Investigation of Direct Electron Transfer of Glucose Oxidase on a Graphene-CNT Composite Surface: A Molecular Dynamics Study Based on Electrochemical Experiments.

Graphene and its variants exhibit excellent electrical properties for the construction of enzymatic interfaces. In particular, the direct electron transfer of glucose oxidase on the electrode surface is a very important issue in the development of enzyme-based bioelectrodes. However, the number of studies conducted to assess how pristine graphene forms different interfaces with other carbon materials is insufficient. Enzyme-based electrodes (formed using carbon materials) have been extensively applied because of their low manufacturing costs and easy production techniques. In this study, the characteristics of a single-walled carbon nanotube/graphene-combined enzyme interface are analyzed at the atomic level using molecular dynamics simulations. The morphology of the enzyme was visualized using an elastic network model by performing normal-mode analysis based on electrochemical and microscopic experiments. Single-carbon electrodes exhibited poorer electrical characteristics than those prepared as composites with enzymes. Furthermore, the composite interface exhibited 4.61- and 2.45-fold higher direct electron efficiencies than GOx synthesized with single-carbon nanotubes and graphene, respectively. Based on this study, we propose that pristine graphene has the potential to develop glucose oxidase interfaces and carbon-nanotube-graphene composites for easy fabrication, low cost, and efficient electrode structures for enzyme-based biofuel cells.

A study of forecasting the Nephila clavipes silk fiber's ultimate tensile strength using machine learning strategies.

Recent advancements in biomaterial research conduct artificial intelligence for predicting diverse material properties. However, research predicting the mechanical properties of biomaterial based on amino acid sequences have been notably absent. This research pioneers the use of classification models to predict ultimate tensile strength from silk fiber amino acid sequences, employing logistic regression, support vector machines with various kernels, and a deep neural network (DNN). Remarkably, the model demonstrates a high accuracy of 0.83 during the generalization test. The study introduces an innovative approach to predicting biomaterial mechanical properties beyond traditional experimental methods. Recognizing the limitations of conventional linear prediction models, the research emphasizes the future trajectory toward DNNs that can adeptly capture non-linear relationships with high precision. Moreover, through comprehensive performance comparisons among diverse prediction models, the study offers insights into the effectiveness of specific models for predicting the mechanical properties of certain materials. In conclusion, this study serves as a pioneering contribution, laying the groundwork for future endeavors and advocating for the seamless integration of AI methodologies into materials research.

P18: Novel Anticancer Peptide from Induced Tumor-Suppressing Cells Targeting Breast Cancer and Bone Metastasis.

BACKGROUND: The skeletal system is a common site for metastasis from breast cancer. In our prior work, we developed induced tumor-suppressing cells (iTSCs) capable of secreting a set of tumor-suppressing proteins. In this study, we examined the possibility of identifying anticancer peptides (ACPs) from trypsin-digested protein fragments derived from iTSC proteomes. METHODS: The efficacy of ACPs was examined using an MTT-based cell viability assay, a Scratch-based motility assay, an EdU-based proliferation assay, and a transwell invasion assay. To evaluate the mechanism of inhibitory action, a fluorescence resonance energy transfer (FRET)-based GTPase activity assay and a molecular docking analysis were conducted. The efficacy of ACPs was also tested using an ex vivo cancer tissue assay and a bone microenvironment assay. RESULTS: Among the 12 ACP candidates, P18 (TDYMVGSYGPR) demonstrated the most effective anticancer activity. P18 was derived from Arhgdia, a Rho GDP dissociation inhibitor alpha, and exhibited inhibitory effects on the viability, migration, and invasion of breast cancer cells. It also hindered the GTPase activity of RhoA and Cdc42 and downregulated the expression of oncoproteins such as Snail and Src. The inhibitory impact of P18 was additive when it was combined with chemotherapeutic drugs such as Cisplatin and Taxol in both breast cancer cells and patient-derived tissues. P18 had no inhibitory effect on mesenchymal stem cells but suppressed the maturation of RANKL-stimulated osteoclasts and mitigated the bone loss associated with breast cancer. Furthermore, the P18 analog modified by N-terminal acetylation and C-terminal amidation (Ac-P18-NH2) exhibited stronger tumor-suppressor effects. CONCLUSIONS: This study introduced a unique methodology for selecting an effective ACP from the iTSC secretome. P18 holds promise for the treatment of breast cancer and the prevention of bone destruction by regulating GTPase signaling.

Unraveling the Mechanical Property Decrease of Electrospun Spider Silk: A Molecular Dynamics Simulation Study.

This study investigated the impact of electric fields on Nephila clavipes spider silk using molecular dynamics modeling. Electric fields with varying amplitudes and directions were observed to disrupt the ß sheet structure of spider silk and reduce its mechanical properties. However, a notable exception was observed when a 0.1 V/nm electric field was applied in the antiparallel direction, resulting in improvements in Young's modulus and ultimate tensile strength. The antiparallel direction was observed to be particularly sensitive to electric fields, causing disruptions in beta sheets and hydrogen bonds, which significantly influence the mechanical properties. This study demonstrates that spider silk maintains its structural integrity at 0.1 V/nm. Possibly, lowering the power levels of typical electrospinning machines can prevent secondary structural disruption. These findings provide valuable insights for enhancing silk fiber production and applications using natural silk proteins while shedding light on the impact of electric fields on other silk proteins. Finally, this study opens up possibilities for optimizing electrospinning processes to enhance performance in various silk electrospinning applications.

Enhanced selective discrimination of point-mutated viral RNA through false amplification regulatory direct insertion in rolling circle amplification.

Coronaviruses are single-stranded RNA viruses with high mutation rates. Although a diagnostic method for coronaviruses has been developed, variants appear rapidly. Low test accuracy owing to single-point mutations is one of the main factors in the failure to prevent the early spread of coronavirus infection. Although reverse transcription-quantitative polymerase chain reaction can detect coronavirus infection, it cannot exclude the possibility of false positives, and an additional multiplexing kit is needed to discriminate single nucleotide polymorphism (SNP) variants. Therefore, in this study, we introduced a new nucleic acid amplification method to determine whether an infected person has a SNP mutation using a lateral flow assay (LFA) as a point-of-care test. Unlike traditional DNA amplification methods, direct insertion into rolling circle amplification amplifies the target genes without false amplification. After SNP-selective nucleic acid amplification, nuclease enzymes are used to make double-stranded DNA fragments that the LFA can detect, where specific mismatched DNA is found and cleaved to show different signals when a SNP-type is present. Therefore, wild- and SNP-type variants can be selectively detected. In this study, the limit of detection was 400 aM for viral RNA, and we successfully identified a dominant SNP variant selectively. Clinical tests were also conducted.

An atomistic scale simulation study of structural properties in the silk-fibrohexamerin complex.

The use of Bombyx mori silk fibroin in composite materials has been extensively explored in many studies, owing to its remarkable mechanical properties. Recently, the N-glycan-engineered P25 protein was utilized to improve the mechanical properties of silk. However, the mechanism by which N-glycan-engineered P25 protein enhances the mechanical properties of silk remains unclear. This study analyzed the interaction between the P25 protein and silkworm silk using quantum mechanics/molecular mechanics multiscale simulations and discovered stronger hydrogen bonding between the amorphous domain and the P25 protein. The results confirmed that glycoengineering of the mannose molecule in N-glycan in orders of three, five, and seven increased the hydrogen bonding of the amorphous structures. However, P25 has fewer binding interactions with the crystalline domain. Silk amino acids and mannose molecules were analyzed using QM simulations, and hydroxyl and charged amino acids in the amorphous domains were found to have relatively higher reactivity with mannose molecules in N-glycans than basic and aliphatic amino acids in the crystalline domain. This study demonstrates how the N-glycan-engineered P25 protein can improve the mechanical properties of silk fibroin and identifies a key factor for N-glycan-engineered proteins.

Exploring the Tumor-Suppressing Potential of PSCA in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with low survival rates. We explored an innovative therapeutic approach by leveraging prognostic oncogenic markers. Instead of inhibiting these marker genes, we harnessed their tumor-modifying potential in the extracellular domain. Surprisingly, many of the proteins highly expressed in PDAC, which is linked to poor survival, exhibited tumor-suppressing qualities in the extracellular environment. For instance, prostate stem cell antigens (PSCA), associated with reduced survival, acted as tumor suppressors when introduced extracellularly. We performed in vitro assays to assess the proliferation and migration and evaluated the tumor-modifying capacity of extracellular factors from peripheral blood mononuclear cells (PBMCs) in PDAC tissues. Molecular docking analysis, immunoprecipitation, Western blotting, and RNA interference were employed to study the regulatory mechanism. Extracellular PSCA recombinant protein notably curtailed the viability, motility, and transwell invasion of PDAC cells. Its anti-PDAC effects were partially mediated by Mesothelin (MSLN), another highly expressed tumor-associated antigen in PDAC. The anti-tumor effects of extracellular PSCA complemented those of chemotherapeutic agents like Irinotecan, 5-Fluorouracil, and Oxaliplatin. PSCA expression increased in a conditioned medium derived from PBMCs and T lymphocytes. This study unveils the paradoxical anti-PDAC potential of PSCA, hinting at the dual roles of oncoproteins like PSCA in PDAC suppression.

Biochemical mechanism involved in the enhancement of the Young's modulus of silk by the SpiCE protein.

Silk fibers are known for their superior mechanical properties, with the strongest possessing over seven times the toughness of kevlar. Recently, low molecular weight non-spidroin protein, spider-silk constituting element (SpiCE), has been reported to enhance the mechanical properties of silk; however, its specific action mechanism has not yet been elucidated. Here, we explored the mechanism by which SpiCE strengthened the mechanical properties of major ampullate spidroin 2 (MaSp2) silk through hydrogen bonds and salt bridges of the silk structure via all-atom molecular dynamics simulations. Tensile pulling simulation on silk fiber with SpiCE protein revealed that the SpiCE protein enhanced the Young's modulus by up to 40% more than that of the wild type. Bond characteristic analysis revealed that SpiCE and MaSp2 formed more hydrogen bonds and salt bridges than the MaSp2 wild-type model. Sequence analysis of MaSp2 silk fiber and SpiCE protein revealed that SpiCE protein contained more amino acids that could act as hydrogen bond acceptors/donors and salt bridge partners. Our results provide insights into the mechanism by which non-spidroin proteins strengthen the properties of silk fibers and lay the groundwork for the development of material selection criteria for the design of de novo artificial silk fibers.

Proteomes from AMPK-inhibited peripheral blood mononuclear cells suppress the progression of breast cancer and bone metastasis.

Background: During a developmental process, embryos employ varying tactics to remove unwanted cells. Using a procedure analogous to some of the embryonic cells, we generated a tumor-eliminating conditioned medium (CM) from AMPK-inhibited lymphocytes and monocytes in peripheral blood mononuclear cells (PBMCs). Methods: AMPK signaling was inhibited by the application of a pharmacological agent, Dorsomorphin, and the therapeutic effects of their conditioned medium (CM) were evaluated using in vitro cell cultures, ex vivo breast cancer tissues, and a mouse model of mammary tumors and tumor-induced osteolysis. The regulatory mechanism was evaluated using mass spectrometry-based proteomics, Western blotting, immunoprecipitation, gene overexpression, and RNA interference. Results: While AMPK signaling acted mostly anti-tumorigenic, we paradoxically inhibited it to build induced tumor-suppressing cells and their tumor-eliminating CM. In a mouse model of breast cancer, the application of AMPK-inhibited lymphocyte-derived CM reduced mammary tumors additively to a chemotherapeutic agent, Taxol. It also prevented bone loss in the tumor-bearing tibia. Furthermore, the application of CM from the patient-derived peripheral blood diminished ex vivo breast cancer tissues isolated from the same patients. Notably, proteins enriched in CM included Moesin (MSN), Enolase 1 (ENO1), and polyA-binding protein 1 (PABPC1), which are considered tumorigenic in many types of cancer. The tumor-suppressing actions of MSN and ENO1 were at least in part mediated by Metadherin (Mtdh), which is known to promote metastatic seeding. Conclusion: We demonstrated that PBMCs can be used to generate tumor-suppressive proteomes, and extracellular tumor-suppressing proteins such as MSN, ENO1, and PABPC1 are converted from tumor-promoting factors inside cancer cells. The results support the possibility of developing autologous blood-based therapy, in which tumor-suppressing proteins are enriched in engineered PBMC-derived CM by the inhibition of AMPK signaling.

Predicting mechanical properties of silk from its amino acid sequences via machine learning.

The silk fiber is increasingly being sought for its superior mechanical properties, biocompatibility, and eco-friendliness, making it promising as a base material for various applications. One of the characteristics of protein fibers, such as silk, is that their mechanical properties are significantly dependent on the amino acid sequence. Numerous studies have been conducted to determine the specific relationship between the amino acid sequence of silk and its mechanical properties. Still, the relationship between the amino acid sequence of silk and its mechanical properties is yet to be clarified. Other fields have adopted machine learning (ML) to establish a relationship between the inputs, such as the ratio of different input material compositions and the resulting mechanical properties. We have proposed a method to convert the amino acid sequence into numerical values for input and succeeded in predicting the mechanical properties of silk from its amino acid sequences. Our study sheds light on predicting mechanical properties of silk fiber from respective amino acid sequences.

Sensitive and selective DNA detecting electrochemical sensor via double cleaving CRISPR Cas12a and dual polymerization on hyperbranched rolling circle amplification.

Electrochemical sensors are widely used for nucleic acid detection. However, they exhibit low sensitivity and specificity. To overcome these limitations, DNA amplification method is necessary. In this study, we introduced CRISPR (Clustered regularly interspaced short palindromic repeats) Cas12a-dependent hyperbranched rolling circle amplification (HRCA) into an electrochemical sensor platform. By resolving the existing false-positive issue of HRCA, CRISPR Cas12a determines the real positive amplification that able to enhance its sensitivity for extremely low concentrations of nucleic acids and specificity for single-point mutations. In detail, CRISPR Cas12a, which activates the nucleic acid amplification reaction, was used for both trans and cis cleavage for the first time. Finally, selectively amplified DNA was detected using a screen-printed electrode. Using the change in surface coverage by DNA, the electrochemical sensor detected a decrease in the redox signal. In summary, combining a novel DNA amplification method and electrochemical sensor platform, our proposed method compensates for the shortcomings of existing RCA and hyperbranched RCA, secures a high sensitivity of 10 aM, and overcomes false-positivity problems. Moreover, such creative applications of CRISPR Cas12a may lead to the expansion of its applications to other nucleic acid amplification methods.

Intracellular and extracellular moesins differentially regulate Src activity and ß-catenin translocation to the nucleus in breast cancer cells.

It is increasingly recognized that a single protein can have multiple, sometimes paradoxical, roles in cell functions as well as pathological conditions depending on its cellular locations. Here we report that moesins (MSNs) in the intracellular and extracellular domains present opposing roles in pro-tumorigenic signaling in breast cancer cells. Using live cell imaging with fluorescence resonance energy transfer (FRET)- and green fluorescent protein (GFP)-based biosensors, we investigated the molecular mechanism underlying the cellular location-dependent effect of MSN on Src and ß-catenin signaling in MDA-MB-231 breast cancer cells. Inhibition of intracellular MSN decreased the activities of Src and FAK, whereas overexpression of intracellular MSN increased them. By contrast, extracellular MSN decreased the activities of Src, FAK, and RhoA, as well as ß-catenin translocation to the nucleus. Consistently, Western blotting and MTT-based analysis showed that overexpression of intracellular MSN elevated the expression of oncogenic genes, such as p-Src, ß-catenin, Lrp5, MMP9, Runx2, and Snail, as well as cell viability, whereas extracellular MSN suppressed them. Conditioned medium derived from MSN-overexpressing mesenchymal stem cells or osteocytes showed the anti-tumor effects by inhibiting the Src activity and ß-catenin translocation to the nucleus as well as the activities of FAK and RhoA and MTT-based cell viability. Conditioned medium derived from MSN-inhibited cells increased the Src activity, but it did not affect the activities of FAK and RhoA. Silencing CD44 and/or FN1 in MDA-MB-231 cells blocked the suppression of Src activity and ß-catenin accumulation in the nucleus by extracellular MSN. Collectively, the results suggest that cellular location-specific MSN is a strong regulator of Src and ß-catenin signaling in breast cancer cells, and that extracellular MSN exerts tumor-suppressive effects via its interaction with CD44 and FN1.

Ultrahigh sensitive and selective detection of single nucleotide polymorphism using peptide nucleic acid and ribonuclease H assembled DNA amplification (PRADA).

Early diagnosis and monitoring of cancer is the best way to increase the survival rate among patients with cancer. However, the current cancer screening technology is expensive and time-consuming; hence, cancer screening remains challenging. Therefore, developing a relatively inexpensive and high-performance analytical method is necessary. Especially, mutations in KRAS can be characterized as single nucleotide polymorphism mutations. Therefore, discrimination of single nucleotide polymorphism is essential to detect cancer mutations. This study introduces a method with high sensitivity and selectivity of real-time PCR using peptide nucleic acid (PNA) and RNase H II to detect KRAS single nucleotide polymorphism. This method was developed via the fusion of the existing PNA clamping PCR technique and the RNase H-dependent PCR technique. A synergistic effect was realized by mitigating the shortcomings of each method. Our method had a detection limit of 1 aM and selectivity of 0.01%. This study demonstrated completed validation tests with DNA-spiked plasma sample analysis, cell culture, and analysis of blood samples collected from patients with cancer. Furthermore, we demonstrated the applicability of this method for breath biopsy.

Highly Sensitive and Real-Time Detection of Zinc Oxide Nanoparticles Using Quartz Crystal Microbalance via DNA Induced Conjugation.

With the development of nanotechnology, nanomaterials have been widely used in the development of commercial products. In particular, zinc oxide nanoparticles (ZnONPs) have been of great interest due to their extraordinary properties, such as semiconductive, piezoelectric, and absorbance properties in UVA and UVB (280-400 nm) spectra. However, recent studies have investigated the toxicity of these ZnONPs; therefore, a ZnONP screening tool is required for human health and environmental problems. In this study, we propose a detection method for ZnONPs using quartz crystal microbalance (QCM) and DNA. The detection method was based on the resonance frequency shift of the QCM. In detail, two different complementary DNA strands were used to conjugate ZnONPs, which were subjected to mass amplification. One of these DNA strands was designed to hybridize to a probe DNA immobilized on the QCM electrode. By introducing the ZnONP conjugation, we were able to detect ZnONPs with a detection limit of 100 ng/mL in both distilled water and a real sample of drinking water, which is 3 orders less than the reported critical harmful concentration of ZnONPs. A phosphate terminal group, which selectively interacts with a zinc oxide compound, was also attached at one end of a DNA linker and was attributed to the selective detection of ZnONPs. As a result, better selective detection of ZnONPs was achieved compared to gold and silicon nanoparticles. This work demonstrated the potential of our proposed method as a ZnONP screening tool in real environmental water systems.

Detection of Cd2+ and Pb2+ using amyloid oligomer-reduced graphene oxide composite.

Heavy metal ions are toxic to humans and can further interact with amyloid in the human body to produce amyloid plaques, which disrupt neurotransmitter function and are linked to Alzheimer's and Parkinson's diseases. In this study, we developed an amyloid oligomer-reduced graphene oxide composite (AOrGOC) electrochemical sensor for effective heavy metal ion detection based on square-wave anodic stripping voltammetry. The reactivity between amyloids and heavy metal ions was studied by analyzing the stripping current for different amyloids (lysozyme, bovine serum albumin, and ß-lactoglobulin) and amyloid growth types (monomers, oligomers, and fibrils). Reduced graphene oxide was used to improve the sensitivity of the sensor. The AOrGOC sensor exhibited the detection limits of 86.0 and 9.5 nM for Cd2+ and Pb2+, respectively, and selectively detected Cd2+ and Pb2+ over other heavy metal ions. The AOrGOC sensor also detected Cd2+ and Pb2+ in human plasma, thus exhibiting its potential as a biosensor. This study not only promoted our fundamental understanding of amyloids and the detection of heavy metal ions using amyloids, but also provided valuable insights into amyloid-based electrochemical sensors.

Novel Detection Method for Circulating EGFR Tumor DNA Using Gravitationally Condensed Gold Nanoparticles and Catalytic Walker DNA.

The detection of circulating tumor DNA is a major challenge in liquid biopsies for cancer. Conventionally, quantitative polymerase chain reactions or next-generation sequencing are used to detect circulating tumor DNA; however, these techniques require significant expertise, and are expensive. Owing to the increasing demand for a simple diagnostic method and constant monitoring of cancer, a cost-effective detection technique that can be conducted by non-experts is required. The aim of this study was to detect the circulating tumor DNA containing the epidermal growth factor receptor (EGFR) exon 19 deletion, which frequently occurs in lung cancer. By applying walker DNA to a catalytic hairpin assembly and using the differential dispersibility of gold nanoparticles, we detected EGFR exon 19 deletion mutant #2 DNA associated with lung cancer. Our sensing platform exhibited a limit of detection of 38.5 aM and a selectivity of 0.1% for EGFR exon 19 wild-type DNA. Moreover, we tested and compared EGFR exon 19 deletion mutants #1 and #3 to evaluate the effect of base pair mismatches on the performance of the said technique.

Synergistic enhanced rolling circle amplification based on mutS and radical polymerization for single-point mutation DNA detection.

The detection of nucleic acids in biofluids is essential for changing the paradigm of disease diagnosis. As there are very few nucleic acids present in human biofluids, a high sensitivity method is required to detect nucleic acids for disease diagnosis. The Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation is associated with non-small cell lung cancer. It is a point mutation and requires a highly selective detection technique. In this study, high sensitivity and selectivity were achieved for the detection of KRAS mutation using rolling circle amplification (RCA), atomic transfer radical polymerization (ATRP), mutS enzyme, and electrochemical sensors. Although RCA can isothermally amplify DNA, it has low selectivity for detecting single-base mismatch DNA, and its sensitivity is not suitable for circulating tumor DNA detection. The selectivity of RCA was improved by using mutS, which can bind specifically to point mutations. In addition, as a method of isothermal radical polymerization, ATRP was used to amplify the weak signal of RCA. Since RCA and ATRP reactions occur simultaneously, detection time was reduced, and the calculated detection limit was 3.09 aM. Computational and experimental analyses were conducted to verify each detection step and the combination of mutS, ATRP, and RCA. The experiment was performed using normal human serum samples for biological application, and the proposed detection method was confirmed to have excellent potential for diagnosing cancer patients.

Enhancement of electrode performance through surface modification using carbon nanotubes and porous gold nanostructures.

Recently, the demand for the sensitive detection of nanomaterials and biomolecules has been increasing for evaluating the toxicity of nanomaterials and early diagnosis of diseases. Although many studies have developed new detection assays, these are heavily influenced by the capabilities of the detection equipment. Therefore, the aim of the present study was to improve electrode performance by modifying the surface of the detection electrode using a simple method. Electrode surface modification was performed using carbon nanotubes (CNT) and porous gold nanostructures (NS) with excellent electrical and chemical properties. Through the simple physical deposition of CNT and electrochemical reduction of NS, the increasement of the electrode surface area was achieved. Because of the CNTs attached to the electrodes at the first step, the metal ions constituting the NS can adhere well to the electrodes. Nanoparticles with a porous structure can be generated through electrochemical reduction (cyclic voltammetry) of metal ions attached to electrodes. Consequently, the surface area of the electrode increased and electrochemical performance was improved (confirmed by atomic force microscopy, Nyquist plot and Bode plot). To quantitatively confirm the improvement of electrode performance according to the surface change through the proposed treatment technique, DNA was detected. Unlike previous surface modification studies, the developed surface treatment technique can be applied to a variety of detection equipment. To confirm this, the detection was performed using two detection devices with different operating principles. DNA detection using the two types of equipment confirmed that the detection limit was increased by approximately 1000-fold through applying a simple surface treatment. In addition, this method is applicable to detect various sizes of nanomaterials. The method proposed in this study is simple and has the advantage that it can be applied to various devices and various materials.

Nano-fishnet formation of silk controlled by Arginine density.

Silk fiber is renowned for its superb mechanical properties, such as over 7 times the toughness of Kevlar 49 Fibre. As the spider silk is tougher than any man-made fiber, there is a lot to be learned from spider silk. Recently, it has been reported that a large portion of the properties of silk is from naturally formed nano-fishnet structures of silk, but neither its formation mechanism nor its formation condition has been explained. Here, we show how the formation and disappearance of nano-fishnet of silk is determined by humidity, and how the humidity-dependency of nano-fishnet formation can be overcome by changing density of Arginine through sequence mutation. We demonstrate that the nano-fishnet-structured silk exhibits higher strength and toughness than its counterparts. This information on controllable nano-fishnet formation of silk is expected to pave the way for development of protein and synthetic fiber design. STATEMENT OF SIGNIFICANCE: Silk fibers are a very interesting material in that it exhibits superb mechanical properties such as 7 times the toughness of Kevlar 49 Fibre, despite being only composed of proteins. Therefore, it is important that we understand the principle of its high mechanical properties so that it may be applied in designing synthetic fibers. Recently, it has been reported that a large portion of its mechanical property comes from its nano-fishnet structures, but no detailed explanation on the condition or mechanism of formation. Through molecular dynamic simulations, we simulated the nano-fishnet formation of silk and analyzed the condition and mechanism behind it, and showed how the formation of nano-fishnet structures could be controlled by changing the density of Arginine residues. Our study provides information on fiber enhancement mechanism that could be applied to synthetic and protein fiber design.