Cy-preds: An algorithm and a web service for the analysis and prediction of cysteine reactivity

Redox Regulation of Brain Selective Kinases BRSK1/2: Implications for Dynamic Control of the Eukaryotic AMPK family through Cys-based mechanisms

In eukaryotes, protein kinase signaling is regulated by a diverse array of post-translational modifications (PTMs), including phosphorylation of Ser/Thr residues and oxidation of cysteine (Cys) residues. While regulation by activation segment phosphorylation of Ser/Thr residues is well understood, relatively little is known about how oxidation of cysteine residues modulate catalysis. In this study, we investigate redox regulation of the AMPK-related Brain-selective kinases (BRSK) 1 and 2, and detail how broad catalytic activity is directly regulated through reversible oxidation and reduction of evolutionarily conserved Cys residues within the catalytic domain. We show that redox-dependent control of BRSKs is a dynamic and multilayered process involving oxidative modifications of several Cys residues, including the formation of intramolecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys within an unusual CPE motif at the end of the activation segment. Consistently, mutation of the CPE-Cys increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family.

Electrophilic MiniFrags Revealed Unprecedented Binding Sites for Covalent HDAC8 Inhibitors

Screening of ultra-low-molecular weight ligands (MiniFrags) successfully identified viable chemical starting points for a variety of drug targets. Here we report the electrophilic analogues of MiniFrags that allow the mapping of potential binding sites for covalent inhibitors by biochemical screening and mass spectrometry. Small electrophilic heterocycles and their N-quaternized analogues were first characterized in the glutathione assay to analyze their electrophilic reactivity. Next, the library was used for systematic mapping of potential covalent binding sites available in human histone deacetylase 8 (HDAC8). The covalent labeling of HDAC8 cysteines has been proven by tandem mass spectrometry measurements, and the observations were explained by mutating HDAC8 cysteines. As a result, screening of electrophilic MiniFrags identified three potential binding sites suitable for the development of allosteric covalent HDAC8 inhibitors. One of the hit fragments was merged with a known HDAC8 inhibitor fragment using different linkers, and the linker length was optimized to result in a lead-like covalent inhibitor.

Predicting cysteine reactivity changes upon phosphorylation using XGBoost

Cysteine reactivity serves as a significant indicator of protein function and can be affected by phosphorylation events. Experimental approaches have been developed to investigate this effect, but the scale is still relatively limited. Machine-learning approaches promise to accelerate the investigation of these phenomena. In this study, protein sequence information, distances to the closest phosphorylation sites, and the membership score of the intrinsically disordered region were used to represent the cysteine. Following the feature selection using an elastic net model, two groups of binary classifiers based on XGBoost were built to predict the occurrence and the direction of the reactivity change as a response to phosphorylation events, respectively. In addition, function enrichment analysis was performed on proteins/genes predicted to have reactivity changes. XGBoost performed the best in the independent test with AUC of 0.8192 and 0.9203 for the prediction of the change's occurrence and direction, respectively. The use of two binary classifiers successively resulted in an accuracy of 0.7568 in predicting whether reactivity would be unchanged, increased, or decreased. The enrichment analysis revealed the association of proteins carrying reactivity-changed cysteine residues with various disease-related pathways, particularly cancer, autosomal dominant diseases, and viral infections. Changes in cysteine reactivity influenced by phosphorylation are site-specific and can be predicted by XGBoost algorithms. Our model provides an efficient alternative way to explore the cysteine reactivity upon phosphorylation at the proteome-wide level, facilitating the investigation of protein functions and their clinical insights. Our code is available on GitHub (https://github.com/DarinaOsamu/predictors-of-cysteine-reactivity-changes).

Hydrogen peroxide-dependent oxidation of ERK2 within its D-recruitment site alters its substrate selection

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) are dysregulated in many pervasive diseases. Recently, we discovered that ERK1/2 is oxidized by signal-generated hydrogen peroxide in various cell types. Since the putative sites of oxidation lie within or near ERK1/2's ligand-binding surfaces, we investigated how oxidation of ERK2 regulates interactions with the model substrates Sub-D and Sub-F. These studies revealed that ERK2 undergoes sulfenylation at C159 on its D-recruitment site surface and that this modification modulates ERK2 activity differentially between substrates. Integrated biochemical, computational, and mutational analyses suggest a plausible mechanism for peroxide-dependent changes in ERK2-substrate interactions. Interestingly, oxidation decreased ERK2's affinity for some D-site ligands while increasing its affinity for others. Finally, oxidation by signal-generated peroxide enhanced ERK1/2's ability to phosphorylate ribosomal S6 kinase A1 (RSK1) in HeLa cells. Together, these studies lay the foundation for examining crosstalk between redox- and phosphorylation-dependent signaling at the level of kinase-substrate selection.

HyperCys: A Structure- and Sequence-Based Predictor of Hyper-Reactive Druggable Cysteines

The cysteine side chain has a free thiol group, making it the amino acid residue most often covalently modified by small molecules possessing weakly electrophilic warheads, thereby prolonging on-target residence time and reducing the risk of idiosyncratic drug toxicity. However, not all cysteines are equally reactive or accessible. Hence, to identify targetable cysteines, we propose a novel ensemble stacked machine learning (ML) model to predict hyper-reactive druggable cysteines, named HyperCys. First, the pocket, conservation, structural and energy profiles, and physicochemical properties of (non)covalently bound cysteines were collected from both protein sequences and 3D structures of protein-ligand complexes. Then, we established the HyperCys ensemble stacked model by integrating six different ML models, including K-nearest neighbors, support vector machine, light gradient boost machine, multi-layer perceptron classifier, random forest, and the meta-classifier model logistic regression. Finally, based on the hyper-reactive cysteines' classification accuracy and other metrics, the results for different feature group combinations were compared. The results show that the accuracy, F1 score, recall score, and ROC AUC values of HyperCys are 0.784, 0.754, 0.742, and 0.824, respectively, after performing 10-fold CV with the best window size. Compared to traditional ML models with only sequenced-based features or only 3D structural features, HyperCys is more accurate at predicting hyper-reactive druggable cysteines. It is anticipated that HyperCys will be an effective tool for discovering new potential reactive cysteines in a wide range of nucleophilic proteins and will provide an important contribution to the design of targeted covalent inhibitors with high potency and selectivity.

Aurora Kinase A Regulation by Cysteine Oxidative Modification

Aurora kinase A (AURKA), which is a member of serine/threonine kinase family, plays a critical role in regulating mitosis. AURKA has drawn much attention as its dysregulation is critically associated with various cancers, leading to the development of AURKA inhibitors, a new class of anticancer drugs. As the spatiotemporal activity of AURKA critically depends on diverse intra- and inter-molecular factors, including its interaction with various protein cofactors and post-translational modifications, each of these pathways should be exploited for the development of a novel class of AURKA inhibitors other than ATP-competitive inhibitors. Several lines of evidence have recently shown that redox-active molecules can modify the cysteine residues located on the kinase domain of AURKA, thereby regulating its activity. In this review, we present the current understanding of how oxidative modifications of cysteine residues of AURKA, induced by redox-active molecules, structurally and functionally regulate AURKA and discuss their implications in the discovery of novel AURKA inhibitors.

Molecular determinants of acrylamide neurotoxicity through covalent docking

Acrylamide (ACR) is formed during food processing by Maillard reaction between sugars and proteins at high temperatures. It is also used in many industries, from water waste treatment to manufacture of paper, fabrics, dyes and cosmetics. Unfortunately, cumulative exposure to acrylamide, either from diet or at the workplace, may result in neurotoxicity. Such adverse effects arise from covalent adducts formed between acrylamide and cysteine residues of several neuronal proteins via a Michael addition reaction. The molecular determinants of acrylamide reactivity and its impact on protein function are not completely understood. Here we have compiled a list of acrylamide protein targets reported so far in the literature in connection with neurotoxicity and performed a systematic covalent docking study. Our results indicate that acrylamide binding to cysteine is favored in the presence of nearby positively charged amino acids, such as lysines and arginines. For proteins with more than one reactive Cys, docking scores were able to discriminate between the primary ACR modification site and secondary sites modified only at high ACR concentrations. Therefore, docking scores emerge as a potential filter to predict Cys reactivity against acrylamide. Inspection of the ACR-protein complex structures provides insights into the putative functional consequences of ACR modification, especially for non-enzyme proteins. Based on our study, covalent docking is a promising computational tool to predict other potential protein targets mediating acrylamide neurotoxicity.

Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network

Covalent ligands have attracted increasing attention due to their unique advantages, such as long residence time, high selectivity, and strong binding affinity. They also show promise for targets where previous efforts to identify noncovalent small molecule inhibitors have failed. However, our limited knowledge of covalent binding sites has hindered the discovery of novel ligands. Therefore, developing in silico methods to identify covalent binding sites is highly desirable. Here, we propose DeepCoSI, the first structure-based deep graph learning model to identify ligandable covalent sites in the protein. By integrating the characterization of the binding pocket and the interactions between each cysteine and the surrounding environment, DeepCoSI achieves state-of-the-art predictive performances. The validation on two external test sets which mimic the real application scenarios shows that DeepCoSI has strong ability to distinguish ligandable sites from the others. Finally, we profiled the entire set of protein structures in the RCSB Protein Data Bank (PDB) with DeepCoSI to evaluate the ligandability of each cysteine for covalent ligand design, and made the predicted data publicly available on website.

Activation mechanism of PINK1

Mutations in the protein kinase PINK1 lead to defects in mitophagy and cause autosomal recessive early onset Parkinson's disease^1,2. PINK1 has many unique features that enable it to phosphorylate ubiquitin and the ubiquitin-like domain of Parkin^3-9. Structural analysis of PINK1 from diverse insect species^10-12 with and without ubiquitin provided snapshots of distinct structural states yet did not explain how PINK1 is activated. Here we elucidate the activation mechanism of PINK1 using crystallography and cryo-electron microscopy (cryo-EM). A crystal structure of unphosphorylated Pediculus humanus corporis (Ph; human body louse) PINK1 resolves an N-terminal helix, revealing the orientation of unphosphorylated yet active PINK1 on the mitochondria. We further provide a cryo-EM structure of a symmetric PhPINK1 dimer trapped during the process of trans-autophosphorylation, as well as a cryo-EM structure of phosphorylated PhPINK1 undergoing a conformational change to an active ubiquitin kinase state. Structures and phosphorylation studies further identify a role for regulatory PINK1 oxidation. Together, our research delineates the complete activation mechanism of PINK1, illuminates how PINK1 interacts with the mitochondrial outer membrane and reveals how PINK1 activity may be modulated by mitochondrial reactive oxygen species.

Protein Modifications: From Chemoselective Probes to Novel Biocatalysts

Chemical reactions can be performed to covalently modify specific residues in proteins. When applied to native enzymes, these chemical modifications can greatly expand the available set of building blocks for the development of biocatalysts. Nucleophilic canonical amino acid sidechains are the most readily accessible targets for such endeavors. A rich history of attempts to design enhanced or novel enzymes, from various protein scaffolds, has paved the way for a rapidly developing field with growing scientific, industrial, and biomedical applications. A major challenge is to devise reactions that are compatible with native proteins and can selectively modify specific residues. Cysteine, lysine, N-terminus, and carboxylate residues comprise the most widespread naturally occurring targets for enzyme modifications. In this review, chemical methods for selective modification of enzymes will be discussed, alongside with examples of reported applications. We aim to highlight the potential of such strategies to enhance enzyme function and create novel semisynthetic biocatalysts, as well as provide a perspective in a fast-evolving topic.

Synthesis of small molecules targeting paclitaxel-induced MyD88 expression in triple-negative breast cancer cell lines

Acquired paclitaxel (PTX) chemoresistance in triple-negative breast cancer (TNBC) can be inferred from the overexpression of toll-like receptor 4 (TLR4) and myeloid differentiation primary response 88 (MyD88) proteins and the activation of the TLR4/MyD88 cascading signalling pathway. Finding a new inhibitor that can attenuate the activation of this pathway is a novel strategy for reducing PTX chemoresistance. In this study, a series of small molecule compounds were synthesised and tested in combination with PTX against TNBC cells. The trimethoxy-substituted compound significantly decreased MyD88 overexpression and improved PTX activity in MDA-MB-231^TLR4+ cells but not in HCC^TLR4- cells. On the contrary, the trifluoromethyl-substituted compound with PTX synergistically improved the growth inhibition in both TNBC subtypes. The fluorescence titrations indicated that both compounds could bind with MD2 with good and comparable binding affinities. This was further supported by docking analysis, in which both compounds fit perfectly well and form some critical binding interactions with MD2, an essential lipid-binding accessory to TLR4 involved in activating the TLR-4/MyD88-dependent pathway.

DeepCys: Structure-based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains

Cysteine (Cys) is the most reactive amino acid participating in a wide range of biological functions. In-silico predictions complement the experiments to meet the need of functional characterization. Multiple Cys function prediction algorithm is scarce, in contrast to specific function prediction algorithms. Here we present a deep neural network-based multiple Cys function prediction, available on web-server (DeepCys) (https://deepcys.herokuapp.com/). DeepCys model was trained and tested on two independent datasets curated from protein crystal structures. This prediction method requires three inputs, namely, PDB identifier (ID), chain ID and residue ID for a given Cys and outputs the probabilities of four cysteine functions, namely, disulphide, metal-binding, thioether and sulphenylation and predicts the most probable Cys function. The algorithm exploits the local and global protein properties, like, sequence and secondary structure motifs, buried fractions, microenvironments and protein/enzyme class. DeepCys outperformed most of the multiple and specific Cys function algorithms. This method can predict maximum number of cysteine functions. Moreover, for the first time, explicitly predicts thioether function. This tool was used to elucidate the cysteine functions on domains of unknown functions belonging to cytochrome C oxidase subunit-II like transmembrane domains. Apart from the web-server, a standalone program is also available on GitHub (https://github.com/vam-sin/deepcys).

Selective and Effective: Current Progress in Computational Structure-Based Drug Discovery of Targeted Covalent Inhibitors

Targeted covalent inhibitors are currently showing great promise for systems that are normally difficult to target with small molecule therapies. This renewed interest has spurred the refinement of existing computational methods as well as the designof new ones, expanding the toolbox for discovery and optimization of selectiveand effective covalent inhibitors. Commonly applied approaches are covalentdocking methods that predict the conformation of the covalent complex with known residues. More recently, a new predictive method, reactive docking, was developed, building on the growing corpus of data generated by large proteomics experiments. This method was successfully used in several 'inverse drug discovery' programs that use high-throughput techniques to isolate effective compounds based on screening of entire compound libraries based on desired phenotypes.

Aurora A regulation by reversible cysteine oxidation reveals evolutionarily conserved redox control of Ser/Thr protein kinase activity

Reactive oxygen species (ROS) are physiological mediators of cellular signaling and play potentially damaging roles in human diseases. In this study, we found that the catalytic activity of the Ser/Thr kinase Aurora A was inhibited by the oxidation of a conserved cysteine residue (Cys290) that lies adjacent to Thr288, a critical phosphorylation site in the activation segment. Cys is present at the equivalent position in ~100 human Ser/Thr kinases, a residue that we found was important not only for the activity of human Aurora A but also for that of fission yeast MAPK-activated kinase (Srk1) and PKA (Pka1). Moreover, the presence of this conserved Cys predicted biochemical redox sensitivity among a cohort of human CAMK, AGC, and AGC-like kinases. Thus, we predict that redox modulation of the conserved Cys290 of Aurora A may be an underappreciated regulatory mechanism that is widespread in eukaryotic Ser/Thr kinases. Given the key biological roles of these enzymes, these findings have implications for understanding physiological and pathological responses to ROS and highlight the importance of protein kinase regulation through multivalent modification of the activation segment.

Predicting Reactive Cysteines with Implicit-Solvent-Based Continuous Constant pH Molecular Dynamics in Amber

Cysteines existing in the deprotonated thiolate form or having a tendency to become deprotonated are important players in enzymatic and cellular redox functions and frequently exploited in covalent drug design; however, most computational studies assume cysteines as protonated. Thus, developing an efficient tool that can make accurate and reliable predictions of cysteine protonation states is timely needed. We recently implemented a generalized Born (GB) based continuous constant pH molecular dynamics (CpHMD) method in Amber for protein pKa calculations on CPUs and GPUs. Here we benchmark the performance of GB-CpHMD for predictions of cysteine pKa's and reactivities using a data set of 24 proteins with both down- and upshifted cysteine pKa's. We found that 10 ns single-pH or 4 ns replica-exchange CpHMD titrations gave root-mean-square errors of 1.2-1.3 and correlation coefficients of 0.8-0.9 with respect to experiment. The accuracy of predicting thiolates or reactive cysteines at physiological pH with single-pH titrations is 86 or 81% with a precision of 100 or 90%, respectively. This performance well surpasses the traditional structure-based methods, particularly a widely used empirical pKa tool that gives an accuracy less than 50%. We discuss simulation convergence, dependence on starting structures, common determinants of the pKa downshifts and upshifts, and the origin of the discrepancies from the structure-based calculations. Our work suggests that CpHMD titrations can be performed on a desktop computer equipped with a single GPU card to predict cysteine protonation states for a variety of applications, from understanding biological functions to covalent drug design.

NEDD9 targets COL3A1 to promote endothelial fibrosis and pulmonary arterial hypertension

Germline mutations involving small mothers against decapentaplegic-transforming growth factor-β (SMAD-TGF-β) signaling are an important but rare cause of pulmonary arterial hypertension (PAH), which is a disease characterized, in part, by vascular fibrosis and hyperaldosteronism (ALDO). We developed and analyzed a fibrosis protein-protein network (fibrosome) in silico, which predicted that the SMAD3 target neural precursor cell expressed developmentally down-regulated 9 (NEDD9) is a critical ALDO-regulated node underpinning pathogenic vascular fibrosis. Bioinformatics and microscale thermophoresis demonstrated that oxidation of Cys18 in the SMAD3 docking region of NEDD9 impairs SMAD3-NEDD9 protein-protein interactions in vitro. This effect was reproduced by ALDO-induced oxidant stress in cultured human pulmonary artery endothelial cells (HPAECs), resulting in impaired NEDD9 proteolytic degradation, increased NEDD9 complex formation with Nk2 homeobox 5 (NKX2-5), and increased NKX2-5 binding to COL3A1 Up-regulation of NEDD9-dependent collagen III expression corresponded to changes in cell stiffness measured by atomic force microscopy. HPAEC-derived exosomal signaling targeted NEDD9 to increase collagen I/III expression in human pulmonary artery smooth muscle cells, identifying a second endothelial mechanism regulating vascular fibrosis. ALDO-NEDD9 signaling was not affected by treatment with a TGF-β ligand trap and, thus, was not contingent on TGF-β signaling. Colocalization of NEDD9 with collagen III in HPAECs was observed in fibrotic pulmonary arterioles from PAH patients. Furthermore, NEDD9 ablation or inhibition prevented fibrotic vascular remodeling and pulmonary hypertension in animal models of PAH in vivo. These data identify a critical TGF-β-independent posttranslational modification that impairs SMAD3-NEDD9 binding in HPAECs to modulate vascular fibrosis and promote PAH.

Using in vivo oxidation status of one- and two-component redox relays to determine H2O2 levels linked to signaling and toxicity

Background

Hydrogen peroxide (H₂O₂) is generated as a by-product of metabolic reactions during oxygen use by aerobic organisms, and can be toxic or participate in signaling processes. Cells, therefore, need to be able to sense and respond to H₂O₂ in an appropriate manner. This is often accomplished through thiol switches: Cysteine residues in proteins that can act as sensors, and which are both scarce and finely tuned. Bacteria and eukaryotes use different types of such sensors—either a one-component (OxyR) or two-component (Pap1-Tpx1) redox relay, respectively. However, the biological significance of these two different signaling modes is not fully understood, and the concentrations and peroxides driving those types of redox cascades have not been determined, nor the intracellular H₂O₂ levels linked to toxicity. Here we elucidate the characteristics, rates, and dynamic ranges of both systems.

Results

By comparing the activation of both systems in fission yeast, and applying mathematical equations to the experimental data, we estimate the toxic threshold of intracellular H₂O₂ able to halt aerobic growth, and the temporal gradients of extracellular to intracellular peroxides. By calculating both the oxidation rates of OxyR and Tpx1 by peroxides, and their reduction rates by the cellular redoxin systems, we propose that, while Tpx1 is a sensor and an efficient H₂O₂ scavenger because it displays fast oxidation and reduction rates, OxyR is strictly a H₂O₂ sensor, since its reduction kinetics are significantly slower than its oxidation by peroxides, and therefore, it remains oxidized long enough to execute its transcriptional role. We also show that these two paradigmatic H₂O₂-sensing models are biologically similar at pre-toxic peroxide levels, but display strikingly different activation behaviors at toxic doses.

Conclusions

Both Tpx1 and OxyR contain thiol switches, with very high reactivity towards peroxides. Nevertheless, the fast reduction of Tpx1 defines it as a scavenger, and this efficient recycling dramatically changes the Tpx1-Pap1 response to H₂O₂ and connects H₂O₂ sensing to the redox state of the cell. In contrast, OxyR is a true H₂O₂ sensor but not a scavenger, being partially insulated from the cellular electron donor capacity.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0523-6) contains supplementary material, which is available to authorized users.

PP1:Tautomycetin Complex Reveals a Path toward the Development of PP1-Specific Inhibitors

Selective inhibitors for each serine/threonine phosphatase (PPP) are essential to investigate the biological actions of PPPs and to guide drug development. Biologically diverse organisms (e.g., cyanobacteria, dinoflagellates, beetles) produce structurally distinct toxins that are catalytic inhibitors of PPPs. However, most toxins exhibit little selectivity, typically inhibiting multiple family members with similar potencies. Thus, the use of these toxins as chemical tools to study the relationship between individual PPPs and their biological substrates, and how disruptions in these relationships contributes to human disease, is severely limited. Here, we show that tautomycetin (TTN) is highly selective for a single PPP, protein phosphatase 1 (PP1/PPP1C). Our structure of the PP1:TTN complex reveals that PP1 selectivity is defined by a covalent bond between TTN and a PP1-specific cysteine residue, Cys127. Together, these data provide key molecular insights needed for the development of novel probes targeting single PPPs, especially PP1.

Proteomic Characterization of Reversible Thiol Oxidations in Proteomes and Proteins

SIGNIFICANCE

Reactive oxygen species are produced during normal metabolism in cells, and their excesses have been implicated in protein damage and toxicity, as well as in the activation of signaling events. In particular, hydrogen peroxide participates in the regulation of different physiological processes as well as in the induction of antioxidant cascades, and often the redox molecular events triggering these pathways are based on reversible cysteine (Cys) oxidation. Recent Advances: Increases in peroxides can cause the accumulation of reversible Cys oxidations in proteomes, which may be either protecting thiols from irreversible oxidations or may just be reporters of future toxicity. It is also becoming clear, however, that only a few proteins, such as the bacterial OxyR or peroxidases, can suffer direct oxidation of their Cys residues by hydrogen peroxide and, therefore, may be the only true sensors initiating signaling events.

CRITICAL ISSUES

We will in this study describe some of the methodologies used to characterize at the proteome level reversible thiol oxidations, specifically those combining gel-free approaches with mass spectrometry. In the second part of this review, we will summarize some of the electrophoretic and proteomic techniques used to monitor Cys oxidation at the protein level, needed to confirm that a protein contains redox Cys involved in signaling relays, using as examples some of the best characterized redox sensors such as bacterial OxyR or yeast Tpx1/Pap1.

FUTURE DIRECTIONS

While Cys oxidations are often detected in proteomes and in specific proteins, major efforts have to be made to establish that they are physiologically relevant. Antioxid. Redox Signal. 26, 329-344.

In Silico Template Selection of Short Antimicrobial Peptide Viscotoxin for Improving Its Antimicrobial Efficiency in Development of Potential Therapeutic Drugs

Rapid increase in antibiotic resistance has posed a worldwide threat, due to increased mortality, morbidity, and expenditure caused by antibiotic-resistant microbes. Recent development of the antimicrobial peptides like viscotoxin (Vt) has been successfully comprehended as a substitute for classical antibiotics. A structurally stable peptide, Vt can enhance antimicrobial property and can be used for various developmental purposes. Thus, structural stability among the antimicrobial peptides, Vt A1 (3C8P), A2 (1JMN), A3 (1ED0), B (1JMP), and C (1ORL) of Viscus album was computationally analyzed. In specific, the static confirmation of VtA3 showed high number of intramolecular interactions, along with an increase in hydrophobicity than others comparatively. Further, conformational sampling was used to analyze various geometrical parameters such as root mean square deviation, root mean square fluctuation, radius of gyration, and ovality which also revealed the structural stability of VtA3. Moreover, the statistically validated contours of surface area, lipophilicity, and distance constraints of disulfide bonds also supported the priority of VtA3 with respect to stability. Finally, the functional activity of peptides was accessed by computing their free energy of membrane association and membrane interactions, which defined VtA3 as functionally stable. Currently, peptide-based antibiotics and nanoparticles have attracted the pharmaceutical industries for their potential therapeutic applications. Thereby, it is proposed that viscotoxin A3 (1ED0) could be used as a preeminent template for scaffolding potentially efficient antimicrobial peptide-based drugs and nanomaterials in future.