In-silico design and molecular docking evaluation of peptides derivatives from bacteriocins and porcine beta defensin-2 as inhibitors of Hepatitis E virus capsid protein

In silico bioprospecting of receptors associated with the mechanism of action of Rondonin, an antifungal peptide from spider Acanthoscurria rondoniae haemolymph

Multiple drug-resistant fungal species are associated with the development of diseases. Thus, more efficient drugs for the treatment of these aetiological agents are needed. Rondonin is a peptide isolated from the haemolymph of the spider Acanthoscurria rondoniae. Previous studies have shown that this peptide has antifungal activity against Candida sp. and Trichosporon sp. strains, acting on their genetic material. However, the molecular targets involved in its biological activity have not yet been described. Bioinformatics tools were used to determine the possible targets involved in the biological activity of Rondonin. The PharmMapper server was used to search for microorganismal targets of Rondonin. The PatchDock server was used to perform the molecular docking. UCSF Chimera software was used to evaluate these intermolecular interactions. In addition, the I-TASSER server was used to predict the target ligand sites. Then, these predictions were contrasted with the sites previously described in the literature. Molecular dynamics simulations were conducted for two promising complexes identified from the docking analysis. Rondonin demonstrated consistency with the ligand sites of the following targets: outer membrane proteins F (id: 1MPF) and A (id: 1QJP), which are responsible for facilitating the passage of small molecules through the plasma membrane; the subunit of the flavoprotein fumarate reductase (id: 1D4E), which is involved in the metabolism of nitrogenous bases; and the ATP-dependent Holliday DNA helicase junction (id: 1IN4), which is associated with histone proteins that package genetic material. Additionally, the molecular dynamics results indicated the stability of the interaction of Rondonin with 1MPF and 1IN4 during a 10 ns simulation. These interactions corroborate with previous in vitro studies on Rondonin, which acts on fungal genetic material without causing plasma membrane rupture. Therefore, the bioprospecting methods used in this research were considered satisfactory since they were consistent with previous results obtained via in vitro experimentation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00224-1.

FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses

Antiviral peptides (AVPs) are widely found in animals and plants, with high specificity and strong sensitivity to drug-resistant viruses. However, due to the great heterogeneity of different viruses, most of the AVPs have specific antiviral activities. Therefore, it is necessary to identify the specific activities of AVPs on virus types. Most existing studies only identify AVPs, with only a few studies identifying subclasses by training multiple binary classifiers. We develop a two-stage prediction tool named FFMAVP that can simultaneously predict AVPs and their subclasses. In the first stage, we identify whether a peptide is AVP or not. In the second stage, we predict the six virus families and eight species specifically targeted by AVPs based on two multiclass tasks. Specifically, the feature extraction module in the two-stage task of FFMAVP adopts the same neural network structure, in which one branch extracts features based on amino acid feature descriptors and the other branch extracts sequence features. Then, the two types of features are fused for the following task. Considering the correlation between the two tasks of the second stage, a multitask learning model is constructed to improve the effectiveness of the two multiclass tasks. In addition, to improve the effectiveness of the second stage, the network parameters trained through the first-stage data are used to initialize the network parameters in the second stage. As a demonstration, the cross-validation results, independent test results and visualization results show that FFMAVP achieves great advantages in both stages.

Identification of Plant Peptides as Novel Inhibitors of Orthohepevirus A (HEV) Capsid Protein by Virtual Screening

Hepatitis E virus (HEV) is the notable causative agent of acute and chronic hepatic, renal, pancreatic, neurological, and hematopoietic blood cell infections with high risk in immunocompromised patients. Hepatic failure is mostly documented among adults, pregnant women, and patients with preexisting liver disease. HEV is a positive sense RNA virus of 7.2 kb genome size with typically three open reading frames (ORFs) which play essential roles in viral replication, genome assembly, and transcription. The mutational substitution in the viral RNA genome makes more it difficult to understand the actual relationship in the host–virus association. ORFs of HEV encode different structural and non-structural proteins and one of them is the capsid protein which is coded by ORF2. The capsid protein mediates the encapsulation of the viral genome as well as being involved in virion assembly. In the current study, the ligand-based docking approach was employed to inhibit the active amino acids of the viral capsid protein. Depending upon S-score, ADMET profiling, and drug scanning, the top ten tetrapeptides were selected as potential drug candidates with no toxicity counter to HEV receptor protein. The S-score or docking score is a mathematical function which predicts the binding affinities of docked complexes. The binding affinity of the predicted drug–target complexes helps in the selectivity of the desired compound as a potential drug. The best two selected peptides (i.e., TDGH with S-score of −8.5 and EGDE with S-score of −8.0) interacted with the active site amino acids of the capsid protein (i.e., Arg399, Gln420, and Asp444). The molecular dynamics simulations of RMSD trajectories of TDGH–capsid protein and EDGE–capsid protein have revealed that both docked complexes were structurally stable. The study revealed that these tetrapeptides would serve as strong potential inhibitors and a starting point for the development of new drug molecules against the HEV capsid protein. In future, in vivo studies are needed to explore selected peptides as potential drug candidates.

Anurans against SARS-CoV-2: A review of the potential antiviral action of anurans cutaneous peptides

At the end of 2019, in China, clinical signs and symptoms of unknown etiology have been reported in several patients whose sample sequencing revealed pneumonia caused by the SARS-CoV-2 virus. COVID-19 is a disease triggered by this virus, and in 2020, the World Health Organization declared it a pandemic. Since then, efforts have been made to find effective therapeutic agents against this disease. Identifying novel natural antiviral drugs can be an alternative to treatment. For this reason, antimicrobial peptides secreted by anurans' skin have gained attention for showing a promissory antiviral effect. Hence, this review aimed to elucidate how and which peptides secreted by anurans' skin can be considered therapeutic agents to treat or prevent human viral infectious diseases. Through a literature review, we attempted to identify potential antiviral frogs' peptides to combat COVID-19. As a result, the Magainin-1 and -2 peptides, from the Magainin family, the Dermaseptin-S9, from the Dermaseptin family, and Caerin 1.6 and 1.10, from the Caerin family, are molecules that already showed antiviral effects against SARS-CoV-2 in silico. In addition to these peptides, this review suggests that future studies should use other families that already have antiviral action against other viruses, such as Brevinins, Maculatins, Esculentins, Temporins, and Urumins. To apply these peptides as therapeutic agents, experimental studies with peptides already tested in silico and new studies with other families not tested yet should be considered.

COVID-19: A systematic review and update on prevention, diagnosis, and treatment

Since the rapid onset of the COVID-19 or SARS-CoV-2 pandemic in the world in 2019, extensive studies have been conducted to unveil the behavior and emission pattern of the virus in order to determine the best ways to diagnosis of virus and thereof formulate effective drugs or vaccines to combat the disease. The emergence of novel diagnostic and therapeutic techniques considering the multiplicity of reports from one side and contradictions in assessments from the other side necessitates instantaneous updates on the progress of clinical investigations. There is also growing public anxiety from time to time mutation of COVID-19, as reflected in considerable mortality and transmission, respectively, from delta and Omicron variants. We comprehensively review and summarize different aspects of prevention, diagnosis, and treatment of COVID-19. First, biological characteristics of COVID-19 were explained from diagnosis standpoint. Thereafter, the preclinical animal models of COVID-19 were discussed to frame the symptoms and clinical effects of COVID-19 from patient to patient with treatment strategies and in-silico/computational biology. Finally, the opportunities and challenges of nanoscience/nanotechnology in identification, diagnosis, and treatment of COVID-19 were discussed. This review covers almost all SARS-CoV-2-related topics extensively to deepen the understanding of the latest achievements (last updated on January 11, 2022).

Bacteriocin producing microbes with bactericidal activity against multidrug resistant pathogens

BACKGROUND

Bacteriocins are proteins or peptides synthesized by bacteria that show inhibitory or killing activities against various bacteria. Bacteriocins are mainly considered for effective alternatives to different commercial antibiotics, preservatives in the food and pharmaceutical industries.

OBJECTIVES

To screen and analyze novel bacteriocin-producing bacteria from the fermented food shidal for antibacterial activity against food pathogens and their molecular interactions studied through computationally.

METHODS

In this study, a strain Lactobacillus plantarum LA21 was isolated from the fermented food shidal identified based on morphological, biochemical, and 16S rDNA gene sequencing. The potent bacterium was subjected to improve bacteriocins production and characterized. Antimicrobial activity against drug-resistant bacteria and minimum inhibitory concentration (MIC) were determined. The bacteriocin was treated with proteolytic enzymes, and the mechanism of action on food pathogens was analyzed. Molecular docking studies were carried out as GLIDE module in the maestro tool of Schrodinger Software.

RESULTS

Bacteriocin was effective against pathogens such as Bacillus pumilus, Bacillus amyloliquefaciens, Staphylococcus aureus, and Listeria monocytogenes, with the most negligible MIC value was detected in L. monocytogenes. Furthermore, the depleted viability of bacterial cells indicated bacteriocin-induced cell lysis in L. monocytogenes via bactericidal activity. In addition, proteolytic enzyme digested bacteriocins revealed bacteriocin-like substances. Finally, molecular docking was performed to study the interactions between the targets and bacteriocins, results in relative intense contact with minimally 3 Å distance.

CONCLUSIONS

The characteristic features of these bacteriocin-like molecules revealed that L. plantarum LA21 is a novel bacteriocin-producing bacterial strain to prepare novel antimicrobial drugs, feed additives or preservatives for future use in livestock and food industries.

In Silico Mutagenesis-Based Remodelling of SARS-CoV-1 Peptide (ATLQAIAS) to Inhibit SARS-CoV-2: Structural-Dynamics and Free Energy Calculations

The prolific spread of COVID-19 caused by a novel coronavirus (SARS-CoV-2) from its epicenter in Wuhan, China, to every nook and cranny of the world after December 2019, jeopardize the prevailing health system in the world and has raised serious concerns about human safety. Multi-directional efforts are made to design small molecule inhibitors, and vaccines and many other therapeutic options are practiced, but their final therapeutic potential is still to be tested. Using the old drug or vaccine or peptides could aid this process to avoid such long experimental procedures. Hence, here, we have repurposed a small peptide (ATLQAIAS) from the previous study, which reported the inhibitory effects of this peptide. We used in silico mutagenesis approach to design more peptides from the native wild peptide, which revealed that substitutions (T2W, T2Y, L3R, and A5W) could increase the binding affinity of the peptide towards the 3CLpro. Furthermore, using MD simulation and free energy calculation confirmed its dynamics stability and stronger binding affinities. Per-residue energy decomposition analysis revealed that the specified substitution significantly increased the binding affinity at the residue level. Our wide-ranging analyses of binding affinities disclosed that our designed peptide owns the potential to hinder the SARS-CoV-2 and will reduce the progression of SARS-CoV-2-borne pneumonia. Our research strongly suggests the experimental and clinical validation of these peptides to curtail the recent corona outbreak.

HantavirusesDB: Vaccinomics and RNA-based therapeutics database for the potentially emerging human respiratory pandemic agents

Hantaviruses are etiological agents of several severe respiratory illnesses in humans and their human-to-human transmission has been reported. To cope with any potential pandemic, this group of viruses needs further research and a data platform. Therefore, herein we developed a database "HantavirusesDB (HVdb)", where genomics, proteomics, immune resource, RNAi based therapeutics and information on the 3D structures of druggable targets of the Orthohantaviruses are provided on a single platform. The database allows the researchers to effectively map the therapeutic strategies by designing multi-epitopes subunit vaccine and RNA based therapeutics. Moreover, the ease of the web interface allow the users to retrieve specific information from the database. Because of the high quality and excellent functionality of the HVdb, therapeutic research of Hantaviruses can be accelerated, and data analysis might be a foundation to design better treatment strategies targeting the hantaviruses. The database is accessible at http://hvdb.dqweilab-sjtu.com/index.php.

In Silico Approaches for the Prediction and Analysis of Antiviral Peptides: A Review

In light of the growing resistance toward current antiviral drugs, efforts to discover novel and effective antiviral therapeutic agents remain a pressing scientific effort. Antiviral peptides (AVPs) represent promising therapeutic agents due to their extraordinary advantages in terms of potency, efficacy and pharmacokinetic properties. The growing volume of newly discovered peptide sequences in the post-genomic era requires computational approaches for timely and accurate identification of AVPs. Machine learning (ML) methods such as random forest and support vector machine represent robust learning algorithms that are instrumental in successful peptide-based drug discovery. Therefore, this review summarizes the current state-of-the-art application of ML methods for identifying AVPs directly from the sequence information. We compare the efficiency of these methods in terms of the underlying characteristics of the dataset used along with feature encoding methods, ML algorithms, cross-validation methods and prediction performance. Finally, guidelines for the development of robust AVP models are also discussed. It is anticipated that this review will serve as a useful guide for the design and development of robust AVP and related therapeutic peptide predictors in the future.

The Antiviral and Virucidal Activities of Voacangine and Structural Analogs Extracted from Tabernaemontana cymosa Depend on the Dengue Virus Strain

Currently, no specific licensed antiviral exists for treating the illness caused by dengue virus (DENV). Therefore, the search for compounds of natural origin with antiviral activity is an important area of research. In the present study, three compounds were isolated and identified from seeds of Tabernaemontana cymosa plants. The in vitro antiviral effect of those compounds and voacangine against different DENV strains was assessed using different experimental approaches: compounds added before the infection (Pre), at the same time with the virus (Trans), after the infection (Post) or compounds present in all moments of the experiment (Pre-Trans-Post, Combined treatment). In silico studies (docking and molecular dynamics) were also performed to explain the possible antiviral mechanisms. The identified compounds were three structural analogs of voacangine (voacangine-7-hydroxyindolenine, rupicoline and 3-oxo-voacangine). In the Pre-treatment, only voacangine-7-hydroxyindolenine and rupicoline inhibited the infection caused by the DENV-2/NG strain (16.4% and 29.6% infection, respectively). In the Trans-treatment approach, voacangine, voacangine-7-hydroxyindolenine and rupicoline inhibited the infection in both DENV-2/NG (11.2%, 80.4% and 75.7% infection, respectively) and DENV-2/16681 infection models (73.7%, 74.0% and 75.3% infection, respectively). The latter strain was also inhibited by 3-oxo-voacangine (82.8% infection). Moreover, voacangine (most effective virucidal agent) was also effective against one strain of DENV-1 (DENV-1/WestPac/74) and against the third strain of DENV-2 (DENV-2/S16803) (48.5% and 32.4% infection, respectively). Conversely, no inhibition was observed in the post-treatment approach. The last approach (combined) showed that voacangine, voacangine-7-hydroxyindolenine and rupicoline inhibited over 90% of infections (3.5%, 6.9% and 3.5% infection, respectively) of both strains (DENV-2/NG and DENV-2/16681). The free energy of binding obtained with an in silico approach was favorable for the E protein and compounds, which ranged between −5.1 and −6.3 kcal/mol. Finally, the complex formed between DENV-2 E protein and the best virucidal compound was stable for 50 ns. Our results show that the antiviral effect of indole alkaloids derived from T. cymose depends on the serotype and the virus strain.

Probiotics at War Against Viruses: What Is Missing From the Picture?

Our world is now facing a multitude of novel infectious diseases. Bacterial infections are treated with antibiotics, albeit with increasing difficulty as many of the more common causes of infection have now developed broad spectrum antimicrobial resistance. However, there is now an even greater challenge from both old and new viruses capable of causing respiratory, enteric, and urogenital infections. Reports of viruses resistant to frontline therapeutic drugs are steadily increasing and there is an urgent need to develop novel antiviral agents. Although this all makes sense, it seems rather strange that relatively little attention has been given to the antiviral capabilities of probiotics. Over the years, beneficial strains of lactic acid bacteria (LAB) have been successfully used to treat gastrointestinal, oral, and vaginal infections, and some can also effect a reduction in serum cholesterol levels. Some probiotics prevent gastrointestinal dysbiosis and, by doing so, reduce the risk of developing secondary infections. Other probiotics exhibit anti-tumor and immunomodulating properties, and in some studies, antiviral activities have been reported for probiotic bacteria and/or their metabolites. Unfortunately, the mechanistic basis of the observed beneficial effects of probiotics in countering viral infections is sometimes unclear. Interestingly, in COVID-19 patients, a clear decrease has been observed in cell numbers of Lactobacillus and Bifidobacterium spp., both of which are common sources of intestinal probiotics. The present review, specifically motivated by the need to implement effective new counters to SARS-CoV-2, focusses attention on viruses capable of co-infecting humans and other animals and specifically explores the potential of probiotic bacteria and their metabolites to intervene with the process of virus infection. The goal is to help to provide a more informed background for the planning of future probiotic-based antiviral research.

Porcine β-defensin 2 inhibits proliferation of pseudorabies virus in vitro and in transgenic mice

Background

Porcine β-defensin 2 (PBD-2), produced by host cells, is an antimicrobial cysteine-rich cationic peptide with multi-functions. Previous studies have demonstrated that PBD-2 can kill various bacteria, regulate host immune responses and promote growth of piglets. However, the antiviral role of PBD-2 is rarely investigated. This study aimed to reveal the antiviral ability of PBD-2 against pseudorabies virus (PRV), the causative pathogen of Aujeszky’s disease, in PK-15 cells and in a PBD-2 expressing transgenic (TG) mouse model.

Methods

In this study, the cytotoxicity of PBD-2 on PK-15 cells was measured by CCK-8 assay. PK-15 cells were incubated with PRV pre-treated with different concentrations of PBD-2 and PRV titers in cell culture supernatants were determined by real-time quantitative PCR (RT-qPCR). TG mice and wild-type (WT) mice were intraperitoneally injected with PRV and the survival rate was recorded for 10 days. Meanwhile, tissue lesions in brain, spleen and liver of infected mice were observed and the viral loads of PRV in brain, liver and lung were analyzed by RT-qPCR.

Results

PBD-2 at a maximum concentration of 80 μg/mL displayed no significant cytotoxicity on PK-15 cells. A threshold concentration of PBD-2 at 40 μg/mL was required to inhibit PRV proliferation in PK-15 cells. The survival rate in PBD-2 TG mice was 50% higher than that of WT mice. In addition, TG mice showed alleviated tissue lesions in brain, spleen and liver compared with their WT littermates after PRV challenge, while viral loads of PRV in brain, liver and lung of TG mice were significantly lower than that of WT mice.

Conclusions

PBD-2 could inhibit PRV proliferation in PK-15 cells and protect mice from PRV infection, which confirmed the antiviral ability of PBD-2 both in vitro and in vivo. The application of PBD-2 in developing anti-viral drugs or disease-resistant animals can be further investigated.

Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation

In spite of the large-scale production and widespread distribution of vaccines and antiviral drugs, viruses remain a prominent human disease. Recently, the discovery of antiviral peptides (AVPs) has become an influential antiviral agent due to their extraordinary advantages. With the avalanche of newly-found peptide sequences in the post-genomic era, there is a great demand to develop a sequence-based predictor for timely identifying AVPs as this information is very useful for both basic research and drug development. In this study, we propose a novel sequence-based meta-predictor with an effective feature representation, called Meta-iAVP, for the accurate prediction of AVPs from given peptide sequences. Herein, the effective feature representation was extracted from a set of prediction scores derived from various machine learning algorithms and types of features. To the best of our knowledge, the model proposed herein represents the first meta-based approach for the prediction of AVPs. An overall accuracy and Matthews correlation coefficient of 95.20% and 0.90, respectively, was achieved from the independent test set on an objective benchmark dataset. Comparative analysis suggested that Meta-iAVP was superior to that of existing methods and therefore represents a useful tool for AVP prediction. Finally, in an effort to facilitate high-throughput prediction of AVPs, the model was deployed as the Meta-iAVP web server and is made freely available online at http://codes.bio/meta-iavp/ where users can submit query peptide sequences for determining the likelihood of whether or not these peptides are AVPs.