Dynamics of Molecular Self-Assembly of Short Peptides at Liquid-Solid Interfaces - Effect of Charged Amino Acid Point Mutations.

Self-organizing solid-binding peptides on atomically flat solid surfaces offer a unique bio/nano hybrid platform, useful for understanding the basic nature of biology/solid coupling and their practical applications. The surface behavior of peptides is determined by their molecular folding, which is influenced by various factors and is challenging to study. Here, the effect of charged amino acids is studied on the self-assembly behavior of a directed evolution selected graphite-binding dodecapeptide on graphite surface. Two mutations, M6 and M8, are designed to introduce negatively and positively charged moieties, respectively, at the anchoring domain of the wild-type (WT) peptide, affecting both binding and assembly. The questions addressed here are whether mutant peptides exhibit molecular crystal formation and demonstrate molecular recognition on the solid surface based on the specific mutations. Frequency-modulated atomic force microscopy is used for observations of the surface processes dynamically in water at molecular resolution over several hours at the ambient. The results indicate that while the mutants display distinct folding and surface behavior, each homogeneously nucleates and forms 2D self-organized patterns, akin to the WT peptide. However, their growth dynamics, domain formation, and crystalline lattice structures differ significantly. The results represent a significant step toward the rational design of bio/solid interfaces, potent facilitators of a variety of future implementations.

A simple machine learning approach for preoperative diagnosis of esophageal burns after caustic substance ingestion in children.

PURPOSE: The unresolved debate about the management of corrosive ingestion is a major problem both for the patients and healthcare systems. This study aims to demonstrate the presence and the severity of the esophageal burn after caustic substance ingestion can be predicted with complete blood count parameters. METHODS: A multicenter, national, retrospective cohort study was performed on all caustic substance cases between 2000 and 2018. The classification learner toolbox of MATLAB version R2021a was used for the classification problem. Machine learning algorithms were used to forecast caustic burn. RESULTS: Among 1839 patients, 142 patients (7.7%) had burns. The type of the caustic and the PDW (platelet distribution width) values were the most important predictors. In the acid group, the AUC (area under curve) value was 84% while it was 70% in the alkaline group. The external validation had 85.17% accuracy in the acidic group and 91.66% in the alkaline group. CONCLUSIONS: Artificial intelligence systems have a high potential to be used in the prediction of caustic burns in pediatric age groups.

Evaluation of the systemic immune inflammation index and the systemic inflammatory response index as new markers for the diagnosis of acute appendicitis in children.

BACKGROUND: Abdominal pain is a common and non-specific symptom in children. It is important to be able to distinguish the source of abdominal pain before surgery. OBJECTIVES: Assess importance of the systemic immune inflammation index (SII), systemic inflammation response index (SIRI), and other systemic inflammatory response blood cell indices in predicting the diagnosis and prognosis of acute appendicitis in children. DESIGN: Retrospective cohort SETTING: Single center in Turkey PATIENTS AND METHODS: The files of patients with abdominal pain aged 0-18 years who underwent surgery for appendicitis in our clinic between January 2011 and January 2022 were reviewed. According to the pathology results, patients were divided into two groups, those with pathologic findings of appendicitis (positive for appendicitis) and those without appendicitis. Systemic inflammation markers were statistically compared between the groups. MAIN OUTCOME MEASURES: Systemic inflammation markers. SAMPLE SIZE: 1265 patients RESULTS: Of the 1265 patients, 784 (62%) were male and 481 were female (38%). According to the pathologic examinations, 256 (20.2%) patients did not have appendicitis, and 1009 (79.8%) patients had acute appendicitis. The SIRI level was significantly higher in patients with acute appendicitis compared with patients without acute appendicitis (P<.001). Levels of SII were significantly higher in patients with acute appendicitis (P<.001). CONCLUSION: In children presenting with abdominal pain, high SIRI and SII values alone support the diagnosis of acute appendicitis at a rate of 95%. When physical examination findings, duration of pain, and imaging test results are added, the diagnosis becomes clear at a rate of 98%. LIMITATIONS: Single-center study and retrospective.

Hepatogonadal fusion (HGF), a rare cause of undescended testis. 7th case in the Literature.

BACKGROUND: Hepatogonadal fusion (HGF). It is a rare congenital anomaly characterized by the fusion of the liver and gonads in the intrauterine period. We report the 7th hepatogonadal fusion case in the literature and its treatment. CASE PRESENTATION: In the physical examination of a 4-month-old male patient who applied with the complaint of recurrent swelling in the right inguinal region, a right inguinal hernia was detected and the right testis could not be palpated. The patient underwent laparoscopy. It was observed that the right testis was in the abdomen at the level of the inner ring of the inguinal canal and adhered to the level of the liver segment 6 with a thick band. Hepatogonadal fusion was separated, then hernia repair and orchidopexy were performed. The patient was discharged on the 1st postoperative day. Both testes of the patient were palpable in the scrotum at the 6th month postoperative follow-up. CONCLUSIONS: In conclusion, HGF may cause undescended testis with intra-abdominal localization. The use of laparoscopy in intrabdominal testis cases is a very accurate choice in the diagnosis and treatment of rare cases such as HGF. KEY WORDS: Hepatogonadal fusion, Intra-abdominal testis, Laparoscopy, Orchidopexy, Undescended testis.

iOBPdb A Database for Experimentally Determined Functional Characterization of Insect Odorant Binding Proteins.

Odorant binding proteins (OBPs) are extra-cellular proteins that solubilize and transport volatile organic compounds (VOCs). Thousands of OBPs have been identified through genome sequencing, and hundreds have been characterized by fluorescence ligand binding assays in individual studies. There is a limited understanding of the comparative structure-function relations of OBPs, primarily due to a lack of a centralized database that relates OBP binding affinity and structure. Combining 181 functional studies containing 382 unique OBPs from 91 insect species, we present a database, iOBPdb, of OBP binding affinities for 622 individual VOC targets. This initial database provides powerful search and associative capabilities for retrieving and analyzing OBP-VOC binding interaction data. We have validated this dataset using phylogenetic mapping to determine the authenticity of the collected sequences and whether they cluster according to their assigned subfamilies. Potential applications include developing molecular probes for biosensors, novel bioassays and drugs, targeted pesticides that inhibit VOC/OBP interactions, and understanding odor sensing and perception in the brain.

Molecular Scale Structure and Kinetics of Layer-by-Layer Peptide Self-Organization at Atomically Flat Solid Surfaces.

Understanding the mechanisms of self-organization of short peptides into two- and three-dimensional architectures are of great interest in the formation of crystalline biomolecular systems and their practical applications. Since the assembly is a dynamic process, the study of structural development is challenging at the submolecular dimensions continuously across an adequate time scale in the natural biological environment, in addition to the complexities stemming from the labile molecular structures of short peptides. Self-organization of solid binding peptides on surfaces offers prospects to overcome these challenges. Here we use a graphite binding dodecapeptide, GrBP5, and record its self-organization process of the first two layers on highly oriented pyrolytic graphite surface in an aqueous solution by using frequency modulation atomic force microscopy in situ. The observations suggest that the first layer forms homogeneously, generating self-organized crystals with a lattice structure in contact with the underlying graphite. The second layer formation is mostly heterogeneous, triggered by the crystalline defects on the first layer, growing row-by-row establishing nominally diverse biomolecular self-organized structures with transient crystalline phases. The assembly is highly dependent on the peptide concentration, with the nucleation being high in high molecular concentrations, e.g., >100 µM, while the domain size is small, with an increase in the growth rate that gradually slows down. Self-assembled peptide crystals are composed of either singlets or doublets establishing P1 and P2 oblique lattices, respectively, each commensurate with the underlying graphite lattice with chiral crystal relations. This work provides insights into the surface behavior of short peptides on solids and offers quantitative guidance toward elucidating molecular mechanisms of self-assembly helping in the scientific understanding and construction of coherent bio/nano hybrid interfaces.

Data-driven design of a multiplexed, peptide-sensitized transistor to detect breath VOC markers of COVID-19.

Exhaled human breath contains a rich mixture of volatile organic compounds (VOCs) whose concentration can vary in response to disease or other stressors. Using simulated odorant-binding proteins (OBPs) and machine learning methods, we designed a multiplex of short VOC- and carbon-binding peptide probes that detect a characteristic "VOC fingerprint". Specifically, we target VOCs associated with COVID-19 in a compact, molecular sensor array that directly transduces vapor composition into multi-channel electrical signals. Rapidly synthesizable, chimeric VOC- and solid-binding peptides were derived from selected OBPs using multi-sequence alignment with protein database structures. Selective peptide binding to targeted VOCs and sensor surfaces was validated using surface plasmon resonance spectroscopy and quartz crystal microbalance. VOC sensing was demonstrated by peptide-sensitized, exposed-channel carbon nanotube transistors. The data-to-device pipeline enables the development of novel devices for non-invasive monitoring, diagnostics of diseases, and environmental exposure assessment.

Biomimetic Dentin Repair: Amelogenin-Derived Peptide Guides Occlusion and Peritubular Mineralization of Human Teeth.

Exposure of dentin tubules due to loss of protective enamel (crown) and cementum (root) tissues as a result of erosion, mechanical wear, gingival recession, etc. has been the leading causes of dentin hypersensitivity. Despite being a widespread ailment, no permanent solution exists to address this oral condition. Current treatments are designed to alleviate the pain by either using desensitizers or blocking dentin tubules by deposition of minerals or solid precipitates, which often have short-lived effects. Reproducing an integrated mineral layer that occludes exposed dentin with concomitant peritubular mineralization is essential to reestablish the structural and mechanical integrity of the tooth with long-term durability. Here, we describe a biomimetic treatment that promotes dentin repair using a mineralization-directing peptide, sADP5, derived from amelogenin. The occlusion was achieved through a layer-by-layer peptide-guided remineralization process that forms an infiltrating mineral layer on dentin. The structure, composition, and nanomechanical properties of the remineralized dentin were analyzed by cross-sectional scanning electron microscopy imaging, energy dispersive X-ray spectroscopy, and nanomechanical testing. The elemental analysis provided calcium and phosphate compositions that are similar to those in hydroxyapatite. The measured average hardness and reduced elastic modulus values for the mineral layer were significantly higher than those of the demineralized and sound human dentin. The structural integration of the new mineral and underlying dentin was confirmed by thermal aging demonstrating no physical separation. These results suggest that a structurally robust and mechanically durable interface is formed between the interpenetrating mineral layer and underlying dentin that can withstand long-term mechanical and thermal stresses naturally experienced in the oral environment. The peptide-guided remineralization procedure described herein could provide a foundation for the development of highly effective oral care products leading to novel biomimetic treatments for a wide range of demineralization-related ailments and, in particular, offers a potent long-term solution for dentin hypersensitivity.

Brain Inspired Cortical Coding Method for Fast Clustering and Codebook Generation.

A major archetype of artificial intelligence is developing algorithms facilitating temporal efficiency and accuracy while boosting the generalization performance. Even with the latest developments in machine learning, a key limitation has been the inefficient feature extraction from the initial data, which is essential in performance optimization. Here, we introduce a feature extraction method inspired by energy-entropy relations of sensory cortical networks in the brain. Dubbed the brain-inspired cortex, the algorithm provides convergence to orthogonal features from streaming signals with superior computational efficiency while processing data in a compressed form. We demonstrate the performance of the new algorithm using artificially created complex data by comparing it with the commonly used traditional clustering algorithms, such as Birch, GMM, and K-means. While the data processing time is significantly reduced-seconds versus hours-encoding distortions remain essentially the same in the new algorithm, providing a basis for better generalization. Although we show herein the superior performance of the cortical coding model in clustering and vector quantization, it also provides potent implementation opportunities for machine learning fundamental components, such as reasoning, anomaly detection and classification in large scope applications, e.g., finance, cybersecurity, and healthcare.

Chimeric Peptide-Based Biomolecular Constructs for Versatile Nucleic Acid Biosensing.

Nucleic acid biomarkers hold great potential as key indicators for the diagnosis and monitoring of diseases. Herein we design and implement bifunctional chimeric biomolecules composed of a solid-binding peptide (SBP) domain that specifically adsorbs onto solid sensor surfaces and a peptide nucleic acid (PNA) moiety that facilitates anchoring of antisense oligonucleotide (ASO) probes for the detection of nucleic acid targets. A gold-binding peptide, AuBP1, previously selected by directed evolution to specifically bind to gold, served as the basis for immobilizing nucleic acid probes onto gold substrates. Using surface plasmon resonance (SPR) spectroscopy and quartz crystal microbalance (QCM) analyses, we demonstrate the sequential biomolecular assembly of the heterofunctional solid-binding peptide-antisense oligomer (SBP-ASO) construct onto a sensor surface and the subsequent detection of DNA in an aqueous environment. The effect of steric hindrance on optimal probe assembly is observed, establishing that less packing density results in greater target capture efficacy. In addition, an adsorbed layer of chimeric solid-binding peptide-peptide nucleic acid (SBP-PNA) undergoes viscoelastic changes at the solid-liquid interface upon probe immobilization and DNA target capture, whereby the rigid biofunctional layer becomes more flexible. The dual nature of the chimeric construct is highly amenable to a variety of platforms allowing for both specific recognition and probe immobilization on the sensor surface, while the modular design of the solid-binding peptide-antisense oligonucleotide provides facile functionalization of a wide diversity of solid substrates.

The Effect of Botulinum Toxin in Experimental Hypertrophic Pyloric Stenosis.

Purpose: Infantile hypertrophic pyloric stenosis is the most common cause of gastric outlet obstruction in the first month of life. Botulinum toxin (BT) is a neurotoxin produced by clostridium botulinum, which causes paralysis in skeletal muscles. We aimed to evaluate the effectiveness of BT in the experimental pyloric stenosis model. Methods: The study protocol was approved by the Selcuk University Medical Faculty Ethics Committee (2017/20). We performed an experimental study using 32 Wistar-Albino newborn rats. Rats were divided randomly into four groups with six rats in both control (C), and L-nitro-arginine methyl ester hydrochloride group, and 10 rats in each sham (S), and BT group. 100 mg/kg per day L-NAME was applied to all groups intraperitoneally for 14 days from birth except control group. 0.2 mL saline and 20 U/kg BT was injected by surgery to S and BT groups, respectively, at 21 days from birth. After 35 days all rats were sacrificed and biopsies were performed from pyloric muscle for histopathological examination. The results were evaluated with the "one-way ANOVA" test. Results: Total and circular muscle thickness of the groups were compared. The total muscle thickness of the L-NAME group was significantly higher than the control group (P = .031). Comparing the circular muscle thickness of botox group (BTG) with control group (CG) and L-NAME GROUP (LNG), muscle thickness was significantly smaller (P < .001, P < .001). The total muscle thickness of BTG was significantly different between LNG (P < .001). Conclusions: Hypertrophy of pylor in an experimental model was reduced by BT injection in this study. We think that Botox injection through endoscopic or interventional radiological methods may be an alternative method for surgery.

Solid-Binding Peptide-Guided Spatially Directed Immobilization of Kinetically Matched Enzyme Cascades in Membrane Nanoreactors.

Biocatalysis is a useful strategy for sustainable green synthesis of fine chemicals due to its high catalytic rate, reaction specificity, and operation under ambient conditions. Addressable immobilization of enzymes onto solid supports for one-pot multistep biocatalysis, however, remains a major challenge. In natural pathways, enzymes are spatially coupled to prevent side reactions, eradicate inhibitory products, and channel metabolites sequentially from one enzyme to another. Construction of a modular immobilization platform enabling spatially directed assembly of multiple biocatalysts would, therefore, not only allow the development of high-efficiency bioreactors but also provide novel synthetic routes for chemical synthesis. In this study, we developed a modular cascade flow reactor using a generalizable solid-binding peptide-directed immobilization strategy that allows selective immobilization of fusion enzymes on anodic aluminum oxide (AAO) monoliths with high positional precision. Here, the lactate dehydrogenase and formate dehydrogenase enzymes were fused with substrate-specific peptides to facilitate their self-immobilization through the membrane channels in cascade geometry. Using this cascade model, two-step biocatalytic production of l-lactate is demonstrated with concomitant regeneration of soluble nicotinamide adenine dinucleotide (NADH). Both fusion enzymes retained their catalytic activity upon immobilization, suggesting their optimal display on the support surface. The 85% cascading reaction efficiency was achieved at a flow rate that kinetically matches the residence time of the slowest enzyme. In addition, 84% of initial catalytic activity was preserved after 10 days of continuous operation at room temperature. The peptide-directed modular approach described herein is a highly effective strategy to control surface orientation, spatial localization, and loading of multiple enzymes on solid supports. The implications of this work provide insight for the single-step construction of high-power cascadic devices by enabling co-expression, purification, and immobilization of a variety of engineered fusion enzymes on patterned surfaces.

Chiral Recognition of Self-Assembled Peptides on MoS2 via Lattice Matching.

Chiral recognition of peptides on solid surfaces has been studied for a better understanding of their assembly mechanism toward its applications in stereochemistry and enantioselective catalysis. However, moving from small peptides such as dipeptides, understanding the chiral recognition of larger biomolecules such as oligopeptides or peptides with a larger sequence is challenging. Furthermore, their intrinsic mechanism for chiral recognition in liquid conditions was poorly investigated experimentally. Here, we used in/ex situ atomic force microscopy (AFM) to investigate the chiral recognition of self-assembled structures of l/d-type peptides on molybdenum disulfide (MoS2). We chose single-layer MoS2 with a triangular shape as a substrate for the self-assembly of peptides. The facet edges of MoS2 were utilized as a landmark to identify the crystallographic orientation of their ordered structures. We found both peptide enantiomers formed nanowires on MoS2 with a mirror symmetry according to the facet edges of MoS2. From in situ AFM measurements, we found a dimension of a unit cell in the self-assembled structure and proposed a model of lattice matching between peptides and MoS2 lattice. The lattice matching for chiral recognition was further investigated by changing peptide sequences and surface lattice from MoS2 to graphite. This work further deepened the understanding of biomolecular chiral recognition and will lead us to rationally design specific morphologies and conformations of chiral self-assembled structures of peptides with expected functions in the future.

Symbiotic assembly of peptide nano-mosaics at solid interfaces.

The spontaneous co-organization of distinct biomolecules at interfaces enables many of Nature's hierarchical organizations involving both hard and soft materials. Engineering efforts to mimic such hybrid complexes rely on our ability to rationally structure biomolecules at inorganic interfaces. Control over the nanoscale structure of patterned biomolecules remains challenging due to difficulties in controlling the multifarious interactions involved. This work discusses binary peptide assembly as a means to fabricate biomolecular nano-mosaics at graphite surfaces with predictable structures. Distinct peptide-substrate interactions lead to divergent crystallographic growth directions, molecular scale immiscibility, and a symbiotic assembly phenomenon. We present a symbiotic assembly model that accurately predicts the binary assembly structure relying solely on the constituent peptide nucleation kinetics and molar fractions. The ability to tune such biomolecular nano-mosaic structures facilitates the bottom up fabrication of high-density, multifunctional interfaces for nanotechnology.

Long-term durability of a physician-modified endovascular graft.

We present a unique assessment confirming the long-term durability of a physician-modified endograft deployed as part of an Investigational Device Exemption clinical trial (NCT# 01538056). After receiving an intact postmortem aorta 7 years after the index procedure, we performed microcomputed tomography, necropsy, and metallurgical analysis on the specimen. Microcomputed tomography showed a single strut fracture not noted during previous surveillance. Necropsy revealed no graft fabric compromise, and examination of all three visceral fenestrations showed excellent alignment with no evidence of degradation. Analysis of the strut fracture implicated an initially small, fatigue-induced crack that likely succumbed during postmortem handling.

Thermal Selection of Aqueous Molecular Conformations for Tailored Energetics of Peptide Assemblies at Solid Interfaces.

Key to the development of functional bioinorganic soft interfaces is the predictive control over the micron-scale assembly structure and energetics of biomolecules at solid interfaces. While assembly of labile biomolecules, such as short peptides, at interfaces is a great deal affected by the shape of the molecule, biomolecular conformations are prompted by external solution conditions, involving temperature, pH, and salt concentration. In this light, one can expect that the environmental conformational selection of aqueous biomolecules could potentially allow for fine-tuning of the equilibrium assembly structure at interfaces, as well as, the binding strength and molecular mobility within these assemblies. Here, we demonstrate the energetic and structural tailoring of two-dimensional surface assemblies of graphite-binding dodecapeptides, through the thermal selection of aqueous peptide conformations. Our findings based on a scanning probe energetic analysis, supplemented by molecular dynamics modeling, show that peptide-graphite and peptide-peptide intermolecular interactions strongly depend on the thermally selected molecular conformation and that the extent of the conformational change is directly related to the observed assembled structure. Enabled by these results was the design of a peptide with predictable binding and assembled structure, thus, suggesting environmental preconditioning of peptides as a means for controlling self-assembling active bioinorganic interfaces for bioelectronic implementations such as biomolecular fuel cells and biosensors.

Conformationally directed assembly of peptides on 2D surfaces mediated by thermal stimuli.

Dynamic and environmentally directed assembly of molecules in biological systems is essential for the fabrication of micronscale, hierarchical, functional structures. Here, we demonstrate the directed assembly of genetically selected graphite binding peptides on 2D solid surfaces upon thermal stimuli. Structural and kinetic analyses as well as molecular dynamics simulations yield the self-assembly process as thermally controllable upon tuning the solvated peptide conformational states. The ability to tailor the structure of two-dimensional soft bio/nano interfaces via external stimuli shows the potential for the bottom-up fabrication of complex materials with nanotechnological importance, such as biosensors, bioelectronics, and biomolecular fuel cells.

Emotional State Estimation using Sensor Fusion of EEG and EDA.

Emotions potentially have a significant impact on human actions and recognizing affective states is an effective way of implementing Brain-Computer Interface (BCI) systems which process brain signals to allow direct communication and interaction with the environment. In this paper, a real-time emotion recognition model was developed on the basis of physiological signals. A sensor fusion method is developed to detect human emotion by using data acquired from ElectroEncephaloGraphy (EEG) and ElectroDermal Activity (EDA) sensors. The proposed physiology-based emotion recognition system using a neural network was implemented and tested on human subjects, and a classification accuracy of 94% on three different emotions was achieved.

Biomimetic Tooth Repair: Amelogenin-Derived Peptide Enables in Vitro Remineralization of Human Enamel.

White spot lesions (WSL) and incipient caries on enamel surfaces are the earliest clinical outcomes for demineralization and caries. If left untreated, the caries can progress and may cause complex restorative procedures or even tooth extraction which destroys soft and hard tissue architecture as a consequence of connective tissue and bone loss. Current clinical practices are insufficient in treating dental caries. A long-standing practical challenge associated with demineralization related to dental diseases is incorporating a functional mineral microlayer which is fully integrated into the molecular structure of the tooth in repairing damaged enamel. This study demonstrates that small peptide domains derived from native protein amelogenin can be utilized to construct a mineral layer on damaged human enamel in vitro. Six groups were prepared to carry out remineralization on artificially created lesions on enamel: (1) no treatment, (2) Ca2+ and PO43- only, (3) 1100 ppm fluoride (F), (4) 20 000 ppm F, (5) 1100 ppm F and peptide, and (6) peptide alone. While the 1100 ppm F sample (indicative of common F content of toothpaste for homecare) did not deliver F to the thinly deposited mineral layer, high F test sample (indicative of clinical varnish treatment) formed mainly CaF2 nanoparticles on the surface. Fluoride, however, was deposited in the presence of the peptide, which also formed a thin mineral layer which was partially crystallized as fluorapatite. Among the test groups, only the peptide-alone sample resulted in remineralization of fairly thick (10 µm) dense mineralized layer containing HAp mineral, resembling the structure of the healthy enamel. The newly formed mineralized layer exhibited integration with the underlying enamel as evident by cross-sectional imaging. The peptide-guided remineralization approach sets the foundation for future development of biomimetic products and treatments for dental health care.

Electrochemical Control of Peptide Self-Organization on Atomically Flat Solid Surfaces: A Case Study with Graphite.

The nanoscale self-organization of biomolecules, such as proteins and peptides, on solid surfaces under controlled conditions is an important issue in establishing functional bio/solid soft interfaces for bioassays, biosensors, and biofuel cells. Electrostatic interaction between proteins and surfaces is one of the most essential parameters in the adsorption and self-assembly of proteins on solid surfaces. Although the adsorption of proteins has been studied with respect to the electrochemical surface potential, the self-assembly of proteins or peptides forming well-organized nanostructures templated by lattice structure of the solid surfaces has not been studied in the relation to the surface potential. In this work, we utilize graphite-binding peptides (GrBPs) selected by the phage display method to investigate the relationship between the electrochemical potential of the highly ordered pyrolytic graphite (HOPG) and peptide self-organization forming long-range-ordered structures. Under modulated electrical bias, graphite-binding peptides form various ordered structures, such as well-ordered nanowires, dendritic structures, wavy wires, amorphous (disordered) structures, and islands. A systematic investigation of the correlation between peptide sequence and self-organizational characteristics reveals that the presence of the bias-sensitive amino acid modules in the peptide sequence has a significant effect on not only surface coverage but also on the morphological features of self-assembled structures. Our results show a new method to control peptide self-assembly by means of applied electrochemical bias as well as peptide design-rules for the construction of functional soft bio/solid interfaces that could be integrated in a wide range of practical implementations.