-based folding sensors at the molecular level.

Osteopontin - A potential biomarker of advanced liver disease

Cirrhosis is a primary cause of liver-related mortality and morbidity. The basic process driving chronic liver disease to cirrhosis is accelerated fibrogenesis. Although the pathogenesis of liver cirrhosis is a multifactorial process, the essential step in the evolution of liver fibrosis is the activation of hepatic stellate cells, which are the main source of collagen produced in the extracellular matrix. This activation process is mediated by multiple growth factors, cytokines, and chemokines. One of the hepatic stellate cell-activating signaling molecules (and also one associated with cell injury and fibrosis) is osteopontin (OPN). OPN concentration in the plasma has been found to be predictive of liver fibrosis in various liver diseases. OPN concentrations correlate significantly with the stage of fibrosis, liver insufficiency, portal hypertension, and the presence of hepatocellular cancer. However, due to its versatile signaling functions, OPN not only contributes to the development of liver cirrhosis, but is also implicated in the pathogenesis of other chronic hepatic diseases such as viral hepatitis, both alcoholic and non-alcoholic steatohepatitis, drug-induced liver injury, and hepatocellular cancer. Thus, the targeting of OPN pathways seems to be a promising approach in the treatment of chronic liver diseases.

Structural and functional analysis of the simultaneous binding of two duplex/quadruplex aptamers to human α-thrombin

The long-range communication between the two exosites of human α-thrombin (thrombin) tightly modulates the protein-effector interactions. Duplex/quadruplex aptamers represent an emerging class of very effective binders of thrombin. Among them, NU172 and HD22 aptamers are at the forefront of exosite I and II recognition, respectively. The present study investigates the simultaneous binding of these two aptamers by combining a structural and dynamics approach. The crystal structure of the ternary complex formed by the thrombin with NU172 and HD22_27mer provides a detailed view of the simultaneous binding of these aptamers to the protein, inspiring the design of novel bivalent thrombin inhibitors. The crystal structure represents the starting model for molecular dynamics studies, which point out the cooperation between the binding at the two exosites. In particular, the binding of an aptamer to its exosite reduces the intrinsic flexibility of the other exosite, that preferentially assumes conformations similar to those observed in the bound state, suggesting a predisposition to interact with the other aptamer. This behaviour is reflected in a significant increase of the anticoagulant activity of NU172 when the inactive HD22_27mer is bound to exosite II, providing a clear evidence of the synergic action of the two aptamers.

Divalent Cation Dependence Enhances Dopamine Aptamer Biosensing

Oligonucleotide receptors (aptamers), which change conformation upon target recognition, enable electronic biosensing under high ionic-strength conditions when coupled to field-effect transistors (FETs). Because highly negatively charged aptamer backbones are influenced by ion content and concentration, biosensor performance and target sensitivities were evaluated under application conditions. For a recently identified dopamine aptamer, physiological concentrations of Mg²⁺ and Ca²⁺ in artificial cerebrospinal fluid produced marked potentiation of dopamine FET-sensor responses. By comparison, divalent cation-associated signal amplification was not observed for FET sensors functionalized with a recently identified serotonin aptamer or a previously reported dopamine aptamer. Circular dichroism spectroscopy revealed Mg²⁺- and Ca²⁺-induced changes in target-associated secondary structure for the new dopamine aptamer, but not the serotonin aptamer nor the old dopamine aptamer. Thioflavin T displacement corroborated the Mg²⁺ dependence of the new dopamine aptamer for target detection. These findings imply allosteric binding interactions between divalent cations and dopamine for the new dopamine aptamer. Developing and testing sensors in ionic environments that reflect intended applications are best practices for identifying aptamer candidates with favorable attributes and elucidating sensing mechanisms.

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

Nucleic acid aptamers hold great promise for therapeutic applications due to their favorable intrinsic properties, as well as high-throughput experimental selection techniques. Despite the utility of the systematic evolution of ligands by the exponential enrichment (SELEX) method for aptamer determination, complementary in silico aptamer design is highly sought after to facilitate virtual screening and increased understanding of important nucleic acid-protein interactions. Here, with a combined experimental and theoretical approach, we have developed two optimal epithelial cellular adhesion molecule (EpCAM) aptamers. Our structure-based in silico method first predicts their binding modes and then optimizes them for EpCAM with molecular dynamics simulations, docking, and free energy calculations. Our isothermal titration calorimetry experiments further confirm that the EpCAM aptamers indeed exhibit enhanced affinity over a previously patented nanomolar aptamer, EP23. Moreover, our study suggests that EP23 and the de novo designed aptamers primarily bind to EpCAM dimers (and not monomers, as hypothesized in previous published works), suggesting a paradigm for developing EpCAM-targeted therapies.

In Silico Design of Novel Mutant Anti-MUC1 Aptamers for Targeted Cancer Therapy

The transmembrane glycoprotein mucin 1 (MUC1) is an attractive tumor marker for cancer therapy and diagnosis. The nine amino acid extracellular epitope APDTRPAPG of this protein is selectively recognized by the S2.2 single-stranded DNA anti-MUC1 aptamer, which has emerged as a promising template for designing novel targeting agents for MUC1-directed therapy. In this work, 100 ns molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, and conformational analysis were employed to propose a novel prospective anti-MUC1 aptamer with increased affinity toward the MUC1 epitope resulting from the double mutation of the T11 and T12 residues with PSU and U nucleosides, respectively. The double mutant aptamer exhibits a tight interaction with the MUC1 epitope and adopts a groove conformation that structurally favors the intermolecular contact with the epitope through the intermediate T11-A18 region leaving the 3' and 5' ends free for further chemical conjugation with a nanocarrier or pharmaceutical. These results are valuable to gain understanding about the molecular features governing aptamer-epitope interactions and constitute a first key step for the design of novel aptamer-based nanocarriers for MUC1-targeted cancer therapy.

Computational Approaches in Theranostics: Mining and Predicting Cancer Data

The ability to understand the complexity of cancer-related data has been prompted by the applications of (1) computer and data sciences, including data mining, predictive analytics, machine learning, and artificial intelligence, and (2) advances in imaging technology and probe development. Computational modelling and simulation are systematic and cost-effective tools able to identify important temporal/spatial patterns (and relationships), characterize distinct molecular features of cancer states, and address other relevant aspects, including tumor detection and heterogeneity, progression and metastasis, and drug resistance. These approaches have provided invaluable insights for improving the experimental design of therapeutic delivery systems and for increasing the translational value of the results obtained from early and preclinical studies. The big question is: Could cancer theranostics be determined and controlled in silico? This review describes the recent progress in the development of computational models and methods used to facilitate research on the molecular basis of cancer and on the respective diagnosis and optimized treatment, with particular emphasis on the design and optimization of theranostic systems. The current role of computational approaches is providing innovative, incremental, and complementary data-driven solutions for the prediction, simplification, and characterization of cancer and intrinsic mechanisms, and to promote new data-intensive, accurate diagnostics and therapeutics.

Molecular Modeling Applied to Nucleic Acid-Based Molecule Development

Molecular modeling by means of docking and molecular dynamics (MD) has become an integral part of early drug discovery projects, enabling the screening and enrichment of large libraries of small molecules. In the past decades, special emphasis was drawn to nucleic acid (NA)-based molecules in the fields of therapy, diagnosis, and drug delivery. Research has increased dramatically with the advent of the SELEX (systematic evolution of ligands by exponential enrichment) technique, which results in single-stranded DNA or RNA sequences that bind with high affinity and specificity to their targets. Herein, we discuss the role and contribution of docking and MD to the development and optimization of new nucleic acid-based molecules. This review focuses on the different approaches currently available for molecular modeling applied to NA interaction with proteins. We discuss topics ranging from structure prediction to docking and MD, highlighting their main advantages and limitations and the influence of flexibility on their calculations.