Free Energy Structure Research Articles

High-Sensitivity Enzyme-Free Fluorescence Probe Based on CRISPR/Cas13 and the Isothermal Amplification Strategy for Axl Sensing.

Axl is an important receptor tyrosine protein kinase that plays a key role in the development and progression of various diseases, such as cancer and inflammation. Developing a highly sensitive Axl detection method can help improve accuracy, better address-specific clinical needs, and guide personalized treatment. In this study, a CHA-CRISPR/Cas13 fluorescence probe was established using Axl-specific aptamers as a mediator to displace the polynucleotide chain (TA). Through TA construction, an entropy-driven nucleotide catalytic hairpin assembly system was created to cyclically release RNA that activates clustered regularly interspaced short palindromic repeats (CRISPR)/Cas13 activity, triggering its cleavage activity. The activated CRISPR/Cas13 system cleaves the reporter labeled with BHQ1 and FAM at both ends, leading to the recovery of FAM fluorescence. Based on the optimization design using the free energy (△G) and secondary structure software simulation results of the nucleic acid sequence, the fluorescence intensity of the probe is proportional to the concentration of Axl. Results showed a good linear relationship between fluorescence intensity increment and log CAxl (CAxl in the range of 3.33-667 pM, r = 0.9907). The probe exhibited ultrahigh sensitivity with a detection limit of 0.84 pM. It was successfully applied in the detection of human serum samples, showing a higher Axl level in cervical cancer patients compared to breast cancer patients. The probe was also successfully applied in the imaging of various tumor cells, consistent with serum detection results. In conclusion, this probe represents an effective new method for detecting Axl, demonstrating outstanding specificity and sensitivity. It provides technological support for tumor diagnosis and shows the potential for detecting circulating tumor cells in blood through cell imaging.

DinoKnot: Duplex Interaction of Nucleic Acids With PseudoKnots.

Interaction of nucleic acid molecules is essential for their functional roles in the cell and their applications in biotechnology. While simple duplex interactions have been studied before, the problem of efficiently predicting the minimum free energy structure of more complex interactions with possibly pseudoknotted structures remains a challenge. In this work, we introduce a novel and efficient algorithm for prediction of Duplex Interaction of Nucleic acids with pseudoKnots, DinoKnot follows the hierarchical folding hypothesis to predict the secondary structure of two interacting nucleic acid strands (both homo- and hetero-dimers). DinoKnot utilizes the structure of molecules before interaction as a guide to find their duplex structure allowing for possible base pair competitions. To showcase DinoKnots's capabilities we evaluated its predicted structures against (1) experimental results for SARS-CoV-2 genome and nine primer-probe sets, (2) a clinically verified example of a mutation affecting detection, and (3) a known nucleic acid interaction involving a pseudoknot. In addition, we compared our results against our closest competition, RNAcofold, further highlighting DinoKnot's strengths. We believe DinoKnot can be utilized for various applications including screening new variants for potential detection issues and supporting existing applications involving DNA/RNA interactions, adding structural considerations to the interaction to elicit functional information.

Computational Studies Show How the H463R Mutation Turns hKv1.5 into an Inactivation State.

The KCNA5 gene provides the code for the α-subunit of the potassium channel Kv1.5. The genetic variant H463R in the Kv1.5 channel has been reported to cause a functional loss in atrial fibrillation (AF) patients. Understanding the mutations at a molecular level is key to developing improved therapeutics concerning cardiac hKv1.5 and hKv1.4 channels. Molecular dynamics and umbrella sampling free energy simulations are an effective tool to understand the mutation's effect on ion conduction, which we have employed and found that the hKv1.5[H463R] mutation imposes an energy barrier on the ion conduction pathway compared to the wild-type channel's ion free energy and pore structure. These results imply that the arginine mutation associated with the AF disease in particular modulates the inactivation process of hKv1.5. Kv1.4, encoded by the KCNA4 gene, is also present in the heart. Therefore, we considered simulation studies of the equivalent H507R mutation in the hKv1.4 channel and found that the mutation slightly reduces the ion conduction barrier in the ion conduction pathway, making it insignificant.

Structural connectivity of 18‐Crown‐6/H+/L‐tryptophan noncovalent complexes in gas phase and in solution: Delineating host–guest–solvent interactions in solution from gas phase structures

AbstractWe investigate the structural correlation of noncovalent crown ether/H+/L‐tryptophan (CR/TrpH+) host–guest complexes in the solution phase with those in the gas phase generated through electrospray ionization/mass spectrometry (ESI/MS) techniques. We perform quantum chemical calculations to determine their structures, relative Gibbs free energies, and infrared spectra. We compare the calculated infrared (IR) spectra with the IR multiphoton dissociation (IRMPD) spectra observed for the 18‐Crown‐6/TrpH+ complex by Polfer and co‐workers [J. Phys. Chem. A 2013, 117, 1181–1188] for assigning the IR bands. We observe that the carboxyl group remains “naked,” lacking hydrogen bonding with the CR unit in the gas phase, and that this most stable conformer originates from the corresponding lowest Gibbs free energy structure in solution. Based on these findings, we propose that gas phase host–guest complexes directly correlate with those in solution, reinforcing the possibility of obtaining invaluable information about host–guest–solvent interactions in solution from the structure of the host–guest pair in the gas phase.

Multi-atomic loaded C2N1 catalysts for CO2 reduction to CO or formic acid.

In recent years, the development of highly active and selective electrocatalysts for the electrochemical reduction of CO2 to produce CO and formic acid has aroused great interest, and can reduce environmental pollution and greenhouse gas emissions. Due to the high utilization of atoms, atom-dispersed catalysts are widely used in CO2 reduction reactions (CO2RRs). Compared with single-atom catalysts (SACs), multi-atom catalysts have more flexible active sites, unique electronic structures and synergistic interatomic interactions, which have great potential in improving the catalytic performance. In this study, we established a single-layer nitrogen-graphene-supported transition metal catalyst (TM-C2N1) based on density functional theory, facilitating the reduction of CO2 to CO or HCOOH with single-atom and multi-atomic catalysts. For the first time, the TM-C2N1 monolayer was systematically screened for its catalytic activity with ab initio molecular dynamics, density of states, and charge density, confirming the stability of the TM-C2N1 catalyst structure. Furthermore, the Gibbs free energy and electronic structure analysis of 3TM-C2N1 revealed excellent catalytic performance for CO and HCOOH in the CO2RR with a lower limiting potential. Importantly, this work highlights the moderate adsorption energy of the intermediate on 3TM-C2N1. It is particularly noteworthy that 3Mo-C2N1 exhibited the best catalytic performance for CO, with a limiting potential (UL) of -0.62 V, while 3Ti-C2N1 showed the best performance for HCOOH, with a corresponding UL of -0.18 V. Additionally, 3TM-C2N1 significantly inhibited competitive hydrogen evolution reactions. We emphasize the crucial role of the d-band center in determining products, as well as the activity and selectivity of triple-atom catalysts in the CO2RR. This theoretical research not only advances our understanding of multi-atomic catalysts, but also offers new avenues for promoting sustainable CO2 conversion.

Preparation and properties of geopolymer containing phosphoric acid-activated fly ash and mechanically-milled kaolinite: Experiments and density function theory

The environmental pollution resulted from the stacking of solid wastes, and the 250 kg CO2 emission caused by calcined a ton of kaolinite have become an urgent problem to be solved. In this study, a novel phosphoric acid-activated geopolymer was developed, which was composed of fly ash (FA), mechanically activated-kaolinite (MAK). The influences of phosphoric acid concentration, mechanical grinding duration, and curing temperature were investigated. Microstructural properties of FAMAK geopolymers were examined through a serious of tests. Furthermore, the Gibbs free energy and nano-scale structure characteristics of acid-activated hydration products were calculated for the first time by using density functional theory. The results show that the optimal mass ratio of FA to MAK is 7:3 with 8 mol/L phosphoric acid, which led to the maximum compressive strength of 36.6 MPa at 56-day. Besides, the optimal grinding time is 3 h and temperature is 40 °C. Moreover, the content of silicon promotes the polymerization reaction. The valence and bonding of aluminum are primarily affected by its coordination number. The key outcomes in this study provides a low-carbon cementitious materials, which can achieve the double benefits of carbon reduction and the utilization of solid wastes.

Gas Phase Conformation of Trisaccharides and Core Pentasaccharide: A Three-Step Tree-Based Sampling and Quantum Mechanical Computational Approach.

As an important component of N-linked glycoproteins, the core pentasaccharide is highly crucial to the potential application prospect of glycoprotein. However, the gas phase conformation study is a challenging one due to the size and complexity of the molecule, together with the necessity to rely on quantum chemistry modeling for relevant energetics and structures. In this paper, the structures of the trisaccharides and core pentasaccharides in N-linked glycans in the gas phase were constructed by a three-step tree-based (TSTB) sampling. Since single point energies of all the conformers are calculated at the temperature of zero, it is necessary to evaluate the stability at a high temperature. We calculate the Gibbs free energies using the standard thermochemistry model (T = 298.15 K). For trimannose, the energetic ordering at 298.15 K can be strongly changed compared to 0 K. Moreover, two structures of trimannose with high energies at 0 K are considered to provide a much better match of IR vibration signatures with the low Gibbs free energies. On this basis, the core pentasaccharide was constructed in three ways. The building configurations of core pentasaccharide were optimized to obtain reasonable low-energy stable conformers. Fortunately, the lowest-energy structure of core pentasaccharide is eventually the minimum at 0 K and 298.15 K. Furthermore, spectrum analysis of core pentasaccharide was carried out. Although poorly resolved, its contour from the experiment was in qualitative correspondence with the computed IR spectrum associated with its minimum free energy structure. A large number of strongly and weakly hydrogen-bonded hydroxyl and acetylamino groups contribute to a highly congested set of overlapping bands. Compared with traditional conformation generators, the TSTB sampling is employed to efficiently and comprehensively obtain preferred conformers of larger saccharides with lower energy.

LinearCoFold and LinearCoPartition: linear-time algorithms for secondary structure prediction of interacting RNA molecules.

Many RNAs function through RNA-RNA interactions. Fast and reliable RNA structure prediction with consideration of RNA-RNA interaction is useful, however, existing tools are either too simplistic or too slow. To address this issue, we present LinearCoFold, which approximates the complete minimum free energy structure of two strands in linear time, and LinearCoPartition, which approximates the cofolding partition function and base pairing probabilities in linear time. LinearCoFold and LinearCoPartition are orders of magnitude faster than RNAcofold. For example, on a sequence pair with combined length of 26,190nt, LinearCoFold is 86.8× faster than RNAcofold MFE mode, and LinearCoPartition is 642.3× faster than RNAcofold partition function mode. Surprisingly, LinearCoFold and LinearCoPartition's predictions have higher PPV and sensitivity of intermolecular base pairs. Furthermore, we apply LinearCoFold to predict the RNA-RNA interaction between SARS-CoV-2 genomic RNA (gRNA) and human U4 small nuclear RNA (snRNA), which has been experimentally studied, and observe that LinearCoFold's prediction correlates better with the wet lab results than RNAcofold's.

Development of Computational Correlations among Known Drug Scaffolds and their Target-Specific Non-Coding RNA Scaffolds of Alzheimer's Disease.

Alzheimer's disease is the most common neurodegenerative disorder. Recent development in sciences has also identified the pivotal role of microRNAs (miRNAs) in AD pathogenesis. We proposed a novel method to identify AD pathway-specific statistically significant miRNAs from the targets of known AD drugs. Moreover, microRNA scaffolds and corresponding drug scaffolds of different pathways were also discovered. A Wilcoxon signed-rank test was performed to identify pathway-specific significant miRNAs. We generated feed-forward loop regulations of microRNA-TF-gene-based networks, studied the minimum free energy structures of pre-microRNA sequences, and clustered those microRNAs with their corresponding structural motifs of robust transcription factors. Conservation analyses of significant microRNAs were done, and the phylogenetic trees were constructed. We identified 3'UTR binding sites and chromosome locations of these significant microRNAs. In this study, hsa-miR-4261, hsa-miR-153-5p, hsa-miR-6766, and hsa-miR-4319 were identified as key miRNAs for the ACHE pathway and hsa-miR-326, hsa-miR-6133, hsa-miR-4251, hsa-miR-3148, hsa-miR-10527-5p, hsa-miR-527, and hsa-miR-518a were identified as regulatory miRNAs for the NMDA pathway. These miRNAs were regulated by several AD-specific TFs, namely RAD21, FOXA1, and ESR1. It has been observed that anisole and adamantane are important chemical scaffolds to regulate these significant miRNAs. This is the first study that developed a detailed correlation between known AD drug scaffolds and their AD target-specific miRNA scaffolds. This study identified chromosomal locations of microRNAs and corresponding structural scaffolds of transcription factors that may be responsible for miRNA co-regulation for Alzheimer's disease. Our study provides hope for therapeutic improvements in the existing microRNAs by regulating pathways and targets.

Hiking down the Free Energy Landscape Using Sequential Solvent and Thermal Processing for Versatile Ordering of Block Copolymer Films.

The kinetics and morphology of the ordering of block copolymer (BCP) films are highly dependent on the processing pathway, as the enthalpic and entropic forces driving the ordering processes can be quite different depending on process history. We may gain some understanding and control of this variability of BCP morphology with processing history through a consideration of the free energy landscape of the BCP material and a consideration of how the processing procedure moves the system through this energy landscape in a way that avoids having the system becoming trapped into well-defined metastable minima having a higher free energy than the target low free energy ordered structure. It is well known that standard thermal annealing (TA) of BCPs leads to structures corresponding to a well-defined stable free energy minimum; however, the BCP must be annealed for a very long time before the target low free energy structures can be achieved. Herein, we show that the same target low-energy structure can be achieved relatively quickly by subjecting as-cast films to an initial solvent annealing [direct immersion annealing (DIA) or solvent vapor annealing (SVA)] procedure, followed by a short period of TA. This process relies on lowering the activation energy barrier by reducing the glass-transition temperature through DIA (or SVA), followed by a multi-interface chain rearrangement through sequential TA. This energy landscape approach to ordering should be applicable to the process design for ordering many other complex materials.

CRNAsp12 Web Server for the Prediction of Circular RNA Secondary Structures and Stabilities

Circular RNAs (circRNAs) are a novel class of non-coding RNA that, unlike linear RNAs, form a covalently closed loop without the 5' and 3' ends. Growing evidence shows that circular RNAs play important roles in life processes and have great potential implications in clinical and research fields. The accurate modeling of circRNAs structure and stability has far-reaching impact on our understanding of their functions and our ability to develop RNA-based therapeutics. The cRNAsp12 server offers a user-friendly web interface to predict circular RNA secondary structures and folding stabilities from the sequence. Through the helix-based landscape partitioning strategy, the server generates distinct ensembles of structures and predicts the minimal free energy structures for each ensemble with the recursive partition function calculation and backtracking algorithms. For structure predictions in the limited structural ensemble, the server also provides users with the option to set the structural constraints of forcing the base pairs and/or forcing the unpaired bases, such that only structures that meet the criteria are enumerated recursively.

Prediction of α-MORFS and folding free energies in intrinsically disordered peptides.

Intrinsically disordered proteins (IDPs) and disordered regions (IDRs) of folded proteins play significant roles in cell signaling, regulation, and recognition. However, the lack of well-defined structures challenges our ability to predict the biological role and working mechanisms of IDPs. Computer simulations provide a powerful tool to characterize the conformational ensembles explored by IDPs. Here, we use free energy calculations in atomistic simulations to explore the applicability of binding-induced folding mechanisms for the development of ligands that specifically bind to intrinsically disordered proteins. Molecular recognition features (MoRFs) are functional regions located within longer intrinsically disordered regions that undergo disorder-to-order transitions upon binding their specific interaction partners. A subgroup called α-MoRFs undergoes disordered to α-helix transitions upon binding. In principle, MoRFs can also be utilized as targets for the design of drug molecules that bind to such regions in disease-causing IDPs and render them inactive or modulate their properties. We quantify the free energy cost involved in transitions from intrinsically disordered peptide states into folded secondary structure motifs for variable peptide sequences. We compare α-MoRFs and fully disordered sequences from several known proteins and compare our results to state-of-the-art structure predictions. In contrast to structure prediction tools, our atomistic simulation protocol not only allows us to determine the minimum free energy structure but also quantifies the free energy difference between folded and disordered conformational states. The latter is critical for the development of drugs targeting a specific IDR in a folded conformation because the binding free energy needs to overcompensate the free energy cost of folding. Our general strategy aims to reduce the “undruggability” of IDPs and IDRs, which lack an inherent structure and represent a significant fraction of the proteome.

New ternary deep eutectic solvents with cycle performance for efficient pretreated radiata pine forming to lignin containing cellulose nanofibrils

Ternary deep eutectic solvents (TDESs) as a new class of solvents play a key role in fabrication of lignin containing cellulose nanofibrils (LCNF), however, current work requires a considerable time and thus limits industrial application of TDES. Herein, a novel strategy was proposed to produce lignin containing cellulose nanofibrils (LCNF) by TDESs based on benzyltrimethylammonium chloride (BTMAC), formic acid (FA), and maleic acid (MA). The TDESs could remove 87.80% of lignin and 89.15% of hemicellulose from Radiata Pine while most of the cellulose reserved under optimum pretreatment conditions (TDES = 100 wt%, T = 130 °C, t = 1.5 h). Benefiting from the increase in cellulase accessibility, desired sugar yield of 98.9% was obtained. Moreover, the proposed TDESs could be regarded as a green medium for the production of containing cellulose nanofibrils (LCNF) in which lignin has been esterified. The LCNF displayed a well-individualized structure with a wide size distribution (32.3–146.9 nm), which was closely associated with lignin content. 13C−1H HSQC 2D NMR test was performed to illustrate the molecular − structural features of lignin and polysaccharide in LCNF. In addition, the self-standing LCNF films exhibited excellent UV-blocking, higher thermal stability, and mechanical strength. Most importantly, LCNF films showed strong barrier property to oil and air owing to lower surface free energy and smaller pore structure. Briefly, this work highlights the pretreatment performance of TDESs for cascade utilization of lignocellulosic biomass to high-value products.

Free Energy and Solvation Structure Analysis for Adsorption of Aromatic Molecules at Pt(111)/Water Interface by 3D-RISM Theory

Abstract The free energy change of aromatic molecules adsorbed at a Pt(111)/water interface was analyzed using the three-dimensional reference interaction site model (3D-RISM) theory with density functional theory (DFT), compared with the reported experimental data. The changes in the solvation structure induced by molecular adsorption were discussed.

First-principles characterisation and comparison of clean, hydrated, and defect α-Al2O3 and α-Fe2O3 (110) surfaces

ABSTRACT Structural models of the (110) termination of α-Al2O3 and α-Fe2O3 are studied using Density Functional Theory (DFT) calculations and thermodynamics to determine the details of the mineral-water interface structure and stability. Prior experiments have characterised these interfaces, but the X-ray reflectivity techniques used cannot identify the distribution of protons on surface sites. In addition, the alumina (110) surface displays two different surface structures stable in water, with their occurrence dependent on sample preparation conditions. We use theory and modelling to determine the thermodynamically preferred surface structures, including protonation states of surface oxygen functional groups, as a function of temperature and pressure. Consistent with studies of other facets of alumina and hematite, we find that thermodynamically unfavourable defect structures, upon hydration and hydroxylation, show comparable stability to the hydrated forms of ideal terminations. The model results are compared to experimental characterisation of hydrated (110) alumina and hematite surfaces with good agreement between the best-fit structures from experiments and the lowest surface free energy structures from theory and modelling. Electronic structure analysis of the exposed surface functional groups is presented, and we highlight instances in which the electronic density of states differs between oxygen functional groups that have similar coordination environments.

English

Crystal lattice structure searching by Particle Swarm Optimization (PSO) and first-principles structural optimization have been used to explore polymorphs of BC2N, possessing sp3 hybridization, under a varying applied hydrostatic pressure. Two low Gibbs free energy structures were identified: one with a primitive orthorhombic structure and Space Group, Pmm2, and the other with a primitive tetragonal structure and Space Group, P m2. Dynamical and mechanical stabilities of the Pmm2, orthorhombic BC2N (o-BC2N) structure were established using its phonon dispersions and elastic constants. The bulk modulus of this predicted BC2N phase was 377.15 GPa, which indicates a super-hard compound. The material is brittle with a B/G ratio of 0.911 and a low degree of elastic anisotropy with a Universal Elastic Anisotropy Index of only 0.774%. Calculations of the electronic band structure demonstrated that the material is a direct band gap semiconductor with a band gap of 1.731 eV at zero applied pressure. The band gap increases monotonically with increased applied pressure and saturates to a value of about 1.756 eV above 1500 kbars; the hydrostatic pressure coefficients associated with this process were determined.  Key words: High pressure phase stability, elastic anisotropy, ultra-hard material.

Femtosecond Photophysics of Molecular Polaritons.

Molecular polaritons are hybrid states of photonic and molecular character that form when molecules strongly interact with light. Strong coupling tunes energy levels and, importantly, can modify molecular properties (e.g., photoreaction rates), opening an avenue for novel polariton chemistry. In this Perspective, we focus on the collective aspects of strongly coupled molecular systems and how this pertains to the dynamical response of such systems, which, though of key importance for attaining modified function under polariton formation, is still not well-understood. We discuss how the ultrafast time and spectral resolution make pump-probe spectroscopy an ideal tool to reveal the energy-transfer pathways from polariton states to other molecular states of functional interest. Finally, we illustrate how analyzing the free (rather than electronic) energy structure in molecular polariton systems may provide new clues into how energy flows and thus how strong coupling may be exploited.

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryo-electron microscopy (EM) requires molecular modeling to refine structural details from data. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins that cannot be resolved by cryo-EM. Here, we introduce CryoFold - a pipeline of molecular dynamics simulations that determines ensembles of protein structures directly from sequence by integrating density data of varying sparsity at 3-5 Å resolution with coarse-grained topological knowledge of the protein folds. We present six examples showing its broad applicability for folding proteins between 72 to 2000 residues, including large membrane and multi-domain systems, and results from two EMDB competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations, unseen by traditional methods, are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python GUI.

The First Report of Genetic Polymorphisms of the Equine SPRN Gene in Outbred Horses, Jeju and Halla Horses.

Simple SummaryPrion disease is a fatal neurodegenerative disease caused by the accumulation of pathogenic prion protein (PrPSc) in various mammalian hosts. However, to date, prion disease has not been reported in horses. Since the Sho protein encoded by the shadow of the prion protein gene (SPRN) plays an essential role in the progression of prion diseases, we investigated the genetic characteristics of the equine SPRN gene in horses. We found four single nucleotide polymorphisms (SNPs) of the equine SPRN gene and significant different distributions among three horse breeds including Jeju, Halla and Thoroughbred horses. Although the polymorphisms affect the property of mRNA of the equine SPRN gene, it did not affect the sequence and structure of Sho protein. Since several non-synonymous SNPs of the SPRN gene have been reported in prion diseases-susceptible animals, the absence of non-synonymous SNP of the equine SPRN gene in the horses is noticeable.Prion disease is a fatal infectious disease caused by the accumulation of pathogenic prion protein (PrPSc) in several mammals. However, to date, prion disease has not been reported in horses. The Sho protein encoded by the shadow of the prion protein gene (SPRN) plays an essential role in the pathomechanism of prion diseases. To date, the only genetic study of the equine SPRN gene has been reported in the inbred horse, Thoroughbred horse. We first discovered four SPRN single nucleotide polymorphisms (SNPs) in 141 Jeju and 88 Halla horses by direct DNA sequencing. In addition, we found that the genotype, allele and haplotype frequencies of these SNPs of Jeju horses were significantly different from those of Halla and Thoroughbred horses, this latter breed is also included in this study. Furthermore, we observed that the minimum free energy and mRNA secondary structure were significantly different according to haplotypes of equine SPRN polymorphisms by the RNAsnp program. Finally, we compared the SNPs in the coding sequence (CDS) of the SPRN gene between horses and prion disease-susceptible species. Notably, prion disease-susceptible animals had polymorphisms that cause amino acid changes in the open reading frame (ORF) of the SPRN gene, while these polymorphisms were not found in horses.

The Development of Polydimethysiloxane/ZnO–GO Antifouling Coatings

The development of antifouling coating for sensor is desirable because the biofilm can shorten sensor’s life and cause inaccurate reading. In this study, a facile one-pot reaction was used to synthesized ZnO–graphene oxide (GO) (ZnO–GO) nanocomposites. Different amount of ZnO–GO was incorporated in the polydimethylsiloxane (PDMS) matrix respectively though a simple solution mixing method, in order to create PDMS/ZnO–GO nanocomposite (PZGO). The coating was obtained directly by spin coating of PZGO/tetrahydrofuran suspension. The hydrophobicity, surface roughness (Ra), surface free-energy (SFE) and nanoscale structure were investigated as antifouling factors. Antifouling tests were performed using two marine microorganisms, the cyanobacterium Synechococcus sp. Strain PCC 7002 and the diatom Phaeodactylum tricornutum. PZGO0.2 (mass ratio of ZnO–GO to PDMS: 0.2 wt%) displayed excellent antifouling property with 8.5% of Synechococcus sp. Strain PCC 7002 biofilm coverage, while PZGO0.1 (mass ratio of ZnO–GO to PDMS: 0.1 wt%) showed 2.4% P. tricornutum biofilm coverage. The antifouling property of the synthesized PZGO nanocomposite can be attributed to its high Ra and hydrophobicity which was caused by the good dispersion of ZnO–GO in PDMS matrix. This study suggests a potential of PZGO nanocomposite for sensor’s antifouling coating, which could contribute to improve sensor’s durability relating to biofouling in future.Graphic