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Muniz Seif EJ, Icimoto MY, Silva Júnior PI. In silico bioprospecting of receptors associated with the mechanism of action of Rondonin, an antifungal peptide from spider Acanthoscurria rondoniae haemolymph. In Silico Pharmacol 2024; 12:55. [PMID: 38863478 PMCID: PMC11162988 DOI: 10.1007/s40203-024-00224-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/24/2024] [Indexed: 06/13/2024] Open
Abstract
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.
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Affiliation(s)
- Elias Jorge Muniz Seif
- Postgraduate Program of Molecular Biology, Biophysics and Biochemistry Department, Federal University of São Paulo, São Paulo, São Paulo 04021-001 Brazil
- Laboratory for Applied Toxicology, Center of Toxins, Immune-Response and Cell Signaling-CeT-ICS/CEPID, Butantan Institute, São Paulo, São Paulo 05503-900 Brazil
| | - Marcelo Yudi Icimoto
- Biophysics Department, Federal University of São Paulo, São Paulo, São Paulo 04024-002 Brazil
| | - Pedro Ismael Silva Júnior
- Postgraduate Program of Molecular Biology, Biophysics and Biochemistry Department, Federal University of São Paulo, São Paulo, São Paulo 04021-001 Brazil
- Laboratory for Applied Toxicology, Center of Toxins, Immune-Response and Cell Signaling-CeT-ICS/CEPID, Butantan Institute, São Paulo, São Paulo 05503-900 Brazil
- Postgraduate Program Interunits in Biotechnology, USP/IPT/IBU, São Paulo, São Paulo Brazil
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Cao R, Hu W, Wei P, Ding Y, Bin Y, Zheng C. FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses. Brief Bioinform 2023; 24:bbad353. [PMID: 37861174 DOI: 10.1093/bib/bbad353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/25/2023] [Accepted: 09/06/2023] [Indexed: 10/21/2023] Open
Abstract
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.
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Affiliation(s)
- Ruifen Cao
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University
| | - Weiling Hu
- Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Computer Science and Technology, Anhui University
| | - Pijing Wei
- Institutes of Physical Science and Information Technology, Anhui University
| | - Yun Ding
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Artificial Intelligence, Anhui University
| | - Yannan Bin
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education and Information Materials and Intelligent Sensing Laboratory of Anhui Province, Institutes of Physical Science and Information Technology, Anhui University
| | - Chunhou Zheng
- Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Artificial Intelligence, Anhui University
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Mustafa G, Mahrosh HS, Attique SA, Arif R, Farah MA, Al-Anazi KM, Ali S. Identification of Plant Peptides as Novel Inhibitors of Orthohepevirus A (HEV) Capsid Protein by Virtual Screening. Molecules 2023; 28:molecules28062675. [PMID: 36985647 PMCID: PMC10051542 DOI: 10.3390/molecules28062675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/12/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023] Open
Abstract
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.
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Affiliation(s)
- Ghulam Mustafa
- Department of Biochemistry, Government College University Faisalabad, Faisalabad 38000, Pakistan
- Correspondence:
| | - Hafiza Salaha Mahrosh
- Department of Biochemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan
| | - Syed Awais Attique
- School of Interdisciplinary Engineering & Science (SINES), National University of Sciences & Technology (NUST), Islamabad 44000, Pakistan
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute, 30 Biopolis Street, Matrix, Singapore 138671, Singapore
| | - Rawaba Arif
- Department of Biochemistry, University of Jhang, Jhang 35200, Pakistan
| | - Mohammad Abul Farah
- Department of Zoology, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
| | - Khalid Mashay Al-Anazi
- Department of Zoology, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
| | - Sajad Ali
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea
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Anurans against SARS-CoV-2: A review of the potential antiviral action of anurans cutaneous peptides. Virus Res 2022; 315:198769. [PMID: 35430319 PMCID: PMC9008983 DOI: 10.1016/j.virusres.2022.198769] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/05/2022] [Accepted: 04/06/2022] [Indexed: 01/17/2023]
Abstract
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.
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Aghamirza Moghim Aliabadi H, Eivazzadeh‐Keihan R, Beig Parikhani A, Fattahi Mehraban S, Maleki A, Fereshteh S, Bazaz M, Zolriasatein A, Bozorgnia B, Rahmati S, Saberi F, Yousefi Najafabadi Z, Damough S, Mohseni S, Salehzadeh H, Khakyzadeh V, Madanchi H, Kardar GA, Zarrintaj P, Saeb MR, Mozafari M. COVID-19: A systematic review and update on prevention, diagnosis, and treatment. MedComm (Beijing) 2022; 3:e115. [PMID: 35281790 PMCID: PMC8906461 DOI: 10.1002/mco2.115] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 12/18/2021] [Accepted: 12/19/2021] [Indexed: 01/09/2023] Open
Abstract
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).
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Affiliation(s)
- Hooman Aghamirza Moghim Aliabadi
- Protein Chemistry LaboratoryDepartment of Medical BiotechnologyBiotechnology Research CenterPasteur Institute of IranTehranIran
- Advance Chemical Studies LaboratoryFaculty of ChemistryK. N. Toosi UniversityTehranIran
| | | | - Arezoo Beig Parikhani
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | | | - Ali Maleki
- Department of ChemistryIran University of Science and TechnologyTehranIran
| | | | - Masoume Bazaz
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | | | | | - Saman Rahmati
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | - Fatemeh Saberi
- Department of Medical BiotechnologySchool of Advanced Technologies in MedicineShahid Beheshti University of Medical SciencesTehranIran
| | - Zeinab Yousefi Najafabadi
- Department of Medical BiotechnologySchool of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
- ImmunologyAsthma & Allergy Research InstituteTehran University of Medical SciencesTehranIran
| | - Shadi Damough
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | - Sara Mohseni
- Non‐metallic Materials Research GroupNiroo Research InstituteTehranIran
| | | | - Vahid Khakyzadeh
- Department of ChemistryK. N. Toosi University of TechnologyTehranIran
| | - Hamid Madanchi
- School of MedicineSemnan University of Medical SciencesSemnanIran
- Drug Design and Bioinformatics UnitDepartment of Medical BiotechnologyBiotechnology Research CenterPasteur Institute of IranTehranIran
| | - Gholam Ali Kardar
- Department of Medical BiotechnologySchool of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
- ImmunologyAsthma & Allergy Research InstituteTehran University of Medical SciencesTehranIran
| | - Payam Zarrintaj
- School of Chemical EngineeringOklahoma State UniversityStillwaterOklahomaUSA
| | - Mohammad Reza Saeb
- Department of Polymer TechnologyFaculty of ChemistryGdańsk University of TechnologyGdańskPoland
| | - Masoud Mozafari
- Department of Tissue Engineering & Regenerative MedicineIran University of Medical SciencesTehranIran
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6
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V A L, Mohammed Alarjani K, Malaisamy A, Balasubramanian B. Bacteriocin producing microbes with bactericidal activity against multidrug resistant pathogens. J Infect Public Health 2021; 14:1802-1809. [PMID: 34740552 DOI: 10.1016/j.jiph.2021.09.029] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 09/08/2021] [Accepted: 09/27/2021] [Indexed: 01/28/2023] Open
Abstract
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.
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Affiliation(s)
- Leslie V A
- Vizhinjam Regional Centre of Central Marine Fisheries Research Institute, Vishinjam, Thiruvananthapuram, Kerala, India.
| | - Khaloud Mohammed Alarjani
- Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
| | - Arunkumar Malaisamy
- Transcriptional Regulation, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
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Khan A, Umbreen S, Hameed A, Fatima R, Zahoor U, Babar Z, Waseem M, Hussain Z, Rizwan M, Zaman N, Ali S, Suleman M, Shah A, Ali L, Ali SS, Wei DQ. In Silico Mutagenesis-Based Remodelling of SARS-CoV-1 Peptide (ATLQAIAS) to Inhibit SARS-CoV-2: Structural-Dynamics and Free Energy Calculations. Interdiscip Sci 2021; 13:521-534. [PMID: 34324157 PMCID: PMC8319699 DOI: 10.1007/s12539-021-00447-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 05/29/2021] [Accepted: 06/04/2021] [Indexed: 12/20/2022]
Abstract
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.
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Affiliation(s)
- Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
| | - Shaheena Umbreen
- Department of Botany, University of Okara, Okara, Punjab, Pakistan
| | - Asma Hameed
- Department of Botany, University of Azad Jammu & Kashmir, Muzaffarabad, Azad Jammu & Kashmir, Pakistan
| | - Rida Fatima
- Department of Chemistry, Bahauddin Zakariya University, Multan, Pakistan
| | - Ujala Zahoor
- Department of Botany, Women University, Bagh, Azad Jammu & Kashmir, Pakistan
| | - Zainib Babar
- Center for Viticulture and Enology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Muhammad Waseem
- Faculty of Rehabilitation and Allied Health Science, Riphah International University, Islamabad, Pakistan
| | - Zahid Hussain
- Center for Biotechnology and Microbiology, University of Swat, Swat, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Rizwan
- Center for Biotechnology and Microbiology, University of Swat, Swat, Khyber Pakhtunkhwa, Pakistan
| | - Nasib Zaman
- Center for Biotechnology and Microbiology, University of Swat, Swat, Khyber Pakhtunkhwa, Pakistan
| | - Shahid Ali
- Center for Biotechnology and Microbiology, University of Swat, Swat, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Suleman
- Center for Biotechnology and Microbiology, University of Swat, Swat, Khyber Pakhtunkhwa, Pakistan
| | - Abdullah Shah
- Department of Biotechnology, Shaheed Benazir Bhutto University, Sheringal, Dir, Khyber Pakhtunkhwa, Pakistan
| | - Liaqat Ali
- Department of Biological Sciences, National University of Medical Sciences (NUMS), Rawalpindi, Pakistan
| | - Syed Shujait Ali
- Center for Biotechnology and Microbiology, University of Swat, Swat, Khyber Pakhtunkhwa, Pakistan
| | - Dong-Qing Wei
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center On Antibacterial Resistances, Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China.
- Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong, 518055, People's Republic of China.
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Khan A, Khan S, Ahmad S, Anwar Z, Hussain Z, Safdar M, Rizwan M, Waseem M, Hussain A, Akhlaq M, Khan T, Ali SS, Wei DQ. HantavirusesDB: Vaccinomics and RNA-based therapeutics database for the potentially emerging human respiratory pandemic agents. Microb Pathog 2021; 160:105161. [PMID: 34461244 DOI: 10.1016/j.micpath.2021.105161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/25/2021] [Accepted: 08/26/2021] [Indexed: 12/29/2022]
Abstract
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.
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Affiliation(s)
- Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, PR China.
| | - Shahzeb Khan
- Center for Biotechnology and Microbiology, University of Swat, Swat, KP, Pakistan
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar, 25000, Pakistan
| | - Zeeshan Anwar
- Department of Pharmacy, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, Pakistan
| | - Zahid Hussain
- Center for Biotechnology and Microbiology, University of Swat, Swat, KP, Pakistan
| | - Muhammad Safdar
- Faculty of Pharmacy, Gomal University, DI Khan, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Rizwan
- Center for Biotechnology and Microbiology, University of Swat, Swat, KP, Pakistan
| | - Muhammad Waseem
- Faculty of Rehabilitation and Allied Health Science, Riphah International University, Islamabad, Pakistan
| | - Abid Hussain
- Department of Pharmacy, University of Poonch, Rawalakot, Azad Jammu and Kashmir, Pakistan
| | - Muhammad Akhlaq
- Faculty of Pharmacy, Gomal University, DI Khan, Khyber Pakhtunkhwa, Pakistan
| | - Taimoor Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, PR China
| | - Syed Shujait Ali
- Center for Biotechnology and Microbiology, University of Swat, Swat, KP, Pakistan
| | - Dong-Qing Wei
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, PR China; State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, PR China; Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong, 518055, PR China.
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9
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Charoenkwan P, Anuwongcharoen N, Nantasenamat C, Hasan MM, Shoombuatong W. In Silico Approaches for the Prediction and Analysis of Antiviral Peptides: A Review. Curr Pharm Des 2021; 27:2180-2188. [PMID: 33138759 DOI: 10.2174/1381612826666201102105827] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 08/20/2020] [Indexed: 11/22/2022]
Abstract
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.
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Affiliation(s)
- Phasit Charoenkwan
- Modern Management and Information Technology, College of Arts, Media and Technology, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Nuttapat Anuwongcharoen
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand
| | - Chanin Nantasenamat
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand
| | - Md Mehedi Hasan
- Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan
| | - Watshara Shoombuatong
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700, Thailand
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10
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The Antiviral and Virucidal Activities of Voacangine and Structural Analogs Extracted from Tabernaemontana cymosa Depend on the Dengue Virus Strain. PLANTS 2021; 10:plants10071280. [PMID: 34201900 PMCID: PMC8309144 DOI: 10.3390/plants10071280] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 06/01/2021] [Accepted: 06/03/2021] [Indexed: 12/21/2022]
Abstract
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.
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Tiwari SK, Dicks LMT, Popov IV, Karaseva A, Ermakov AM, Suvorov A, Tagg JR, Weeks R, Chikindas ML. Probiotics at War Against Viruses: What Is Missing From the Picture? Front Microbiol 2020; 11:1877. [PMID: 32973697 PMCID: PMC7468459 DOI: 10.3389/fmicb.2020.01877] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 07/16/2020] [Indexed: 01/07/2023] Open
Abstract
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.
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Affiliation(s)
- Santosh Kumar Tiwari
- Department of Genetics, Maharshi Dayanand University, Rohtak, India,*Correspondence: Santosh Kumar Tiwari,
| | - Leon M. T. Dicks
- Department of Microbiology, Stellenbosch University, Stellenbosch, South Africa
| | - Igor V. Popov
- Center for Agro-Biotechnology, Faculty of Bioengineering and Veterinary Medicine, Don State Technical University, Rostov-on-Don, Russia
| | - Alena Karaseva
- Institute of Experimental Medicine, Saint Petersburg, Russia
| | - Alexey M. Ermakov
- Center for Agro-Biotechnology, Faculty of Bioengineering and Veterinary Medicine, Don State Technical University, Rostov-on-Don, Russia
| | - Alexander Suvorov
- Institute of Experimental Medicine, Saint Petersburg, Russia,Saint Petersburg State University, Saint Petersburg, Russia
| | | | - Richard Weeks
- Health Promoting Naturals Laboratory, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Brunswick, NJ, United States
| | - Michael L. Chikindas
- Center for Agro-Biotechnology, Faculty of Bioengineering and Veterinary Medicine, Don State Technical University, Rostov-on-Don, Russia,Health Promoting Naturals Laboratory, School of Environmental and Biological Sciences, Rutgers, The State University of New Jersey, Brunswick, NJ, United States
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Huang J, Qi Y, Wang A, Huang C, Liu X, Yang X, Li L, Zhou R. Porcine β-defensin 2 inhibits proliferation of pseudorabies virus in vitro and in transgenic mice. Virol J 2020; 17:18. [PMID: 32014007 PMCID: PMC6998849 DOI: 10.1186/s12985-020-1288-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 01/20/2020] [Indexed: 12/31/2022] Open
Abstract
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.
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Affiliation(s)
- Jing Huang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Yanhua Qi
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Antian Wang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Chao Huang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xiao Liu
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China
| | - Xi Yang
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China.,Chongqing Academy of Animal Sciences, Chongqing, 402460, China
| | - Lu Li
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China. .,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China. .,Key Laboratory of Development of Veterinary Diagnostic Products, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Wuhan, 430070, China. .,International Research Center for Animal Disease, Ministry of Science and Technology of the People's Republic of China, Wuhan, 430070, China.
| | - Rui Zhou
- State Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, 430070, China. .,Key Laboratory of Preventive Veterinary Medicine in Hubei Province, Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070, China. .,Key Laboratory of Development of Veterinary Diagnostic Products, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Wuhan, 430070, China. .,International Research Center for Animal Disease, Ministry of Science and Technology of the People's Republic of China, Wuhan, 430070, China.
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Schaduangrat N, Nantasenamat C, Prachayasittikul V, Shoombuatong W. Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation. Int J Mol Sci 2019; 20:ijms20225743. [PMID: 31731751 PMCID: PMC6888698 DOI: 10.3390/ijms20225743] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 11/07/2019] [Accepted: 11/13/2019] [Indexed: 12/31/2022] Open
Abstract
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.
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Affiliation(s)
- Nalini Schaduangrat
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand; (N.S.); (C.N.)
| | - Chanin Nantasenamat
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand; (N.S.); (C.N.)
| | - Virapong Prachayasittikul
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand;
| | - Watshara Shoombuatong
- Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand; (N.S.); (C.N.)
- Correspondence: ; Tel.: +66-2441-4371 (ext. 2715)
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