Molecular Dynamics Simulation of a RNA Aptasensor

In Silico Design of a Solution-Gated Graphene Transistor Sensor for the Efficient Detection of Guanine Quadruplexes

Guanine quadruplexes (G4s) are nucleic acid structures present in diverse regions of the genome, such as telomeres and transcription initiators. Recently, the different biological roles of G4s have been evidenced as well as their role as biomarkers for tumors or viral infections. However, the fast and efficient detection of G4s in complex matrices remains elusive. In this contribution, by using long-scale molecular dynamics simulations, we propose the design of a biosensor based on organic field-effect transistors recognizing G4s. In particular, we show that the interaction of the G4s with the biosensor is translated into a change in the charge density profile, which correlates with the electrical transduction of the signal, thus allowing the detection of the nucleic acid structure. We also provide rules of thumb for the optimization of the design of the device and more generally for the integration of computationally driven design approaches.

Dynamic simulation and experimental studies of molecularly imprinted label-free sensor for determination of milk quality marker

Bovine serum albumin (BSA) has emerged as a biomarker for mammary gland health and cow quality, being recognized as a significant allergenic protein. In this study, a novel flexible molecular imprinted electrochemical sensor by surface electropolymerization using pyrrole (Py) as functional monomer, which can be better applied to the detection of milk quality marker BSA. Based on computational results, with regard to all polypyrrole (PPy) conformations and amino-acid positions within the protein, the BSA molecule remained firmly embedded into PPy polymers with no biological changes. The molecular imprinted electrochemical sensor displayed a broad linear detection range from 1.0 × 10-4 to 50 ng·mL-1 (R2 = 0.995) with a low detection limit (LOD) of 4.5 × 10-2 pg·mL-1. Additionally, the sensor was highly selective, reproducible, stable and recoverable, suggesting that it might be utilized for the evaluation of milk quality.

In silico selection of aptamers for bacterial toxins detection

The most commonly used toxins in biological warfare are staphylococcal enterotoxin B (3SEB), cholera toxin (1XTC), and botulinum toxin (3BTA). Uncovering novel strategies for identifying these toxins is paramount; therefore, aptamers are used for this purpose. Aptamers are single-stranded DNA or RNA oligonucleotides selected via Systematic Evolution of Ligands by Exponential Enrichment (SELEX) with high binding affinity and specificity against target molecules. However, SELEX in vitro is tedious; hence, adopting alternative in silico molecular docking approaches is necessary. We aimed to conduct molecular docking with accessible tools and obtain RNA aptamers. First, 4,820,095 sequences obtained from an initial library of 9.5 × 109 Python script sequences were used. The GraphClust program was used to create representative groups or clusters, and the DoGSiteScorer (https://proteins.plus/) was used to conduct binding site detection of the proteins: 5DO4 (thrombin), 3SEB, 1XTC, and 3BTA. rDock, HDock, and PatchDock were adopted, combining different docking program results (consensus scoring), to improve receptor-ligand prediction. An analysis of the poses and root mean square deviation (RMSD) was performed, and 468 structurally different aptamers were obtained. The DoGSiteScorer program predicted the binding site of each protein to direct the interaction with the aptamer. Candidate aptamers for 3SEB, 1XTC, and 3BTA were selected according to the pose value considering the closeness of the interaction with a lower mean of 45.923 Å, 45.854 Å, and 72.490 Å, respectively.Communicated by Ramaswamy H. Sarma.

DockSurf: A Molecular Modeling Software for the Prediction of Protein/Surface Adhesion

The elucidation of structural interfaces between proteins and inorganic surfaces is a crucial aspect of bionanotechnology development. Despite its significance, the interfacial structures between proteins and metallic surfaces are yet to be fully understood, and the lack of experimental investigation has impeded the development of many devices. To overcome this limitation, we suggest considering the generation of protein/surface structures as a molecular docking problem with a homogenous plan as the target. To this extent, we propose a new software, DockSurf, which aims to quickly propose reliable protein/surface structures. Our approach considers the conformational exploration with Euler's angles, which provide a cartography instead of a unique structure. Interaction energies were derived from quantum mechanics computations for a set of small molecules that describe protein atom types and implemented in a Derjaguin, Landau, Verwey, and Overbeek potential for the consideration of large systems such as proteins. The validation of DockSurf software was conducted with molecular dynamics for corona proteins with gold surfaces and provided enthusiastic results. This software is implemented in the RPBS platform to facilitate widespread access to the scientific community.

Computational Biomaterials: Computational Simulations for Biomedicine

With the flourishing development of material simulation methods (quantum chemistry methods, molecular dynamics, Monte Carlo, phase field, etc.), extensive adoption of computing technologies (high-throughput, artificial intelligence, machine learning, etc.), and the invention of high-performance computing equipment, computational simulation tools have sparked the fundamental mechanism-level explorations to predict the diverse physicochemical properties and biological effects of biomaterials and investigate their enormous application potential for disease prevention, diagnostics, and therapeutics. Herein, the term "computational biomaterials" is proposed and the computational methods currently used to explore the inherent properties of biomaterials, such as optical, magnetic, electronic, and acoustic properties, and the elucidation of corresponding biological behaviors/effects in the biomedical field are summarized/discussed. The theoretical calculation of the physiochemical properties/biological performance of biomaterials applied in disease diagnosis, drug delivery, disease therapeutics, and specific paradigms such as biomimetic biomaterials is discussed. Additionally, the biosafety evaluation applications of theoretical simulations of biomaterials are presented. Finally, the challenges and future prospects of such computational simulations for biomaterials development are clarified. It is anticipated that these simulations would offer various methodologies for facilitating the development and future clinical translations/utilization of versatile biomaterials.

Inspirations of Biomimetic Affinity Ligands: A Review

Affinity chromatography is a well-known method dependent on molecular recognition and is used to purify biomolecules by mimicking the specific interactions between the biomolecules and their substrates. Enzyme substrates, cofactors, antigens, and inhibitors are generally utilized as bioligands in affinity chromatography. However, their cost, instability, and leakage problems are the main drawbacks of these bioligands. Biomimetic affinity ligands can recognize their target molecules with high selectivity. Their cost-effectiveness and chemical and biological stabilities make these antibody analogs favorable candidates for affinity chromatography applications. Biomimetics applies to nature and aims to develop nanodevices, processes, and nanomaterials. Today, biomimetics provides a design approach to the biomimetic affinity ligands with the aid of computational methods, rational design, and other approaches to meet the requirements of the bioligands and improve the downstream process. This review highlighted the recent trends in designing biomimetic affinity ligands and summarized their binding interactions with the target molecules with computational approaches.

Between Two Walls: Modeling the Adsorption Behavior of β-Glucosidase A on Bare and SAM-Functionalized Gold Surfaces

The efficient immobilization of enzymes on surfaces remains a complex but central issue in the biomaterials field, which requires us to understand this process at the atomic level. Using a multiscale approach combining all-atom molecular dynamics and coarse-grain Brownian dynamics simulations, we investigated the adsorption behavior of β-glucosidase A (βGA) on bare and self-assembled monolayer (SAM)-functionalized gold surfaces. We monitored the enzyme position and orientation during the molecular dynamics (MD) trajectories and measured the contacts it forms with both surfaces. While the adsorption process has little impact on the protein conformation, it can nonetheless perturb its mechanical properties and catalytic activity. Our results show that compared to the SAM-functionalized surface, the adsorption of βGA on bare gold is more stable, but less specific, and more likely to disrupt the enzyme's function. This observation emphasizes the fact that the structural organization of proteins at the solid interface is a key point when designing devices based on enzyme immobilization, as one must find an acceptable stability-activity trade-off.

Atomistic Simulations of Functionalized Nano-Materials for Biosensors Applications

Nanoscale biosensors, a highly promising technique in clinical analysis, can provide sensitive yet label-free detection of biomolecules. The spatial and chemical specificity of the surface coverage, the proper immobilization of the bioreceptor as well as the underlying interfacial phenomena are crucial elements for optimizing the performance of a biosensor. Due to experimental limitations at the microscopic level, integrated cross-disciplinary approaches that combine in silico design with experimental measurements have the potential to present a powerful new paradigm that tackles the issue of developing novel biosensors. In some cases, computational studies can be seen as alternative approaches to assess the microscopic working mechanisms of biosensors. Nonetheless, the complex architecture of a biosensor, associated with the collective contribution from "substrate-receptor-analyte" conjugate in a solvent, often requires extensive atomistic simulations and systems of prohibitive size which need to be addressed. In silico studies of functionalized surfaces also require ad hoc force field parameterization, as existing force fields for biomolecules are usually unable to correctly describe the biomolecule/surface interface. Thus, the computational studies in this field are limited to date. In this review, we aim to introduce fundamental principles that govern the absorption of biomolecules onto functionalized nanomaterials and to report state-of-the-art computational strategies to rationally design nanoscale biosensors. A detailed account of available in silico strategies used to drive and/or optimize the synthesis of functionalized nanomaterials for biosensing will be presented. The insights will not only stimulate the field to rationally design functionalized nanomaterials with improved biosensing performance but also foster research on the required functionalization to improve biomolecule-surface complex formation as a whole.

Molecular dynamics simulation study of gold nanosheet as drug delivery vehicles for anti-HIV-1 aptamers

The adsorption process of three aptamers with gold nanosheet (GNS) as a drug carrier has been investigated with the help of molecular dynamics simulations. The sequencing of the considered aptamers are as (CUUCAUUGUAACUUCUCAUAAUUUCCCGAGGCUUUUACUUUCGGGGUCCU) and (CCGGGUCGUCCCCUACGGGGACUAAAGACUGUGUCCAACCGCCCUCGCCU) for AP1 and AP2, respectively. AP3 is a muted version of AP1 in which nucleotide positions 4, 6, 18, 28 and 39 have C4A, U6G, A18G, G28A, and U39C mutations. At positions 24, and 40, a deletion mutation is seen to eliminate U24 and U40 bases. These aptamers are inhibitors for HIV-1 protease and can be candidates as potential pharmaceutics for treatment of AIDS in the future. The interactions between considered aptamers and GNS have been analyzed in detail with help of structural and energetic properties. These analyses showed that all three aptamers could well adsorb on GNS. Overall, the final results show that the adsorption of AP2 on the GNS is more favorable than other considered ones and consequently GNS can be considered as a device in order to immobilize these aptamers.

Transferable Gaussian Attractive Potentials for Organic/Oxide Interfaces

Organic/oxide interfaces play an important role in many areas of chemistry and in particular for lubrication and corrosion. Molecular dynamics simulations are the method of choice for providing complementary insight to experiments. However, the force fields used to simulate the interaction between molecules and oxide surfaces tend to capture only weak physisorption interactions, discarding the stabilizing Lewis acid/base interactions. We here propose a simple complement to the straightforward molecular mechanics description based on "out-of-the-box" Lennard-Jones potentials and electrostatic interactions: the addition of an attractive Gaussian potential between reactive sites of the surface and heteroatoms of adsorbed organic molecules, leading to the Gaussian Lennard-Jones (GLJ) potential. The interactions of four oxygenated and four amine molecules with the typical and widespread hematite and γ-alumina surfaces are investigated. The root mean square deviation (RMSD) for all probed molecules is only 5.7 kcal/mol, which corresponds to an error of 23% over hematite. On γ-alumina, the RMSD is 11.2 kcal/mol using a single parameter for all five chemically inequivalent surface aluminum atoms. Applying GLJ to the simulation of organic films on oxide surfaces demonstrates that the mobility of the surfactants is overestimated by the simplistic LJ potential, while GLJ and other qualitatively correct potentials show a strong structuration and slow dynamics of the surface films, as could be expected from the first-principles adsorption energies for model head groups.

Theoretical and Experimental Elucidation of the Adsorption Process of a Bioinspired Peptide on Mineral Surfaces

Inorganic materials used for biomedical applications such as implants generally induce the adsorption of proteins on their surface. To control this phenomenon, the bioinspired peptidomimetic polymer 1 (PMP1), which aims to reproduce the adhesion of mussel foot proteins, is commonly used to graft specific proteins on various surfaces and to regulate the interfacial mechanism. To date and despite its wide application, the elucidation at the atomic scale of the PMP1 mechanism of adsorption on surfaces is still unknown. The purpose of the present work was thus to unravel this process through experimental and computational investigations of adsorption of PMP1 on gold, TiO₂, and SiO₂ surfaces. A common mechanism of adsorption is identified for the adsorption of PMP1 which emphasizes the role of electrostatics to approach the peptide onto the surface followed by a full adhesion process where the entropic desolvation step plays a key role. Besides, according to the fact that mussel naturally controls the oxidation states of its proteins, further investigations were performed for two distinct redox states of PMP1, and we conclude that even if both states are able to allow interaction of PMP1 with the surfaces, the oxidation of PMP1 leads to a stronger interaction.

Computational Studies of a DNA-Based Aptasensor: toward Theory-Driven Transduction Improvement

Aptamers are a class of bioreceptors intensively used in current analytical tools dedicated to molecular diagnostics due to their ability to perform large structural reorganization upon target binding. However, there is a lack of methodologies allowing us to rationalize their structure in order to improve the transduction efficiency in aptamer sensors. We choose here, as a model system, a three-strand DNA structure as the probe, composed of two DNA strands anchored on a gold surface and partially hybridized with an aptamer sequence sensitive to ampicillin (AMP). The DNA structure has been designed to show strong structural change upon AMP binding to its aptamer. Using a set of computational techniques including molecular dynamics simulations, we deeply investigated the structure change upon analyte binding, taking into account the grafting on the surface. Original analyses of ion distributions along the trajectories unveil a distinct pattern between both states which can be related to changes in capacitance of the interface between these states. To our knowledge, this work demonstrates the ability of computational investigations for the first time to drive, in silico, the design of aptasensors.

De novo ssRNA Aptamers against the SARS-CoV-2 Main Protease: In Silico Design and Molecular Dynamics Simulation

Herein, we have generated ssRNA aptamers to inhibit SARS-CoV-2 M^pro, a protease necessary for the SARS-CoV-2 coronavirus replication. Because there is no aptamer 3D structure currently available in the databanks for this protein, first, we modeled an ssRNA aptamer using an entropic fragment-based strategy. We refined the initial sequence and 3D structure by using two sequential approaches, consisting of an elitist genetic algorithm and an RNA inverse process. We identified three specific aptamers against SARS-CoV-2 M^pro, called MApta^pro, MApta^pro-IR1, and MApta^pro-IR2, with similar 3D conformations and that fall in the dimerization region of the SARS-CoV-2 M^pro necessary for the enzymatic activity. Through the molecular dynamic simulation and binding free energy calculation, the interaction between the MApta^pro-IR1 aptamer and the SARS-CoV-2 M^pro enzyme resulted in the strongest and the highest stable complex; therefore, the ssRNA MApta^pro-IR1 aptamer was selected as the best potential candidate for the inhibition of SARS-CoV-2 M^pro and a perspective therapeutic drug for the COVID-19 disease.

Effects of the Chemical and Structural Properties of Silane Monolayers on the Organization of Water Molecules and Ions at Interfaces, from Molecular Dynamics Simulations

Understanding the organization of the hydration layer at functionalized silica surfaces is relevant for a large range of biosensing applications or surface phenomena such as biomolecule adsorption. Silane monolayers are widely used to functionalize silica surfaces. Using molecular dynamics simulations, we have investigated the role of silane molecule head-group charge, alkyl chain length, and surface coverage in the structural organization and dynamic properties of Na⁺ ions, Cl^- ions, and water molecules at the interface. The silane molecules studied are 3-aminopropyldimethylethoxysilane, n-propyldimethylmethoxysilane, octadecyldimethylmethoxysilane, and (dimethylamino)dimethylsilylundecanoate. Our results suggest that the distribution of interfacial ions is sensitive to the 2D dispersion of the silane-charged head groups. Also, while charged silane monolayers show a strong orientation of interfacial water molecules, which leads to a rupture in the hydrogen bond network and disturbs their tetrahedral organization, the arrangement of water molecules at the interface with uncharged silane monolayers seems to be related to the surface roughness and to alkyl chain length. In line with these results, the diffusion of ions and water molecules is higher at the CH₃ long monolayer interface than at the CH₃ short monolayer interface and at the charged monolayer interfaces. Also, whatever the silane molecules studied, bulk properties are recovered around 0.7 nm above the interface. The interfacial water organization is known to impact biomolecule adsorption. Therefore, these results could further help in optimizing the functionalization layers to capture analytes.

Atomistic simulations of gold surface functionalization for nanoscale biosensors applications

A wide class of biosensors can be built via functionalization of gold surface with proper bio conjugation element capable of interacting with the analyte in solution, and the detection can be performed either optically, mechanically or electrically. Any change in physico-chemical environment or any slight variation in mass localization near the surface of the sensor can cause differences in nature of the transduction mechanism. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection of the analyte. Here, we employ molecular modeling techniques to assist the optimization of a gold-surface biosensor. The gold surface of a quartz-crystal-microbalance sensor is functionalized using polymeric chains of poly(ethylene glycol) (PEG) of 2 KDa molecular weight, which is an inert long chain amphiphilic molecule, supporting biotin molecules (bPEG) as the ligand molecules for streptavidin analyte. The PEG linkers are immobilized onto the gold surface through sulphur chemistry. Four gold surfaces with different PEG linker density and different biotinylation ratio between bPEG and PEG, are investigated by means of state-of-the art atomistic simulations and compared with available experimental data. Results suggest that the amount of biotin molecules accessible for the binding with the protein increases upon increasing the linkers density. At the high density a 1:1 ratio of bPEG/PEG can further improve the accessibility of the biotin ligand due to a strong repulsion between linker chains and different degree of hydrophobicity between bPEG and PEG linkers. The study provides a computaional protocol to model sensors at the level of single molecular interactions, and for optimizing the physical properties of surface conjugated ligand which is crucial to enhance output of the sensor.

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.

Molecular dynamics study of the recognition of ATP by nucleic acid aptamers

Despite their great success in recognizing small molecules in vitro, nucleic acid aptamers are rarely used in clinical settings. This is partially due to the lack of structure-based mechanistic information. In this work, atomistic molecular dynamics simulations are used to study the static and dynamic supramolecular structures relevant to the process of the wild-type (wt) nucleic acid aptamer recognition and binding of ATP. The effects brought about by mutation of key residues in the recognition site are also explored. The simulations reveal that the aptamer displays a high degree of rigidity and is structurally very little affected by the binding of ATP. Interaction energy decomposition shows that dispersion forces from π-stacking between ATP and the G6 and A23 nucleobases in the aptamer binding site plays a more important role in stabilizing the supramolecular complex, compared to hydrogen-bond interaction between ATP and G22. Moreover, metadynamics simulations show that during the association process, water molecules act as essential bridges connecting ATP with G22, which favors the dynamic stability of the complex. The calculations carried out on three mutated aptamer structures confirm the crucial role of the hydrogen bonds and π-stacking interactions for the binding affinity of the ATP nucleic acid aptamer.

Impact of Silane Monolayers on the Adsorption of Streptavidin on Silica and Its Subsequent Interactions with Biotin: Molecular Dynamics and Steered Molecular Dynamics Simulations

Protein adsorption on surfaces is used in analytical tools as an immobilization mean to trap the analyte to be detected. However, protein adsorption can lead to a conformational change in the protein structure, resulting in a loss of bioactivity. Here, we study adsorption of a streptavidin-biotin complex on amorphous SiO₂ surfaces functionalized with five different silane self-assembled monolayers by all-atom molecular dynamics simulations. We find that the streptavidin global conformational change, as well as the nature of residues with high mobility, depends on the alkyl chain length and head-group charge of silane molecules. Effects on interactions with biotin are further investigated by steered molecular dynamics (SMD) simulations, which mimics atomic force microscopy (AFM) with the biotin attached on the tip. We show the combined effects of adsorption-induced global conformational changes and of the position of residues with high mobility on the streptavidin-biotin rupture force. By comparing our results to experimental and SMD rupture forces obtained in water, without any surface, we conclude that silane with uncharged and short alkyl chains allows streptavidin immobilization, while keeping biotin interactions better than silanes with long alkyl chains or charged head groups.

In Vitro interaction between yeast frataxin and superoxide dismutases: Influence of mitochondrial metals

BACKGROUND

Friedreich's ataxia results from a decreased expression of the nuclear gene encoding the mitochondrial protein, frataxin. Frataxin participates in the biosynthesis of iron-sulfur clusters and heme cofactors, as well as in iron storage and protection against oxidative stress. How frataxin interacts with the antioxidant defence components is poorly understood.

METHODS

Therefore, we have investigated by kinetic, thermodynamic and modelling approaches the molecular interactions between yeast frataxin (Yfh1) and superoxide dismutases, Sod1 and Sod2, and the influence of Yfh1 on their enzymatic activities.

RESULTS

Yfh1 interacts with cytosolic Sod1 with a dissociation constant, Kd = 1.3 ± 0.3 μM, in two kinetic steps. The first step occurs in the 200 ms range and corresponds to the Yfh1-Sod1 interaction, whereas the second is slow and is assumed to be a change in the conformation of the protein-protein adduct. Furthermore, computational investigations confirm the stability of the Yfh1-Sod1 complex. Yfh1 forms two protein complexes with mitochondrial Sod2 with 1:1 and 2:1 Yfh1/Sod2 stoichiometry (Kd1 = 1.05 ± 0.05 and Kd2 = 6.6 ± 0.1 μM). Furthermore, Yfh1 increases the enzymatic activity of Sod1 while slightly affecting that of Sod2. Finally, the stabilities of the protein-protein adducts and the effect of Yfh1 on superoxide dismutase activities depend on the nature of the mitochondrial metal.

CONCLUSIONS

This work confirms the participation of Yfh1 in cellular defence against oxidative stress.

Detailed Analysis of 17β-Estradiol-Aptamer Interactions: A Molecular Dynamics Simulation Study

Micro-pollutants such as 17β-Estradiol (E2) have been detected in different water resources and their negative effects on the environment and organisms have been observed. Aptamers are established as a possible detection tool, but the underlying ligand binding is largely unexplored. In this study, a previously described 35-mer E2-specific aptamer was used to analyse the binding characteristics between E2 and the aptamer with a MD simulation in an aqueous medium. Because there is no 3D structure information available for this aptamer, it was modeled using coarse-grained modeling method. The E2 ligand was positioned inside a potential binding area of the predicted aptamer structure, the complex was used for an 25 ns MD simulation, and the interactions were examined for each time step. We identified E2-specific bases within the interior loop of the aptamer and also demonstrated the influence of frequently underestimated water-mediated hydrogen bonds. The study contributes to the understanding of the behavior of ligands binding with aptamer structure in an aqueous solution. The developed workflow allows generating and examining further appealing ligand-aptamer complexes.

Thermotropic Liquid Crystal-Assisted Chemical and Biological Sensors

In this review article, we analyze recent progress in the application of liquid crystal-assisted advanced functional materials for sensing biological and chemical analytes. Multiple research groups demonstrate substantial interest in liquid crystal (LC) sensing platforms, generating an increasing number of scientific articles. We review trends in implementing LC sensing techniques and identify common problems related to the stability and reliability of the sensing materials as well as to experimental set-ups. Finally, we suggest possible means of bridging scientific findings to viable and attractive LC sensor platforms.