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Soltan MA, Abdulsahib WK, Amer M, Refaat AM, Bagalagel AA, Diri RM, Albogami S, Fayad E, Eid RA, Sharaf SMA, Elhady SS, Darwish KM, Eldeen MA. Mining of Marburg Virus Proteome for Designing an Epitope-Based Vaccine. Front Immunol 2022; 13:907481. [PMID: 35911751 PMCID: PMC9334820 DOI: 10.3389/fimmu.2022.907481] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/16/2022] [Indexed: 12/11/2022] Open
Abstract
Marburg virus (MARV) is one of the most harmful zoonotic viruses with deadly effects on both humans and nonhuman primates. Because of its severe outbreaks with a high rate of fatality, the world health organization put it as a risk group 4 pathogen and focused on the urgent need for the development of effective solutions against that virus. However, up to date, there is no effective vaccine against MARV in the market. In the current study, the complete proteome of MARV (seven proteins) was analyzed for the antigenicity score and the virulence or physiological role of each protein where we nominated envelope glycoprotein (Gp), Transcriptional activator (VP30), and membrane-associated protein (VP24) as the candidates for epitope prediction. Following that, a vaccine construct was designed based on CTL, HTL, and BCL epitopes of the selected protein candidates and to finalize the vaccine construct, several amino acid linkers, β-defensin adjuvant, and PADRE peptides were incorporated. The generated potential vaccine was assessed computationally for several properties such as antigenicity, allergenicity, stability, and other structural features where the outcomes of these assessments nominated this potential vaccine to be validated for its binding affinity with two molecular targets TLR-8 and TLR-4. The binding score and the stability of the vaccine-receptor complex, which was deeply studied through molecular docking-coupled dynamics simulation, supported the selection of our designed vaccine as a putative solution for MARV that should be validated through future wet-lab experiments. Here, we describe the computational approach for designing and analysis of this potential vaccine.
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Affiliation(s)
- Mohamed A. Soltan
- Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai University, Ismailia, Egypt
- *Correspondence: Mohamed A. Soltan, ; Muhammad Alaa Eldeen,
| | - Waleed K. Abdulsahib
- Department of pharmacology and Toxicology, College of Pharmacy, Al- Farahidi University, Baghdad, Iraq
| | - Mahmoud Amer
- Internal Medicine Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Ahmed M. Refaat
- Zoology Department, Faculty of Science, Minia University, El-Minia, Egypt
| | - Alaa A. Bagalagel
- Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Reem M. Diri
- Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Sarah Albogami
- Department of Biotechnology, College of Science, Taif University, Taif, Saudi Arabia
| | - Eman Fayad
- Department of Biotechnology, College of Science, Taif University, Taif, Saudi Arabia
| | - Refaat A. Eid
- Department of Pathology, College of Medicine, King Khalid University, Abha, Saudi Arabia
| | | | - Sameh S. Elhady
- Department of Natural Products, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Khaled M. Darwish
- Department of Medicinal Chemistry, Faculty of Pharmacy, Suez Canal University, Ismailia, Egypt
| | - Muhammad Alaa Eldeen
- Cell Biology, Histology and Genetics Division, Zoology Department, Faculty of Science, Zagazig University, Zagazig, Egypt
- *Correspondence: Mohamed A. Soltan, ; Muhammad Alaa Eldeen,
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102
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An In-Silico Investigation to Design a Multi-Epitopes Vaccine against Multi-Drug Resistant Hafnia alvei. Vaccines (Basel) 2022; 10:vaccines10071127. [PMID: 35891291 PMCID: PMC9316606 DOI: 10.3390/vaccines10071127] [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: 04/14/2022] [Revised: 06/19/2022] [Accepted: 07/12/2022] [Indexed: 11/16/2022] Open
Abstract
Antimicrobial resistance has become a significant health issue because of the misuse of antibiotics in our daily lives, resulting in high rates of morbidity and mortality. Hafnia alvei is a rod-shaped, Gram-negative and facultative anaerobic bacteria. The medical community has emphasized H. alvei’s possible association with gastroenteritis. As of now, there is no licensed vaccine for H. alvei, and as such, computer aided vaccine design approaches could be an ideal approach to highlight the potential vaccine epitopes against this bacteria. By using bacterial pan-genome analysis (BPGA), we were able to study the entire proteomes of H. alvei with the aim of developing a vaccine. Based on the analysis, 20,370 proteins were identified as core proteins, which were further used in identifying potential vaccine targets based on several vaccine candidacy parameters. The prioritized vaccine targets against the bacteria are; type 1 fimbrial protein, flagellar hook length control protein (FliK), flagellar hook associated protein (FlgK), curli production assembly/transport protein (CsgF), fimbria/pilus outer membrane usher protein, fimbria/pilus outer membrane usher protein, molecular chaperone, flagellar filament capping protein (FliD), TonB-dependent hemoglobin /transferrin/lactoferrin family receptor, Porin (OmpA), flagellar basal body rod protein (FlgF) and flagellar hook-basal body complex protein (FliE). During the epitope prediction phase, different antigenic, immunogenic, non-Allergenic, and non-Toxic epitopes were predicted for the above-mentioned proteins. The selected epitopes were combined to generate a multi-epitope vaccine construct and a cholera toxin B subunit (adjuvant) was added to enhance the vaccine’s antigenicity. Downward analyses of vaccines were performed using a vaccine three-dimensional model. Docking studies have confirmed that the vaccine strongly binds with MHC-I, MHC-II, and TLR-4 immune cell receptors. Additionally, molecular dynamics simulations confirmed that the vaccine epitopes were exposed to nature and to the host immune system and interpreted strong intermolecular binding between the vaccine and receptors. Based on the results of the study, the model vaccine construct seems to have the capacity to produce protective immune responses in the host, making it an attractive candidate for further in vitro and in vivo studies.
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103
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Rida T, Ahmad S, Ullah A, Ismail S, Tahir ul Qamar M, Afsheen Z, Khurram M, Saqib Ishaq M, Alkhathami AG, Alatawi EA, Alrumaihi F, Allemailem KS. Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19148408. [PMID: 35886259 PMCID: PMC9320593 DOI: 10.3390/ijerph19148408] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/05/2022] [Accepted: 07/07/2022] [Indexed: 02/08/2023]
Abstract
Porphyromonas gingivalis is a Gram-negative anaerobic bacterium, mainly present in the oral cavity and causes periodontal infections. Currently, no licensed vaccine is available against P. gingivalis and other oral bacterial pathogens. To develop a vaccine against P. gingivalis, herein, we applied a bacterial pan-genome analysis (BPGA) on the bacterial genomes that retrieved a total number of 4908 core proteins, which were further utilized for the identification of good vaccine candidates. After several vaccine candidacy analyses, three proteins, namely lytic transglycosylase domain-containing protein, FKBP-type peptidyl-propyl cis-trans isomerase and superoxide dismutase, were shortlisted for epitopes prediction. In the epitopes prediction phase, different types of B and T-cell epitopes were predicted and only those with an antigenic, immunogenic, non-allergenic, and non-toxic profile were selected. Moreover, all the predicted epitopes were joined with each other to make a multi-epitopes vaccine construct, which was linked further to the cholera toxin B-subunit to enhance the antigenicity of the vaccine. For downward analysis, a three dimensional structure of the designed vaccine was modeled. The modeled structure was checked for binding potency with major histocompatibility complex I (MHC-I), major histocompatibility complex II (MHC-II), and Toll-like receptor 4 (TLR-4) immune cell receptors which revealed that the designed vaccine performed proper binding with respect to immune cell receptors. Additionally, the binding efficacy of the vaccine was validated through a molecular dynamic simulation that interpreted strong intermolecular vaccine-receptor binding and confirmed the exposed situation of vaccine epitopes to the host immune system. In conclusion, the study suggested that the model vaccine construct has the potency to generate protective host immune responses and that it might be a good vaccine candidate for experimental in vivo and in vitro studies.
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Affiliation(s)
- Tehniyat Rida
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (T.R.); (A.U.); (Z.A.); (M.S.I.)
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (T.R.); (A.U.); (Z.A.); (M.S.I.)
- Correspondence: (S.A.); (K.S.A.)
| | - Asad Ullah
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (T.R.); (A.U.); (Z.A.); (M.S.I.)
| | - Saba Ismail
- Department of Biological Sciences, National University of Medical Sciences, Rawalpindi 46000, Pakistan;
| | - Muhammad Tahir ul Qamar
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad 38000, Pakistan;
| | - Zobia Afsheen
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (T.R.); (A.U.); (Z.A.); (M.S.I.)
| | - Muhammad Khurram
- Department of Pharmacy, Abasyn University, Peshawar 25000, Pakistan;
| | - Muhammad Saqib Ishaq
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (T.R.); (A.U.); (Z.A.); (M.S.I.)
| | - Ali G. Alkhathami
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha 61481, Saudi Arabia;
| | - Eid A. Alatawi
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 71491, Saudi Arabia;
| | - Faris Alrumaihi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia;
| | - Khaled S. Allemailem
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia;
- Correspondence: (S.A.); (K.S.A.)
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104
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Almansour NM. Immunoinformatics- and Bioinformatics-Assisted Computational Designing of a Novel Multiepitopes Vaccine Against Cancer-Causing Merkel Cell Polyomavirus. Front Microbiol 2022; 13:929669. [PMID: 35836414 PMCID: PMC9273964 DOI: 10.3389/fmicb.2022.929669] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 06/01/2022] [Indexed: 12/22/2022] Open
Abstract
Merkel cell polyomavirus (MCV) contains double-stranded DNA as its genome and is the fifth polyomavirus that infects humans. The virus causes Merkel cell carcinoma (aggressive skin cancer). Till present, no proper drug or vaccines are available to treat/prevent the virus infection and stop the emergence of Merkel cell carcinoma. In this study, computational vaccine design strategies were applied to design a chimeric-epitopes vaccine against the virus. The complete proteome comprised of four proteins was filtered through various vaccine candidacy parameters and as such two proteins, namely, capsid protein VP1 and capsid protein VP2, were considered as good vaccine targets. Furthermore, they harbor safe and potential B and T cell epitopes, which can be used in a chimeric multiepitopes-based vaccine design. The epitopes of the vaccine have maximum world population coverage of 95.04%. The designed vaccine structure was modeled in 3D that reported maximum residues in favored regions (95.7%) of the Ramachandran plot. The interactions analysis with different human immune receptors like TLR3, MHC-I, and MHC-II illustrated vaccine's good binding affinity and stable dynamics. The structural deviations of the vaccine receptor(s) complexes are within 5 Å, where majority of the receptors residues remain in good equilibrium in the simulation time. Also, the vaccine was found to form between 60 and 100 hydrogen bonds to receptors. The vaccine stimulated strong immune responses in addition to interferon and cytokines. The strength of vaccine-receptor(s) binding was further affirmed by binding energies estimation that concluded <-150.32 kcal/mol of net binding energy. All these findings suggest the vaccine as a promising candidate that needs further experimental testing to disclose its real immune protective efficacy. Furthermore, the designed vaccine might accelerate vaccine development against the MCV and could save time and expenses.
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105
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Alsowayeh N, Albutti A, Al-Shouli ST. Reverse Vaccinology and Immunoinformatic Assisted Designing of a Multi-Epitopes Based Vaccine Against Nosocomial Burkholderia cepacia. Front Microbiol 2022; 13:929400. [PMID: 35875518 PMCID: PMC9297367 DOI: 10.3389/fmicb.2022.929400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 05/20/2022] [Indexed: 11/29/2022] Open
Abstract
Burkholderia cepacia is a Gram-negative nosocomial pathogen and is considered as a troublesome bacterium due to its resistance to many common antibiotics. There is no licensed vaccine available to prevent the pathogen infections, thus making the condition more alarming and warrant the search for novel therapeutic and prophylactic approaches. In order to identify protective antigens from pathogen proteome, substantial efforts are put forth to prioritized potential vaccine targets and antigens that can be easily evaluated experimentally. In this vaccine design investigation, it was found that B. cepacia completely sequenced proteomes available in NCBI genome database has a total of 28,966 core proteins. Out of total, 25,282 proteins were found redundant while 3,684 were non-redundant. Subcellular localization revealed that 18 proteins were extracellular, 31 were part of the outer membrane, 75 proteins were localized in the periplasm, and 23 were virulent proteins. Five proteins namely flagellar hook protein (FlgE), fimbria biogenesis outer membrane usher protein, Type IV pilus secretin (PilQ), cytochrome c4, flagellar hook basal body complex protein (FliE) were tested for positive for antigenic, non-toxic, and soluble epitopes during predication of B-cell derived T-cell epitopes. A vaccine peptide of 14 epitopes (joined together via GPGPG linkers) and cholera toxin B subunit (CTBS) adjuvant (joined to epitopes peptide via EAAAK linker) was constructed. Binding interaction of the modeled vaccine with MHC-I, MHC-II, and Toll-like receptor 4 (TLR-4) immune receptors was studied using molecular docking studies and further analyzed in molecular dynamics simulations that affirms strong intermolecular binding and stable dynamics. The maximum root mean square deviation (RMSD) score of complexes in the simulation time touches to 2 Å. Additionally, complexes binding free energies were determined that concluded robust interaction energies dominated by van der Waals. The total energy of each complex is < -190 kcal/mol. In summary, the designed vaccine showed promising protective immunity against B. cepacia and needs to be examined in experiments.
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Affiliation(s)
- Noorah Alsowayeh
- Department of Biology, College of Education (Majmaah), Majmaah University, Al-Majmaah, Saudi Arabia
| | - Aqel Albutti
- Department of Medical Biotechnology, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia
| | - Samia T. Al-Shouli
- Immunology Unit, Pathology Department, College of Medicine, King Saud University, Riyadh, Saudi Arabia
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106
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Alshammari A, Alharbi M, Alghamdi A, Alharbi SA, Ashfaq UA, Tahir ul Qamar M, Ullah A, Irfan M, Khan A, Ahmad S. Computer-Aided Multi-Epitope Vaccine Design against Enterobacter xiangfangensis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19137723. [PMID: 35805383 PMCID: PMC9265868 DOI: 10.3390/ijerph19137723] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/13/2022] [Accepted: 06/15/2022] [Indexed: 12/22/2022]
Abstract
Antibiotic resistance is a global public health threat and is associated with high mortality due to antibiotics’ inability to treat bacterial infections. Enterobacter xiangfangensis is an emerging antibiotic-resistant bacterial pathogen from the Enterobacter genus and has the ability to acquire resistance to multiple antibiotic classes. Currently, there is no effective vaccine against Enterobacter species. In this study, a chimeric vaccine is designed comprising different epitopes screened from E. xiangfangensis proteomes using immunoinformatic and bioinformatic approaches. In the first phase, six fully sequenced proteomes were investigated by bacterial pan-genome analysis, which revealed that the pathogen consists of 21,996 core proteins, 3785 non-redundant proteins and 18,211 redundant proteins. The non-redundant proteins were considered for the vaccine target prioritization phase where different vaccine filters were applied. By doing so, two proteins; ferrichrome porin (FhuA) and peptidoglycan-associated lipoprotein (Pal) were shortlisted for epitope prediction. Based on properties of antigenicity, allergenicity, water solubility and DRB*0101 binding ability, three epitopes (GPAPTIAAKR, ATKTDTPIEK and RNNGTTAEI) were used in multi-epitope vaccine designing. The designed vaccine construct was analyzed in a docking study with immune cell receptors, which predicted the vaccine’s proper binding with said receptors. Molecular dynamics analysis revealed that the vaccine demonstrated stable binding dynamics, and binding free energy calculations further validated the docking results. In conclusion, these in silico results may help experimentalists in developing a vaccine against E. xiangfangensis in specific and Enterobacter in general.
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Affiliation(s)
- Abdulrahman Alshammari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia; (A.A.); (M.A.)
| | - Metab Alharbi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia; (A.A.); (M.A.)
| | - Abdullah Alghamdi
- Department of Pathology and Laboratory Medicine, Riyadh Security Forces Hospital, Ministry of Interior, Riyadh 11432, Saudi Arabia;
| | | | - Usman Ali Ashfaq
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan;
| | - Muhammad Tahir ul Qamar
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan;
- Correspondence: (M.T.u.Q.); (S.A.)
| | - Asad Ullah
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (A.K.)
| | - Muhammad Irfan
- Department of Oral Biology, College of Dentistry, University of Florida, Gainesville, FL 32611, USA;
| | - Amjad Khan
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (A.K.)
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (A.K.)
- Correspondence: (M.T.u.Q.); (S.A.)
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107
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Kaushik V, G SK, Gupta LR, Kalra U, Shaikh AR, Cavallo L, Chawla M. Immunoinformatics Aided Design and In-Vivo Validation of a Cross-Reactive Peptide Based Multi-Epitope Vaccine Targeting Multiple Serotypes of Dengue Virus. Front Immunol 2022; 13:865180. [PMID: 35799781 PMCID: PMC9254734 DOI: 10.3389/fimmu.2022.865180] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 05/05/2022] [Indexed: 02/03/2023] Open
Abstract
Dengue virus (DENV) is an arboviral disease affecting more than 400 million people annually. Only a single vaccine formulation is available commercially and many others are still under clinical trials. Despite all the efforts in vaccine designing, the improvement in vaccine formulation against DENV is very much needed. In this study, we used a roboust immunoinformatics approach, targeting all the four serotypes of DENV to design a multi-epitope vaccine. A total of 13501 MHC II binding CD4+ epitope peptides were predicted from polyprotein sequences of four dengue virus serotypes. Among them, ten conserved epitope peptides that were interferon-inducing were selected and found to be conserved among all the four dengue serotypes. The vaccine was formulated using antigenic, non-toxic and conserved multi epitopes discovered in the in-silico study. Further, the molecular docking and molecular dynamics predicted stable interactions between predicted vaccine and immune receptor, TLR-5. Finally, one of the mapped epitope peptides was synthesized for the validation of antigenicity and antibody production ability where the in-vivo tests on rabbit model was conducted. Our in-vivo analysis clearly indicate that the imunogen designed in this study could stimulate the production of antibodies which further suggest that the vaccine designed possesses good immunogenicity.
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Affiliation(s)
- Vikas Kaushik
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India
| | - Sunil Krishnan G
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India
| | - Lovi Raj Gupta
- Domain of Bioinformatics, School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Punjab, India
| | - Utkarsh Kalra
- Department of Research and Innovation, STEMskills Research and Education Lab Private Limited, Faridabad, India
- Department of Data Science, Innopolis University, Innopolis, Russia
| | - Abdul Rajjak Shaikh
- Department of Research and Innovation, STEMskills Research and Education Lab Private Limited, Faridabad, India
- *Correspondence: Abdul Rajjak Shaikh, ; Luigi Cavallo, ; Mohit Chawla, ;
| | - Luigi Cavallo
- Kaust Catalysis Center, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- *Correspondence: Abdul Rajjak Shaikh, ; Luigi Cavallo, ; Mohit Chawla, ;
| | - Mohit Chawla
- Kaust Catalysis Center, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- *Correspondence: Abdul Rajjak Shaikh, ; Luigi Cavallo, ; Mohit Chawla, ;
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108
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Bon C, Cabantous S, Julien S, Guillet V, Chalut C, Rima J, Brison Y, Malaga W, Sanchez-Dafun A, Gavalda S, Quémard A, Marcoux J, Waldo GS, Guilhot C, Mourey L. Solution structure of the type I polyketide synthase Pks13 from Mycobacterium tuberculosis. BMC Biol 2022; 20:147. [PMID: 35729566 PMCID: PMC9210659 DOI: 10.1186/s12915-022-01337-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Type I polyketide synthases (PKSs) are multifunctional enzymes responsible for the biosynthesis of a group of diverse natural compounds with biotechnological and pharmaceutical interest called polyketides. The diversity of polyketides is impressive despite the limited set of catalytic domains used by PKSs for biosynthesis, leading to considerable interest in deciphering their structure-function relationships, which is challenging due to high intrinsic flexibility. Among nineteen polyketide synthases encoded by the genome of Mycobacterium tuberculosis, Pks13 is the condensase required for the final condensation step of two long acyl chains in the biosynthetic pathway of mycolic acids, essential components of the cell envelope of Corynebacterineae species. It has been validated as a promising druggable target and knowledge of its structure is essential to speed up drug discovery to fight against tuberculosis. RESULTS We report here a quasi-atomic model of Pks13 obtained using small-angle X-ray scattering of the entire protein and various molecular subspecies combined with known high-resolution structures of Pks13 domains or structural homologues. As a comparison, the low-resolution structures of two other mycobacterial polyketide synthases, Mas and PpsA from Mycobacterium bovis BCG, are also presented. This study highlights a monomeric and elongated state of the enzyme with the apo- and holo-forms being identical at the resolution probed. Catalytic domains are segregated into two parts, which correspond to the condensation reaction per se and to the release of the product, a pivot for the enzyme flexibility being at the interface. The two acyl carrier protein domains are found at opposite sides of the ketosynthase domain and display distinct characteristics in terms of flexibility. CONCLUSIONS The Pks13 model reported here provides the first structural information on the molecular mechanism of this complex enzyme and opens up new perspectives to develop inhibitors that target the interactions with its enzymatic partners or between catalytic domains within Pks13 itself.
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Affiliation(s)
- Cécile Bon
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France.
| | - Stéphanie Cabantous
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
- Los Alamos National Laboratory, Bioscience Division B-N2, Los Alamos, NM, 87545, USA
- Present address: Centre de Recherche en Cancérologie de Toulouse (CRCT), Inserm, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Sylviane Julien
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Valérie Guillet
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Christian Chalut
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Julie Rima
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Yoann Brison
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
- Present address: Toulouse White Biotechnology, 31400, Toulouse, France
| | - Wladimir Malaga
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Angelique Sanchez-Dafun
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Sabine Gavalda
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
- Present address: Carbios, Biopole Clermont Limagne, 63360, Saint-Beauzire, France
| | - Annaïk Quémard
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Julien Marcoux
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Geoffrey S Waldo
- Los Alamos National Laboratory, Bioscience Division B-N2, Los Alamos, NM, 87545, USA
| | - Christophe Guilhot
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France
| | - Lionel Mourey
- Institut de Pharmacologie et de Biologie Structurale, IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France.
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109
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Ezzemani W, Kettani A, Sappati S, Kondaka K, El Ossmani H, Tsukiyama-Kohara K, Altawalah H, Saile R, Kohara M, Benjelloun S, Ezzikouri S. Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants. J Biomol Struct Dyn 2022:1-22. [PMID: 35549819 DOI: 10.1080/07391102.2022.2075468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
The genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel epitopes were identified as immunogenic triggering immune responses and no toxic after investigation with in silico tools. Furthermore, we found these peptide vaccine candidates showed a significant binding affinity for MHC I and MHC II alleles in molecular docking investigations. We consider them to be promising targets for developing peptide-based vaccines against SARS-CoV-2. Subsequently, we designed two efficient multi-epitopes vaccines against the SARS-CoV-2, the first one based on potent MHC class I and class II T-cell epitopes of S (FPNITNLCPF-NYNYLYRLFR-MFVFLVLLPLVSSQC), M (MWLSYFIASF-GLMWLSYFIASFRLF), E (LTALRLCAY-LLFLAFVVFLLVTLA), and N (SPRWYFYYL-AQFAPSASAFFGMSR). The second candidate is the result of the tailoring of the first designed vaccine according to three classes of SARS-CoV-2 variants. Molecular docking showed that the protein-protein binding interactions between the vaccines construct and TLR2-TLR4 immune receptors are stable complexes. These findings confirmed that the final multi-epitope vaccine could be easily adapted to new viral variants. Our study offers a shortlist of promising epitopes that can accelerate the development of an effective and safe vaccine against the virus and its adaptation to new variants.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Wahiba Ezzemani
- Virology Unit, Viral Hepatitis Laboratory, Institut Pasteur du Maroc, Casablanca, Morocco.,Laboratoire de Biologie et Santé (URAC34), Départment de Biologie, Faculté des Sciences Ben Msik, Hassan II University of Casablanca, Casablanca, Morocco
| | - Anass Kettani
- Laboratoire de Biologie et Santé (URAC34), Départment de Biologie, Faculté des Sciences Ben Msik, Hassan II University of Casablanca, Casablanca, Morocco
| | - Subrahmanyam Sappati
- Department of Pharmaceutical Technology and Biochemistry, Gdańsk University of Technology, Gdańsk, Poland.,BioTechMed Center, Gdańsk University of Technology, Gdańsk, Poland
| | - Kavya Kondaka
- Department of Pharmaceutical Technology and Biochemistry, Gdańsk University of Technology, Gdańsk, Poland
| | - Hicham El Ossmani
- Institut de Criminalistique de la Gendarmerie Royale, AMSSNuR, Rabat, Morocco
| | - Kyoko Tsukiyama-Kohara
- Transboundary Animal Diseases Centre, Joint Faculty of Veterinary Medicine, Kagoshima University, Kagoshima, Japan
| | - Haya Altawalah
- Department of Microbiology, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait.,Virology Unit, Yacoub Behbehani Center, Sabah Hospital, Ministry of Health, Kuwait City, Kuwait
| | - Rachid Saile
- Laboratoire de Biologie et Santé (URAC34), Départment de Biologie, Faculté des Sciences Ben Msik, Hassan II University of Casablanca, Casablanca, Morocco
| | - Michinori Kohara
- Department of Microbiology and Cell Biology, The Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Soumaya Benjelloun
- Virology Unit, Viral Hepatitis Laboratory, Institut Pasteur du Maroc, Casablanca, Morocco
| | - Sayeh Ezzikouri
- Virology Unit, Viral Hepatitis Laboratory, Institut Pasteur du Maroc, Casablanca, Morocco
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110
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Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19095568. [PMID: 35564967 PMCID: PMC9104312 DOI: 10.3390/ijerph19095568] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 04/23/2022] [Accepted: 04/28/2022] [Indexed: 12/13/2022]
Abstract
Antibiotic resistance (AR) is the result of microbes’ natural evolution to withstand the action of antibiotics used against them. AR is rising to a high level across the globe, and novel resistant strains are emerging and spreading very fast. Acinetobacter baumannii is a multidrug resistant Gram-negative bacteria, responsible for causing severe nosocomial infections that are treated with several broad spectrum antibiotics: carbapenems, β-lactam, aminoglycosides, tetracycline, gentamicin, impanel, piperacillin, and amikacin. The A. baumannii genome is superplastic to acquire new resistant mechanisms and, as there is no vaccine in the development process for this pathogen, the situation is more worrisome. This study was conducted to identify protective antigens from the core genome of the pathogen. Genomic data of fully sequenced strains of A. baumannii were retrieved from the national center for biotechnological information (NCBI) database and subjected to various genomics, immunoinformatics, proteomics, and biophysical analyses to identify potential vaccine antigens against A. baumannii. By doing so, four outer membrane proteins were prioritized: TonB-dependent siderphore receptor, OmpA family protein, type IV pilus biogenesis stability protein, and OprD family outer membrane porin. Immuoinformatics predicted B-cell and T-cell epitopes from all four proteins. The antigenic epitopes were linked to design a multi-epitopes vaccine construct using GPGPG linkers and adjuvant cholera toxin B subunit to boost the immune responses. A 3D model of the vaccine construct was built, loop refined, and considered for extensive error examination. Disulfide engineering was performed for the stability of the vaccine construct. Blind docking of the vaccine was conducted with host MHC-I, MHC-II, and toll-like receptors 4 (TLR-4) molecules. Molecular dynamic simulation was carried out to understand the vaccine-receptors dynamics and binding stability, as well as to evaluate the presentation of epitopes to the host immune system. Binding energies estimation was achieved to understand intermolecular interaction energies and validate docking and simulation studies. The results suggested that the designed vaccine construct has high potential to induce protective host immune responses and can be a good vaccine candidate for experimental in vivo and in vitro studies.
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111
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Design of a Multi-Epitope Vaccine against Tropheryma whipplei Using Immunoinformatics and Molecular Dynamics Simulation Techniques. Vaccines (Basel) 2022; 10:vaccines10050691. [PMID: 35632446 PMCID: PMC9147804 DOI: 10.3390/vaccines10050691] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 04/13/2022] [Accepted: 04/20/2022] [Indexed: 12/15/2022] Open
Abstract
Whipple’s disease is caused by T. whipplei, a Gram-positive pathogenic bacterium. It is considered a persistent infection affecting various organs, more likely to infect males. There is currently no licensed vaccination available for Whipple’s disease; thus, the development of a chimeric peptide-based vaccine against T. whipplei has the potential to be tremendously beneficial in preventing Whipple’s disease in the future. The present study aimed to apply modern computational approaches to generate a multi-epitope-based vaccine that expresses antigenic determinants prioritized from the core proteome of two T. whipplei whole proteomes. Using an integrated computational approach, four immunodominant epitopes were found from two extracellular proteins. Combined, these epitopes covered 89.03% of the global population. The shortlisted epitopes exhibited a strong binding affinity for the B- and T-cell reference set of alleles, high antigenicity score, nonallergenic nature, high solubility, nontoxicity, and excellent binders of DRB1*0101. Through the use of appropriate linkers and adjuvation with a suitable adjuvant molecule, the epitopes were designed into a chimeric vaccine. An adjuvant was linked to the connected epitopes to boost immunogenicity and efficiently engage both innate and adaptive immunity. The physiochemical properties of the vaccine were observed favorable, leading toward the 3D modeling of the construct. Furthermore, the vaccine’s binding confirmation to the TLR-4 critical innate immune receptor was also determined using molecular docking and molecular dynamics (MD) simulations, which shows that the vaccine has a strong binding affinity for TLR4 (−29.4452 kcal/mol in MM-GBSA and −42.3229 kcal/mol in MM-PBSA). Overall, the vaccine described here has a promising potential for eliciting protective and targeted immunogenicity, subject to further experimental testing.
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112
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Naveed M, Ali U, Karobari MI, Ahmed N, Mohamed RN, Abullais SS, Kader MA, Marya A, Messina P, Scardina GA. A Vaccine Construction against COVID-19-Associated Mucormycosis Contrived with Immunoinformatics-Based Scavenging of Potential Mucoralean Epitopes. Vaccines (Basel) 2022; 10:664. [PMID: 35632420 PMCID: PMC9147184 DOI: 10.3390/vaccines10050664] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/16/2022] [Accepted: 04/19/2022] [Indexed: 01/09/2023] Open
Abstract
Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92-98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of -896.0, -948.4, and -925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.
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Affiliation(s)
- Muhammad Naveed
- Department of Biotechnology, Faculty of Life Sciences, University of Central Punjab, Lahore 54000, Pakistan; (M.N.); (U.A.)
| | - Urooj Ali
- Department of Biotechnology, Faculty of Life Sciences, University of Central Punjab, Lahore 54000, Pakistan; (M.N.); (U.A.)
| | - Mohmed Isaqali Karobari
- Center for Transdisciplinary Research (CFTR), Saveetha Institute of Medical and Technical Sciences, Saveetha Dental College, Saveetha University, Chennai 600077, India
- Department of Restorative Dentistry & Endodontics, Faculty of Dentistry, University of Puthisastra, Phnom Penh 12211, Cambodia
| | - Naveed Ahmed
- Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia;
| | - Roshan Noor Mohamed
- Department of Pediatric Dentistry, Faculty of Dentistry, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | - Shahabe Saquib Abullais
- Department of Periodontics and Community Dental Sciences, College of Dentistry, King Khalid University, Abha 61421, Saudi Arabia;
| | - Mohammed Abdul Kader
- Department Restorative Dental Science, College of Dentistry, King Khalid University, Abha 61421, Saudi Arabia;
| | - Anand Marya
- Department of Orthodontics, University of Puthisastra, Phnom Penh 12211, Cambodia;
| | - Pietro Messina
- Department of Surgical, Oncological and Stomatological Disciplines, University of Palermo, 90133 Palermo, Italy;
| | - Giuseppe Alessandro Scardina
- Department of Surgical, Oncological and Stomatological Disciplines, University of Palermo, 90133 Palermo, Italy;
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113
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Designing of a Novel Multi-Antigenic Epitope-Based Vaccine against E. hormaechei: An Intergraded Reverse Vaccinology and Immunoinformatics Approach. Vaccines (Basel) 2022; 10:vaccines10050665. [PMID: 35632421 PMCID: PMC9143018 DOI: 10.3390/vaccines10050665] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/15/2022] [Accepted: 04/20/2022] [Indexed: 12/14/2022] Open
Abstract
Enterobacter hormaechei is involved in multiple hospital-associated infections and is resistant to beta-lactam and tetracycline antibiotics. Due to emerging antibiotics resistance in E. hormaechei and lack of licensed vaccine availability, efforts are required to overcome the antibiotics crisis. In the current research study, a multi-epitope-based vaccine against E. hormaechei was designed using reverse vaccinology and immunoinformatic approaches. A total number of 50 strains were analyzed from which the core proteome was extracted. One extracellular (curlin minor subunit CsgB) and two periplasmic membrane proteins (flagellar basal-body rod protein (FlgF) and flagellar basal body P-ring protein (FlgI) were prioritized for B and T-cell epitope prediction. Only three filtered TPGKMDYTS, GADMTPGKM and RLSAESQAT epitopes were used when designing the vaccine construct. The epitopes were linked via GPGPG linkers and EAAAK linker-linked cholera toxin B-subunit adjuvant was used to enhance the immune stimulation efficacy of the vaccine. Docking studies of the vaccine construct with immune cell receptors revealed better interactions, vital for generating proper immune reactions. Docked complexes of vaccine with MHC-I, MHC-II and Tool-like receptor 4 (TLR-4) reported the lowest binding energy of −594.1 kcal/mol, −706.7 kcal/mol, −787.2 kcal/mol, respectively, and were further subjected to molecular dynamic simulations. Net binding free energy calculations also confirmed that the designed vaccine has a strong binding affinity for immune receptors and thus could be a good vaccine candidate for future experimental investigations.
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114
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Vuoristo S, Bhagat S, Hydén-Granskog C, Yoshihara M, Gawriyski L, Jouhilahti EM, Ranga V, Tamirat M, Huhtala M, Kirjanov I, Nykänen S, Krjutškov K, Damdimopoulos A, Weltner J, Hashimoto K, Recher G, Ezer S, Paluoja P, Paloviita P, Takegami Y, Kanemaru A, Lundin K, Airenne TT, Otonkoski T, Tapanainen JS, Kawaji H, Murakawa Y, Bürglin TR, Varjosalo M, Johnson MS, Tuuri T, Katayama S, Kere J. DUX4 is a multifunctional factor priming human embryonic genome activation. iScience 2022; 25:104137. [PMID: 35402882 PMCID: PMC8990217 DOI: 10.1016/j.isci.2022.104137] [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: 06/04/2021] [Revised: 02/04/2022] [Accepted: 03/18/2022] [Indexed: 12/13/2022] Open
Abstract
Double homeobox 4 (DUX4) is expressed at the early pre-implantation stage in human embryos. Here we show that induced human DUX4 expression substantially alters the chromatin accessibility of non-coding DNA and activates thousands of newly identified transcribed enhancer-like regions, preferentially located within ERVL-MaLR repeat elements. CRISPR activation of transcribed enhancers by C-terminal DUX4 motifs results in the increased expression of target embryonic genome activation (EGA) genes ZSCAN4 and KHDC1P1. We show that DUX4 is markedly enriched in human zygotes, followed by intense nuclear DUX4 localization preceding and coinciding with minor EGA. DUX4 knockdown in human zygotes led to changes in the EGA transcriptome but did not terminate the embryos. We also show that the DUX4 protein interacts with the Mediator complex via the C-terminal KIX binding motif. Our findings contribute to the understanding of DUX4 as a regulator of the non-coding genome.
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Affiliation(s)
- Sanna Vuoristo
- Department of Biosciences and Nutrition, Karolinska Institutet, 17177 Huddinge, Sweden.,Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
| | - Shruti Bhagat
- Department of Biosciences and Nutrition, Karolinska Institutet, 17177 Huddinge, Sweden.,RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Instutute for the Advanced Study of Human Biology, Kyoto University, Kyoto 606-8501, Japan
| | | | - Masahito Yoshihara
- Department of Biosciences and Nutrition, Karolinska Institutet, 17177 Huddinge, Sweden
| | - Lisa Gawriyski
- Institute of Biotechnology, University of Helsinki, 00790 Helsinki, Finland
| | - Eeva-Mari Jouhilahti
- Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland
| | - Vipin Ranga
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, 20520 Turku, Finland
| | - Mahlet Tamirat
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, 20520 Turku, Finland
| | - Mikko Huhtala
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, 20520 Turku, Finland
| | - Ida Kirjanov
- Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
| | - Sonja Nykänen
- Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
| | - Kaarel Krjutškov
- Department of Biosciences and Nutrition, Karolinska Institutet, 17177 Huddinge, Sweden.,Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland.,Competence Centre for Health Technologies, 51010 Tartu, Estonia.,University of Tartu, Department of Obstetrics and Gynecology, Institute of Clinical Medicine, 50406 Tartu, Estonia
| | | | - Jere Weltner
- Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland
| | - Kosuke Hashimoto
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan
| | - Gaëlle Recher
- Laboratoire Photonique Numérique et Nanosciences, CNRS, Institut d'Optique Graduate School, University of Bordeaux, UMR 5298, 33400 Bordeaux, France
| | - Sini Ezer
- Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland.,Folkhälsan Research Center, 00290 Helsinki, Finland
| | - Priit Paluoja
- Competence Centre for Health Technologies, 51010 Tartu, Estonia.,Institute of Clinical Medicine, University of Tartu, 50090 Tartu, Estonia.,University of Helsinki, Doctoral Program in Population Health, 00014 Helsinki, Finland
| | - Pauliina Paloviita
- Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
| | | | | | - Karolina Lundin
- Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland
| | - Tomi T Airenne
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, 20520 Turku, Finland
| | - Timo Otonkoski
- Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland.,Children's Hospital, Helsinki University Central Hospital, 00290
| | - Juha S Tapanainen
- Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland.,Reproductive Medicine Unit, Helsinki University Hospital, 00290 Helsinki, Finland.,Oulu University Hospital, 90220 Oulu, Finland
| | - Hideya Kawaji
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,RIKEN Preventive Medicine and Diagnosis Innovation Program, Wako 351-0198, Japan.,Tokyo Metropolitan Institute of Medical Science, Tokyo 156-8506, Japan
| | - Yasuhiro Murakawa
- RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.,Instutute for the Advanced Study of Human Biology, Kyoto University, Kyoto 606-8501, Japan.,IFOM, The FIRC Institute of Molecular Oncology, 20139 Milan, Italy.,Department of Medical Systems Genomics, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan
| | - Thomas R Bürglin
- Department of Biomedicine, University of Basel, 4031 Basel, Switzerland
| | - Markku Varjosalo
- Institute of Biotechnology, University of Helsinki, 00790 Helsinki, Finland
| | - Mark S Johnson
- Structural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, 20520 Turku, Finland
| | - Timo Tuuri
- Department of Obstetrics and Gynecology, 00014, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland.,Reproductive Medicine Unit, Helsinki University Hospital, 00290 Helsinki, Finland
| | - Shintaro Katayama
- Department of Biosciences and Nutrition, Karolinska Institutet, 17177 Huddinge, Sweden.,Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland.,Folkhälsan Research Center, 00290 Helsinki, Finland
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, 17177 Huddinge, Sweden.,Stem Cells and Metabolism Research Program, University of Helsinki, 00014 Helsinki, Finland.,Folkhälsan Research Center, 00290 Helsinki, Finland
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115
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Designing of a Recombinant Multi-Epitopes Based Vaccine against Enterococcus mundtii Using Bioinformatics and Immunoinformatics Approaches. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19063729. [PMID: 35329417 PMCID: PMC8949936 DOI: 10.3390/ijerph19063729] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/16/2022] [Accepted: 03/18/2022] [Indexed: 12/14/2022]
Abstract
Enterococcus species are an emerging group of bacterial pathogens that have a significant role in hospital-associated infections and are associated with higher mortality and morbidity rates. Among these pathogens, Enterococcus mundtii is one of the causative agents of multiple hospital associated infections. Currently, no commercially available licensed vaccine is present, and multi-drug resistant strains of the pathogen are prominent. Due to several limitations of experimental vaccinology, computational vaccine designing proved to be helpful in vaccine designing against several bacterial pathogens. Herein, we designed a multi-epitope-based vaccine against E. mundtii using in silico approaches. After an in-depth analysis of the core genome, three probable antigenic proteins (lytic polysaccharide monooxygenase, siderophore ABC transporter substrate-binding protein, and lytic polysaccharide monooxygenase) were shortlisted for epitope prediction. Among predicted epitopes, ten epitopes-GPADGRIAS, TTINHGGAQA, SERTALSVTT, GDGGNGGGEV, GIKEPDLEK, KQADDRIEA, QAIGGDTSN, EPLDEQTASR, AQWEPQSIEA, QPLKFSDFEL-were selected for multi-epitope vaccine construct designing. The screened B- and T-cell epitopes were joined with each other via specific linkers and linked to the cholera toxin B subunit as an adjuvant to enhance vaccine immune protection efficacy. The designed vaccine construct induced cellular and humoral immune responses. Blind docking with immune cell receptors, followed by molecular dynamic simulation results confirms the good binding potency and stability of the vaccine in providing protection against the pathogen.
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116
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Soltan MA, Behairy MY, Abdelkader MS, Albogami S, Fayad E, Eid RA, Darwish KM, Elhady SS, Lotfy AM, Alaa Eldeen M. In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes. Front Med (Lausanne) 2022; 9:829467. [PMID: 35308494 PMCID: PMC8931290 DOI: 10.3389/fmed.2022.829467] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 01/21/2022] [Indexed: 12/20/2022] Open
Abstract
Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.
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Affiliation(s)
- Mohamed A. Soltan
- Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai University, Ismailia, Egypt
| | - Mohammed Y. Behairy
- Department of Microbiology and Immunology, Faculty of Pharmacy, University of Sadat City, Sadat City, Egypt
| | - Mennatallah S. Abdelkader
- Department of Microbiology and Immunology, Faculty of Pharmacy, Suez Canal University, Ismailia, Egypt
| | - Sarah Albogami
- Department of Biotechnology, College of Science, Taif University, Taif, Saudi Arabia
| | - Eman Fayad
- Department of Biotechnology, College of Science, Taif University, Taif, Saudi Arabia
| | - Refaat A. Eid
- Department of Pathology, College of Medicine, King Khalid University, Abha, Saudi Arabia
| | - Khaled M. Darwish
- Department of Medicinal Chemistry, Faculty of Pharmacy, Suez Canal University, Ismailia, Egypt
| | - Sameh S. Elhady
- Department of Natural Products, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ahmed M. Lotfy
- Department of Pharmacology, Faculty of Veterinary Medicine, Zagazig University, Zagazig, Egypt
| | - Muhammad Alaa Eldeen
- Division of Cell Biology, Histology and Genetics, Department of Zoology, Faculty of Science, Zagazig University, Zagazig, Egypt
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117
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Immunogenicity of a xenogeneic multi-epitope HER2+ breast cancer DNA vaccine targeting the dendritic cell restricted antigen-uptake receptor DEC205. Vaccine 2022; 40:2409-2419. [DOI: 10.1016/j.vaccine.2022.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 02/10/2022] [Accepted: 03/05/2022] [Indexed: 11/18/2022]
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118
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Ismail S, Abbasi SW, Yousaf M, Ahmad S, Muhammad K, Waheed Y. Design of a Multi-Epitopes Vaccine against Hantaviruses: An Immunoinformatics and Molecular Modelling Approach. Vaccines (Basel) 2022; 10:vaccines10030378. [PMID: 35335010 PMCID: PMC8953224 DOI: 10.3390/vaccines10030378] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 02/23/2022] [Accepted: 02/25/2022] [Indexed: 02/07/2023] Open
Abstract
Hantaviruses are negative-sense, enveloped, single-stranded RNA viruses of the family Hantaviridae. In recent years, rodent-borne hantaviruses have emerged as novel zoonotic viruses posing a substantial health issue and socioeconomic burden. In the current research, a reverse vaccinology approach was applied to design a multi-epitope-based vaccine against hantavirus. A set of 340 experimentally reported epitopes were retrieved from Virus Pathogen Database and Analysis Resource (ViPR) and subjected to different analyses such as antigenicity, allergenicity, solubility, IFN gamma, toxicity, and virulent checks. Finally, 10 epitopes which cleared all the filters used were linked with each other through specific GPGPG linkers to construct a multi-antigenic epitope vaccine. The designed vaccine was then joined to three different adjuvants-TLR4-agonist adjuvant, β-defensin, and 50S ribosomal protein L7/L12-using an EAAAK linker to boost up immune-stimulating responses and check the potency of vaccine with each adjuvant. The designed vaccine structures were modelled and subjected to error refinement and disulphide engineering to enhance their stability. To understand the vaccine binding affinity with immune cell receptors, molecular docking was performed between the designed vaccines and TLR4; the docked complex with a low level of global energy was then subjected to molecular dynamics simulations to validate the docking results and dynamic behaviour. The docking binding energy of vaccines with TLR4 is -29.63 kcal/mol (TLR4-agonist), -3.41 kcal/mol (β-defensin), and -11.03 kcal/mol (50S ribosomal protein L7/L12). The systems dynamics revealed all three systems to be highly stable with a root-mean-square deviation (RMSD) value within 3 Å. To test docking predictions and determine dominant interaction energies, binding free energies of vaccine(s)-TLR4 complexes were calculated. The net binding energy of the systems was as follows: TLR4-agonist vaccine with TLR4 (MM-GBSA, -1628.47 kcal/mol and MM-PBSA, -37.75 kcal/mol); 50S ribosomal protein L7/L12 vaccine with TLR4 complex (MM-GBSA, -194.62 kcal/mol and MM-PBSA, -150.67 kcal/mol); β-defensin vaccine with TLR4 complex (MM-GBSA, -9.80 kcal/mol and MM-PBSA, -42.34 kcal/mol). Finally, these findings may aid experimental vaccinologists in developing a very potent hantavirus vaccine.
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Affiliation(s)
- Saba Ismail
- Foundation University Medical College, Foundation University Islamabad, Islamabad 44000, Pakistan;
| | - Sumra Wajid Abbasi
- NUMS Department of Biological Sciences, National University of Medical Sciences, Abid Majeed Rd, The Mall, Rawalpindi 46000, Pakistan;
| | - Maha Yousaf
- Department of Biosciences, COMSATS University Islamabad, Islamabad 45550, Pakistan;
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan;
| | - Khalid Muhammad
- Department of Biology, College of Science, United Arab Emirates University, Al Ain 15551, United Arab Emirates
- Correspondence: (K.M.); (Y.W.)
| | - Yasir Waheed
- Foundation University Medical College, Foundation University Islamabad, Islamabad 44000, Pakistan;
- Correspondence: (K.M.); (Y.W.)
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Ismail S, Waheed Y, Ahmad S, Ahsan O, Abbasi SW, Sadia K. An in silico study to unveil potential drugs and vaccine chimera for HBV capsid assembly protein: combined molecular docking and dynamics simulation approach. J Mol Model 2022; 28:51. [PMID: 35112241 DOI: 10.1007/s00894-022-05042-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 01/25/2022] [Indexed: 02/07/2023]
Abstract
Humans are a major reservoir of the hepatitis B virus (HBV), therefore promising treatment and control vaccination strategies are needed to eradicate the virus. Though promising drugs and vaccines are available against HBV, still efforts are required to enrich the therapy options. Herein, the HBV assembly protein was explored to identify novel targets for future use against HBV. Computer-aided drug designing and immune-informatics techniques were employed for the identification of putative inhibitors and vaccine ensemble against HBV using capsid assembly protein. The identified drug molecule binds with high affinity to the active pocket of the protein, and several epitopes are scanned in the protein sequence. The drug molecule, besides being a good putative inhibitor, has acceptable drug-like properties. A multi-epitope vaccine is also constructed to overcome the limitations of weakly immunogenic epitopes. In contrast to the MHC II level, the set of predicted epitopes has been recognized to interact with significant numbers of HLA alleles of MHC I. Selected epitopes are extremely virulent, antigenic, nontoxic, nonallergic, have suitable affinity to bind with the prevailing DRB*0101 allele, and also spectacle 86% mediocre population coverage. A multi-epitope peptide-based vaccine chimera having 73 amino acids was designed. It emerged as substantially immunogenic, thermally stable, robust in producing cellular as well as humoral immune responses, and had competent physicochemical properties to analyze in vitro and in vivo studies. The capsid assembly protein is a in more stable nature in the presence of the drug molecule compared to the TLR3 receptor in the vaccine presence. These particulars were confirmed by exposing the docked molecules to absolute and relative binding free energy approaches of MMGBSA/PBSA. The purpose to investigate the interactions between the vaccine and a representative TLR3 immune receptor can reveal the intermolecular affinity and possible presentation mechanism of the vaccine by TLR3 to the host immune system. It was revealed that the vaccine is showing a very good affinity of binding for the TLR3 and forming a network of hydrophobic and hydrophilic interactions. Overall, the findings of this study are promising and might be useful for further experimental validations.
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Affiliation(s)
- Saba Ismail
- Foundation University Medical College, Foundation University Islamabad, DHA-I Islamabad, Islamabad, 44000, Pakistan
| | - Yasir Waheed
- Foundation University Medical College, Foundation University Islamabad, DHA-I Islamabad, Islamabad, 44000, Pakistan.
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan
| | - Omar Ahsan
- Foundation University Medical College, Foundation University Islamabad, DHA-I Islamabad, Islamabad, 44000, Pakistan
| | - Sumra Wajid Abbasi
- Department of Biological Sciences, National University of Medical Sciences, Abid Majeed Rd, The Mall, Rawalpindi, Pakistan
| | - Khulah Sadia
- Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan
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Khetan R, Curtis R, Deane CM, Hadsund JT, Kar U, Krawczyk K, Kuroda D, Robinson SA, Sormanni P, Tsumoto K, Warwicker J, Martin ACR. Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics. MAbs 2022; 14:2020082. [PMID: 35104168 PMCID: PMC8812776 DOI: 10.1080/19420862.2021.2020082] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.
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Affiliation(s)
- Rahul Khetan
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | - Robin Curtis
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | | | | | - Uddipan Kar
- Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | | | - Daisuke Kuroda
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.,Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.,Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan
| | | | - Pietro Sormanni
- Chemistry of Health, Yusuf Hamied Department of Chemistry, University of Cambridge
| | - Kouhei Tsumoto
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.,Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.,Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan.,The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Jim Warwicker
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | - Andrew C R Martin
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK
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Gong W, Pan C, Cheng P, Wang J, Zhao G, Wu X. Peptide-Based Vaccines for Tuberculosis. Front Immunol 2022; 13:830497. [PMID: 35173740 PMCID: PMC8841753 DOI: 10.3389/fimmu.2022.830497] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/10/2022] [Indexed: 12/12/2022] Open
Abstract
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.
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Affiliation(s)
- Wenping Gong
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
| | - Chao Pan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Biotechnology, Beijing, China
| | - Peng Cheng
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
- Hebei North University, Zhangjiakou City, China
| | - Jie Wang
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
| | - Guangyu Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Xueqiong Wu
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
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Designing a Recombinant Vaccine against Providencia rettgeri Using Immunoinformatics Approach. Vaccines (Basel) 2022; 10:vaccines10020189. [PMID: 35214648 PMCID: PMC8876559 DOI: 10.3390/vaccines10020189] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/19/2022] [Accepted: 01/21/2022] [Indexed: 11/23/2022] Open
Abstract
Antibiotic resistance (AR) is the resistance mechanism pattern in bacteria that evolves over some time, thus protecting the bacteria against antibiotics. AR is due to bacterial evolution to make itself fit to changing environmental conditions in a quest for survival of the fittest. AR has emerged due to the misuse and overuse of antimicrobial drugs, and few antibiotics are now left to deal with these superbug infections. To combat AR, vaccination is an effective method, used either therapeutically or prophylactically. In the current study, an in silico approach was applied for the design of multi-epitope-based vaccines against Providencia rettgeri, a major cause of traveler’s diarrhea. A total of six proteins: fimbrial protein, flagellar hook protein (FlgE), flagellar basal body L-ring protein (FlgH), flagellar hook-basal body complex protein (FliE), flagellar basal body P-ring formation protein (FlgA), and Gram-negative pili assembly chaperone domain proteins, were considered as vaccine targets and were utilized for B- and T-cell epitope prediction. The predicted epitopes were assessed for allergenicity, antigenicity, virulence, toxicity, and solubility. Moreover, filtered epitopes were utilized in multi-epitope vaccine construction. The predicted epitopes were joined with each other through specific GPGPG linkers and were joined with cholera toxin B subunit adjuvant via another EAAAK linker in order to enhance the efficacy of the designed vaccine. Docking studies of the designed vaccine construct were performed with MHC-I (PDB ID: 1I1Y), MHC-II (1KG0), and TLR-4 (4G8A). Findings of the docking study were validated through molecular dynamic simulations, which confirmed that the designed vaccine showed strong interactions with the immune receptors, and that the epitopes were exposed to the host immune system for proper recognition and processing. Additionally, binding free energies were estimated, which highlighted both electrostatic energy and van der Waals forces to make the complexes stable. Briefly, findings of the current study are promising and may help experimental vaccinologists to formulate a novel multi-epitope vaccine against P. rettgeri.
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Lin YF, Liu JJ, Chang YJ, Yu CS, Yi W, Lane HY, Lu CH. Predicting Anticancer Drug Resistance Mediated by Mutations. Pharmaceuticals (Basel) 2022; 15:ph15020136. [PMID: 35215249 PMCID: PMC8878306 DOI: 10.3390/ph15020136] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/16/2022] [Accepted: 01/21/2022] [Indexed: 02/01/2023] Open
Abstract
Cancer drug resistance presents a challenge for precision medicine. Drug-resistant mutations are always emerging. In this study, we explored the relationship between drug-resistant mutations and drug resistance from the perspective of protein structure. By combining data from previously identified drug-resistant mutations and information of protein structure and function, we used machine learning-based methods to build models to predict cancer drug resistance mutations. The performance of our combined model achieved an accuracy of 86%, a Matthews correlation coefficient score of 0.57, and an F1 score of 0.66. We have constructed a fast, reliable method that predicts and investigates cancer drug resistance in a protein structure. Nonetheless, more information is needed concerning drug resistance and, in particular, clarification is needed about the relationships between the drug and the drug resistance mutations in proteins. Highly accurate predictions regarding drug resistance mutations can be helpful for developing new strategies with personalized cancer treatments. Our novel concept, which combines protein structure information, has the potential to elucidate physiological mechanisms of cancer drug resistance.
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Affiliation(s)
- Yu-Feng Lin
- Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung 41354, Taiwan; (Y.-F.L.); (W.Y.)
| | - Jia-Jun Liu
- The Ph.D. Program of Biotechnology and Biomedical Industry, China Medical University, Taichung 40402, Taiwan; (J.-J.L.); (Y.-J.C.)
| | - Yu-Jen Chang
- The Ph.D. Program of Biotechnology and Biomedical Industry, China Medical University, Taichung 40402, Taiwan; (J.-J.L.); (Y.-J.C.)
| | - Chin-Sheng Yu
- Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40201, Taiwan;
| | - Wei Yi
- Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung 41354, Taiwan; (Y.-F.L.); (W.Y.)
| | - Hsien-Yuan Lane
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung 40402, Taiwan;
- Department of Psychiatry, China Medical University Hospital, Taichung 40402, Taiwan
- Brain Disease Research Center, China Medical University Hospital, Taichung 40402, Taiwan
| | - Chih-Hao Lu
- The Ph.D. Program of Biotechnology and Biomedical Industry, China Medical University, Taichung 40402, Taiwan; (J.-J.L.); (Y.-J.C.)
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung 40402, Taiwan;
- Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung 40402, Taiwan
- Correspondence:
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124
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In silico Design and Characterization of Multi-epitopes Vaccine for SARS-CoV2 from Its Spike Protein. Int J Pept Res Ther 2022; 28:37. [PMID: 35002585 PMCID: PMC8722413 DOI: 10.1007/s10989-021-10348-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2021] [Indexed: 11/04/2022]
Abstract
COVID 19 is a disease caused by a novel coronavirus, SARS-CoV2 originated in China most probably of Bat origin. Multiepitopes vaccine would be useful in eliminating SARS-CoV2 infections as asymptomatic patients are in large numbers. In response to this, we utilized bioinformatic tools to develop an efficient vaccine candidate against SARS-CoV2. The designed vaccine has effective BCR and TCR epitopes screened from the sequence of S-protein of SARS-CoV2. Predicted BCR and TCR epitopes found antigenic, non-toxic and probably non-allergen. Modeled and the refined tertiary structure predicted as valid for further use. Protein–Protein interaction prediction of TLR2/4 and designed vaccine indicates promising binding. The designed multiepitope vaccine has induced cell-mediated and humoral immunity along with increased interferon-gamma response. Macrophages and dendritic cells were also found to increase upon the vaccine exposure. In silico codon optimization and cloning in expression vector indicates that the vaccine can be efficiently expressed in E. coli. In conclusion, the predicted vaccine is a good antigen, probable no allergen, and has the potential to induce cellular and humoral immunity.
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125
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Math RK, Mudennavar N, Javaregowda PK, Savanur A. In Silico Comparative Analysis of the Functional, Structural, and Evolutionary Properties of SARS-CoV-2 Variant Spike Proteins. JMIR BIOINFORMATICS AND BIOTECHNOLOGY 2022; 3:e37391. [PMID: 35669291 PMCID: PMC9158474 DOI: 10.2196/37391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/25/2022] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND A recent global outbreak of COVID-19 caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) created a pandemic and emerged as a potential threat to humanity. The analysis of virus genetic composition has revealed that the spike protein, one of the major structural proteins, facilitates the entry of the virus to host cells. OBJECTIVE The spike protein has become the main target for prophylactics and therapeutics studies. Here, we compared the spike proteins of SARS-CoV-2 variants using bioinformatics tools. METHODS The spike protein sequences of wild-type SARS-CoV-2 and its 6 variants-D614G, alpha (B.1.1.7), beta (B.1.351), delta (B.1.617.2), gamma (P.1), and omicron (B.1.1.529)-were retrieved from the NCBI database. The ClustalX program was used to sequence multiple alignment and perform mutational analysis. Several online bioinformatics tools were used to predict the physiological, immunological, and structural features of the spike proteins of SARS-CoV-2 variants. A phylogenetic tree was constructed using CLC software. Statistical analysis of the data was done using jamovi 2 software. RESULTS Multiple sequence analysis revealed that the P681R mutation in the delta variant, which changed an amino acid from histidine (H) to arginine (R), made the protein more alkaline due to arginine's high pKa value (12.5) compared to histidine's (6.0). Physicochemical properties revealed the relatively higher isoelectric point (7.34) and aliphatic index (84.65) of the delta variant compared to other variants. Statistical analysis of the isoelectric point, antigenicity, and immunogenicity of all the variants revealed significant correlation, with P values ranging from <.007 to .04. The generation of a 2D gel map showed the separation of the delta spike protein from a grouping of the other variants. The phylogenetic tree of the spike proteins showed that the delta variant was close to and a mix of the Rousettus bat coronavirus and MERS-CoV. CONCLUSIONS The comparative analysis of SARS-CoV-2 variants revealed that the delta variant is more aliphatic in nature, which provides more stability to it and subsequently influences virus behavior.
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Affiliation(s)
- Renukaradhya K Math
- SDM Research Institute for Biomedical Sciences Shri Dharmasthala Manjunatheshwara University Dharwad India
| | - Nayana Mudennavar
- SDM Research Institute for Biomedical Sciences Shri Dharmasthala Manjunatheshwara University Dharwad India
| | | | - Ambuja Savanur
- SDM Research Institute for Biomedical Sciences Shri Dharmasthala Manjunatheshwara University Dharwad India
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126
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Roy RS, Quadir F, Soltanikazemi E, Cheng J. OUP accepted manuscript. Bioinformatics 2022; 38:1904-1910. [PMID: 35134816 PMCID: PMC8963319 DOI: 10.1093/bioinformatics/btac063] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 01/17/2022] [Accepted: 01/31/2022] [Indexed: 11/23/2022] Open
Abstract
Motivation Deep learning has revolutionized protein tertiary structure prediction recently. The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy tertiary structures for most individual protein chains. However, the accuracy of predicting quaternary structures of protein complexes consisting of multiple chains is still relatively low due to lack of advanced deep learning methods in the field. Because interchain residue–residue contacts can be used as distance restraints to guide quaternary structure modeling, here we develop a deep dilated convolutional residual network method (DRCon) to predict interchain residue–residue contacts in homodimers from residue–residue co-evolutionary signals derived from multiple sequence alignments of monomers, intrachain residue–residue contacts of monomers extracted from true/predicted tertiary structures or predicted by deep learning, and other sequence and structural features. Results Tested on three homodimer test datasets (Homo_std dataset, DeepHomo dataset and CASP-CAPRI dataset), the precision of DRCon for top L/5 interchain contact predictions (L: length of monomer in a homodimer) is 43.46%, 47.10% and 33.50% respectively at 6 Å contact threshold, which is substantially better than DeepHomo and DNCON2_inter and similar to Glinter. Moreover, our experiments demonstrate that using predicted tertiary structure or intrachain contacts of monomers in the unbound state as input, DRCon still performs well, even though its accuracy is lower than using true tertiary structures in the bound state are used as input. Finally, our case study shows that good interchain contact predictions can be used to build high-accuracy quaternary structure models of homodimers. Availability and implementation The source code of DRCon is available at https://github.com/jianlin-cheng/DRCon. The datasets are available at https://zenodo.org/record/5998532#.YgF70vXMKsB. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Raj S Roy
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
| | - Farhan Quadir
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
| | - Elham Soltanikazemi
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA
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Karachitos A, Grabiński W, Baranek M, Kmita H. Redox-Sensitive VDAC: A Possible Function as an Environmental Stress Sensor Revealed by Bioinformatic Analysis. Front Physiol 2021; 12:750627. [PMID: 34966287 PMCID: PMC8710658 DOI: 10.3389/fphys.2021.750627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
Voltage-dependent anion-selective channel (VDAC) allows the exchange of small metabolites and inorganic ions across the mitochondrial outer membrane. It is involved in complex interactions that regulate mitochondrial and cellular functioning. Many organisms have several VDAC paralogs that play distinct but poorly understood roles in the life and death of cells. It is assumed that such a large diversity of VDAC-encoding genes might cause physiological plasticity to cope with abiotic and biotic stresses known to impact mitochondrial function. Moreover, cysteine residues in mammalian VDAC paralogs may contribute to the reduction-oxidation (redox) sensor function based on disulfide bond formation and elimination, resulting in redox-sensitive VDAC (rsVDAC). Therefore, we analyzed whether rsVDAC is possible when only one VDAC variant is present in mitochondria and whether all VDAC paralogs present in mitochondria could be rsVDAC, using representatives of currently available VDAC amino acid sequences. The obtained results indicate that rsVDAC can occur when only one VDAC variant is present in mitochondria; however, the possibility of all VDAC paralogs in mitochondria being rsVDAC is very low. Moreover, the presence of rsVDAC may correlate with habitat conditions as rsVDAC appears to be prevalent in parasites. Thus, the channel may mediate detection and adaptation to environmental conditions.
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Affiliation(s)
- Andonis Karachitos
- Department of Bioenergetics, Faculty of Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
| | - Wojciech Grabiński
- Department of Bioenergetics, Faculty of Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
| | - Martyna Baranek
- Department of Bioenergetics, Faculty of Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
| | - Hanna Kmita
- Department of Bioenergetics, Faculty of Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznań, Poland
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Udosen B, Soremekun O, Ekenna C, Idowu Omotuyi O, Chikowore T, Nashiru O, Fatumo S. In-silico analysis reveals druggable single nucleotide polymorphisms in angiotensin 1 converting enzyme involved in the onset of blood pressure. BMC Res Notes 2021; 14:457. [PMID: 34930451 PMCID: PMC8686250 DOI: 10.1186/s13104-021-05879-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/06/2021] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE The Angiotensin 1 converting enzyme (ACE1) gene plays a critical role in regulating blood pressure and thus, it has become a major therapeutic target of antihypertensives. Single nucleotide polymorphisms (SNPs) occurring within a gene most especially at the functional segment of the genes alter the structure-function relationship of that gene. RESULTS Our study revealed that five nsSNPs of the ACE1 gene were found to be potentially deleterious and damaging and they include rs2229839, rs14507892, rs12709442, and rs4977 at point mutations P351R, R953Q, I1018T, F1051V, and T1187M. The protein stability predictive tools revealed that all the nsSNPs decreased stability of the protein and the Consurf server which estimates the evolutionary conservation profile of a protein showed that three mutants were in the highly conserved region. In conclusion, this study predicted potential druggable deleterious mutants that can be further explored to understand the pathological basis of cardiovascular disease.
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Affiliation(s)
- Brenda Udosen
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda
- The African Center of Excellence in Bioinformatics of Bamako (ACE-B), University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
| | - Opeyemi Soremekun
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda
| | | | - Olaposi Idowu Omotuyi
- Department of Biochemistry, Adekunle Ajasin University, Akungba-Akoko, Ondo State, Nigeria
| | - Tinashe Chikowore
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Oyekanmi Nashiru
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI, and LSHTM, Entebbe, Uganda.
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
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129
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Madani M, Lin K, Tarakanova A. DSResSol: A Sequence-Based Solubility Predictor Created with Dilated Squeeze Excitation Residual Networks. Int J Mol Sci 2021; 22:13555. [PMID: 34948354 PMCID: PMC8704505 DOI: 10.3390/ijms222413555] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 12/13/2021] [Accepted: 12/14/2021] [Indexed: 11/16/2022] Open
Abstract
Protein solubility is an important thermodynamic parameter that is critical for the characterization of a protein's function, and a key determinant for the production yield of a protein in both the research setting and within industrial (e.g., pharmaceutical) applications. Experimental approaches to predict protein solubility are costly, time-consuming, and frequently offer only low success rates. To reduce cost and expedite the development of therapeutic and industrially relevant proteins, a highly accurate computational tool for predicting protein solubility from protein sequence is sought. While a number of in silico prediction tools exist, they suffer from relatively low prediction accuracy, bias toward the soluble proteins, and limited applicability for various classes of proteins. In this study, we developed a novel deep learning sequence-based solubility predictor, DSResSol, that takes advantage of the integration of squeeze excitation residual networks with dilated convolutional neural networks and outperforms all existing protein solubility prediction models. This model captures the frequently occurring amino acid k-mers and their local and global interactions and highlights the importance of identifying long-range interaction information between amino acid k-mers to achieve improved accuracy, using only protein sequence as input. DSResSol outperforms all available sequence-based solubility predictors by at least 5% in terms of accuracy when evaluated by two different independent test sets. Compared to existing predictors, DSResSol not only reduces prediction bias for insoluble proteins but also predicts soluble proteins within the test sets with an accuracy that is at least 13% higher than existing models. We derive the key amino acids, dipeptides, and tripeptides contributing to protein solubility, identifying glutamic acid and serine as critical amino acids for protein solubility prediction. Overall, DSResSol can be used for the fast, reliable, and inexpensive prediction of a protein's solubility to guide experimental design.
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Affiliation(s)
- Mohammad Madani
- Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA;
- Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA;
| | - Kaixiang Lin
- Department of Computer Science & Engineering, University of Connecticut, Storrs, CT 06269, USA;
| | - Anna Tarakanova
- Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA;
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA
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130
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Khalid K, Irum S, Ullah SR, Andleeb S. In-Silico Vaccine Design Based on a Novel Vaccine Candidate Against Infections Caused by Acinetobacter baumannii. Int J Pept Res Ther 2021; 28:16. [PMID: 34873398 PMCID: PMC8636788 DOI: 10.1007/s10989-021-10316-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/26/2021] [Indexed: 12/24/2022]
Abstract
Acinetobacter baumannii is notorious for causing serious infections of the skin, lungs, soft tissues, bloodstream, and urinary tract. Despite the overwhelming information available so far, there has still been no approved vaccine in the market to prevent these infections. Therefore, this study focuses on developing a rational vaccine design using the technique of epitope mapping to curb the infections caused by A. baumannii. An outer membrane protein with immunogenic potential as well as all the properties of a good vaccine candidate was selected and used to calculate epitopes for selection on the basis of a low percentile rank, high binding scores, good immunological properties, and non-allergenicity. Thus, a 240 amino-acid vaccine sequence was obtained by manually joining all the epitopes in sequence-wise manner with the appropriate linkers, namely AAY, GPGPG, and EAAAK. Additionally, a 50S ribosomal protein L7/L12, agonist to the human innate immune receptors was attached to the N-terminus to increase the overall immune response towards the vaccine. As a result, enhanced overall protein stability, expression, immunostimulatory capabilities, and solubility of the designed construct were observed. Molecular dynamic simulations revealed the compactness and stability of the polypeptide construct. Moreover, molecular docking exhibited strong binding of the designed vaccine with TLR-4 and TLR-9. In-silico immune simulations indicated an immense increment in T-cell and B-cell populations. Bioinformatic tools also significantly assisted with optimizing codons which allowed for successful cloning of constructs into desired host vectors. Using in-silico tools to design a vaccine against A. baumannii demonstrated that this construct could pave the way for successfully combating infections caused by multidrug-resistant bacteria.
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Affiliation(s)
- Kashaf Khalid
- Department of Industrial Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000 Pakistan
| | - Sidra Irum
- Department of Industrial Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000 Pakistan
| | - Sidra Rahmat Ullah
- Department of Industrial Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000 Pakistan
| | - Saadia Andleeb
- Department of Industrial Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000 Pakistan
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131
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Mugunthan SP, Mani Chandra H. A Computational Reverse Vaccinology Approach for the Design and Development of Multi-Epitopic Vaccine Against Avian Pathogen Mycoplasma gallisepticum. Front Vet Sci 2021; 8:721061. [PMID: 34765664 PMCID: PMC8577832 DOI: 10.3389/fvets.2021.721061] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 09/21/2021] [Indexed: 01/28/2023] Open
Abstract
Avian mycoplasma is a bacterial disease causing chronic respiratory disease (CRD) in poultry industries with high economic losses. The eradication of this disease still remains as a challenge. A multi-epitope prophylactic vaccine aiming the antigenic proteins of Mycoplasma gallisepticum can be a capable candidate to eradicate this infection. The present study is focused to design a multi-epitope vaccine candidate consisting of cytotoxic T-cell (CTL), helper T-cell (HTL), and B-cell epitopes of antigenic proteins, using immunoinformatics strategies. The multi-epitopic vaccine was designed, and its tertiary model was predcited, which was further refined and validated by computational tools. After initial validation, molecular docking was performed between multi-epitope vaccine construct and chicken TLR-2 and 5 receptors, which predicted effective binding. The in silico results specify the structural stability, precise specificity, and immunogenic response of the designed multi-epitope vaccine, and it could be an appropriate vaccine candidate for the M. gallisepticum infection.
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Affiliation(s)
| | - Harish Mani Chandra
- Plant Genetic Engineering and Molecular Farming Lab, Department of Biotechnology, Thiruvalluvar University, Vellore, India
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132
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Albutti A. An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis. Sci Rep 2021; 11:21929. [PMID: 34753983 PMCID: PMC8578660 DOI: 10.1038/s41598-021-01283-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/25/2021] [Indexed: 12/17/2022] Open
Abstract
Tuberculosis (TB) is a highly contagious disease that mostly affects the lungs and is caused by a bacterial pathogen, Mycobacterium tuberculosis. The associated mortality rate of TB is much higher compared to any other disease and the situation is more worrisome by the rapid emergence of drug resistant strains. Bacillus Calmette-Guerin (BCG) is the only licensed attenuated vaccine available for use in humans however, many countries have stopped its use as it fails to confer protective immunity. Therefore, urgent efforts are required to identify new and safe vaccine candidates that are not only provide high immune protection but also have broad spectrum applicability. Considering this, herein, I performed an extensive computational vaccine analysis to investigate 200 complete sequenced genomes of M. tuberculosis to identify core vaccine candidates that harbor safe, antigenic, non-toxic, and non-allergic epitopes. To overcome literature reported limitations of epitope-based vaccines, I carried out additional analysis by designing a multi-epitopes vaccine to achieve maximum protective immunity as well as to make experimental follow up studies easy by selecting a vaccine that can be easily analyzed because of its favorable physiochemical profile. Based on these analyses, I identified two potential vaccine proteins that fulfill all required vaccine properties. These two vaccine proteins are diacylglycerol acyltransferase and ESAT-6-like protein. Epitopes: DSGGYNANS from diacylglycerol acyltransferase and AGVQYSRAD, ADEEQQQAL, and VSRADEEQQ from ESAT-6-like protein were found to cover all necessary parameters and thus used in a multi-epitope vaccine construct. The designed vaccine is depicting a high binding affinity for different immune receptors and shows stable dynamics and rigorous van der Waals and electrostatic binding energies. The vaccine also simulates profound primary, secondary, tertiary immunoglobulin production as well as high interleukins and interferons count. In summary, the designed vaccine is ideal to be evaluated experimentally to decipher its real biological efficacy in controlling drug resistant infections of M. tuberculosis.
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Affiliation(s)
- Aqel Albutti
- Department of Medical Biotechnology, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia.
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133
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Soltan MA, Eldeen MA, Elbassiouny N, Kamel HL, Abdelraheem KM, El-Gayyed HA, Gouda AM, Sheha MF, Fayad E, Ali OAA, Ghany KAE, El-damasy DA, Darwish KM, Elhady SS, Sileem AE. In Silico Designing of a Multitope Vaccine against Rhizopus microsporus with Potential Activity against Other Mucormycosis Causing Fungi. Cells 2021; 10:3014. [PMID: 34831237 PMCID: PMC8616407 DOI: 10.3390/cells10113014] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 10/27/2021] [Accepted: 10/27/2021] [Indexed: 12/27/2022] Open
Abstract
During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, β-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.
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Affiliation(s)
- Mohamed A. Soltan
- Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai University, Ismailia 41611, Egypt;
| | - Muhammad Alaa Eldeen
- Cell Biology, Histology & Genetics Division, Zoology Department, Faculty of Science, Zagazig University, Zagazig 44519, Egypt;
| | - Nada Elbassiouny
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Sinai University, Ismailia 41611, Egypt;
| | - Hasnaa L. Kamel
- Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai University, Ismailia 41611, Egypt;
| | - Kareem M. Abdelraheem
- Department of Biochemistry, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt; (K.M.A.); (H.A.E.-G.)
| | - Hanaa Abd El-Gayyed
- Department of Biochemistry, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt; (K.M.A.); (H.A.E.-G.)
| | - Ahmed M. Gouda
- Department of Pharmacy Practice, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt;
| | - Mohammed F. Sheha
- Department of Biochemistry, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt;
| | - Eman Fayad
- Department of Biotechnology, Faculty of Sciences, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | - Ola A. Abu Ali
- Department of Chemistry, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | | | - Dalia A. El-damasy
- Department of Microbiology and Immunology, Faculty of Pharmacy, Egyptian Russian University, Cairo 11829, Egypt;
| | - Khaled M. Darwish
- Department of Medicinal Chemistry, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt;
| | - Sameh S. Elhady
- Department of Natural Products, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia;
| | - Ashraf E. Sileem
- Department of Chest Diseases, Faculty of Medicine, Zagazig University, Zagazig 44519, Egypt;
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134
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Jin C, Gao J, Shi Z, Zhang H. ATTCry: Attention-based neural network model for protein crystallization prediction. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2021.08.029] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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135
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Ullah A, Ahmad S, Ismail S, Afsheen Z, Khurram M, Tahir ul Qamar M, AlSuhaymi N, Alsugoor MH, Allemailem KS. Towards A Novel Multi-Epitopes Chimeric Vaccine for Simulating Strong Immune Responses and Protection against Morganella morganii. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:10961. [PMID: 34682706 PMCID: PMC8535705 DOI: 10.3390/ijerph182010961] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/11/2021] [Accepted: 10/13/2021] [Indexed: 12/16/2022]
Abstract
Morganella morganii is one of the main etiological agents of hospital-acquired infections and no licensed vaccine is available against the pathogen. Herein, we designed a multi-epitope-based vaccine against M. morganii. Predicted proteins from fully sequenced genomes of the pathogen were subjected to a core sequences analysis, followed by the prioritization of non-redundant, host non-homologous and extracellular, outer membrane and periplasmic membrane virulent proteins as vaccine targets. Five proteins (TonB-dependent siderophore receptor, serralysin family metalloprotease, type 1 fimbrial protein, flagellar hook protein (FlgE), and pilus periplasmic chaperone) were shortlisted for the epitope prediction. The predicted epitopes were checked for antigenicity, toxicity, solubility, and binding affinity with the DRB*0101 allele. The selected epitopes were linked with each other through GPGPG linkers and were joined with the cholera toxin B subunit (CTBS) to boost immune responses. The tertiary structure of the vaccine was modeled and blindly docked with MHC-I, MHC-II, and Toll-like receptors 4 (TLR4). Molecular dynamic simulations of 250 nanoseconds affirmed that the designed vaccine showed stable conformation with the receptors. Further, intermolecular binding free energies demonstrated the domination of both the van der Waals and electrostatic energies. Overall, the results of the current study might help experimentalists to develop a novel vaccine against M. morganii.
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Affiliation(s)
- Asad Ullah
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (Z.A.); (M.K.)
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (Z.A.); (M.K.)
| | - Saba Ismail
- Department of Biological Sciences, National University of Medical Sciences, Rawalpindi 46000, Pakistan;
| | - Zobia Afsheen
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (Z.A.); (M.K.)
| | - Muhammad Khurram
- Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan; (A.U.); (Z.A.); (M.K.)
- Department of Pharmacy, Abasyn University, Peshawar 25000, Pakistan
| | | | - Naif AlSuhaymi
- Department of Emergency Medical Services, Faculty of Health Sciences, AlQunfudah, Umm Al-Qura University, Makkah 21912, Saudi Arabia; (N.A.); (M.H.A.)
| | - Mahdi H. Alsugoor
- Department of Emergency Medical Services, Faculty of Health Sciences, AlQunfudah, Umm Al-Qura University, Makkah 21912, Saudi Arabia; (N.A.); (M.H.A.)
| | - Khaled S. Allemailem
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia
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136
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Identification of immunodominant epitopes in allelic variants VK210 and VK247 of Plasmodium Vivax Circumsporozoite immunogen. INFECTION GENETICS AND EVOLUTION 2021; 96:105120. [PMID: 34655808 DOI: 10.1016/j.meegid.2021.105120] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 10/06/2021] [Accepted: 10/11/2021] [Indexed: 11/23/2022]
Abstract
Plasmodium vivax-induced malaria is among the leading causes of morbidity and mortality in sub-tropical and tropical regions and infect 2.85 billion people globally. The continual rise and propagation of resistance against anti-malarial drugs is a prerequisite to develop a potent vaccine candidate for Plasmodium vivax (P. vivax). Circumsporozoite protein (CSP) is an important immunogen of malaria parasite that has the conserved CSP structure as an immune dominant B-cell epitope. In current study, we focused on designing multi-epitope vaccines (MEVs) using various immunoinformatics tools against Pakistani based allelic variants VK210 and VK247 of P. vivax CSP (PvCSP) gene. Antigenicity, allergic potential and physicochemical parameters of both PvCSP variants were assessed for the designed MEVs and they were within acceptable range suitable for post experimental investigations. The three-dimensional structures of both MEVs have been predicted ab initio, optimized, and validated by using different online servers. The both MEVs candidates were stable and free from aggregation-prone regions. The stability of both MEVs had been improved by a disulfide engineering approach. To estimate the binding energy and stability of the MEVs, molecular docking simulation and binding free energy calculations with TLR-4 immune receptor have been conducted. The docking score of PvCSP210 and PvCSP247 for TLR-4 was -6.34 kJ/mol and - 2.3 kJ/mol, respectively. For PvCSP210-TLR4 system, mean RMSD was 4.96 Å while PvCSP247-TLR4 system, average RMSD was 4.49 Å. The binding free energy of PvCSP210-TLR4 complex and PvCSP247-TLR4 complex was -50.49/-117.15 kcal/mol (MMGBSA/MMPSA) and -52.94/-96.26 kcal/mol (MMGBSA/MMPSA), respectively. The expression of both MEVs produced in Escherichia coli K12 expression system by in silico cloning was significant. Immune simulation revealed that the proposed MEVs induce strong humoral and cellular immunological responses, in addition to significant production of interleukins and cytokines. In conclusions, we believed that the MEVs proposed in current research, using combine approach of immunoinformatics, structural biology and biophysical approaches, could induce protective and effective immune responses against P. vivax and the experimental validation of our findings could contribute to the development of potential malaria vaccine.
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137
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Adhikari UK, Tayebi M. Epitope-specific anti-PrP antibody toxicity: a comparative in-silico study of human and mouse prion proteins. Prion 2021; 15:155-176. [PMID: 34632945 PMCID: PMC8900626 DOI: 10.1080/19336896.2021.1964326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
Abstract
Despite having therapeutic potential, anti-PrP antibodies caused a major controversy due to their neurotoxic effects. For instance, treating mice with ICSM antibodies delayed prion disease onset, but both were found to be either toxic or innocuous to neurons by researchers following cross-linking PrPC. In order to elucidate and understand the reasons that led to these contradictory outcomes, we conducted a comprehensive in silico study to assess the antibody-specific toxicity. Since most therapeutic anti-PrP antibodies were generated against human truncated recombinant PrP91-231 or full-length mouse PrP23-231, we reasoned that host specificity (human vs murine) of PrPC might influence the nature of the specific epitopes recognized by these antibodies at the structural level possibly explaining the 'toxicity' discrepancies reported previously. Initially, molecular dynamics simulation and pro-motif analysis of full-length human (hu)PrP and mouse (mo)PrP 3D structure displayed conspicuous structural differences between huPrP and moPrP. We identified 10 huPrP and 6 moPrP linear B-cell epitopes from the prion protein 3D structure where 5 out of 10 huPrP and 3 out of 6 moPrP B-cell epitopes were predicted to be potentially toxic in immunoinformatics approaches. Herein, we demonstrate that some of the predicted potentially 'toxic' epitopes identified by the in silico analysis were similar to the epitopes recognized by the toxic antibodies such as ICSM18 (146-159), POM1 (138-147), D18 (133-157), ICSM35 (91-110), D13 (95-103) and POM3 (95-100). This in silico study reveals the role of host specificity of PrPC in epitope-specific anti-PrP antibody toxicity.
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Affiliation(s)
| | - Mourad Tayebi
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
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138
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Lu H, Li F, Yuan L, Domenzain I, Yu R, Wang H, Li G, Chen Y, Ji B, Kerkhoven EJ, Nielsen J. Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection. Mol Syst Biol 2021; 17:e10427. [PMID: 34676984 PMCID: PMC8532513 DOI: 10.15252/msb.202110427] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 10/02/2021] [Accepted: 10/04/2021] [Indexed: 12/24/2022] Open
Abstract
Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome-scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence-level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.
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Affiliation(s)
- Hongzhong Lu
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Feiran Li
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Le Yuan
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Iván Domenzain
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Rosemary Yu
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Hao Wang
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- National Bioinformatics Infrastructure SwedenScience for Life LaboratoryChalmers University of TechnologyGothenburgSweden
| | - Gang Li
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Yu Chen
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Boyang Ji
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- The Novo Nordisk Foundation Center for BiosustainabilityTechnical University of DenmarkLyngbyDenmark
| | - Eduard J Kerkhoven
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Jens Nielsen
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- The Novo Nordisk Foundation Center for BiosustainabilityTechnical University of DenmarkLyngbyDenmark
- BioInnovation InstituteCopenhagen NDenmark
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139
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Allemailem KS. A Comprehensive Computer Aided Vaccine Design Approach to Propose a Multi-Epitopes Subunit Vaccine against Genus Klebsiella Using Pan-Genomics, Reverse Vaccinology, and Biophysical Techniques. Vaccines (Basel) 2021; 9:1087. [PMID: 34696195 PMCID: PMC8540426 DOI: 10.3390/vaccines9101087] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 09/17/2021] [Accepted: 09/24/2021] [Indexed: 01/04/2023] Open
Abstract
Klebsiella is a genus of nosocomial bacterial pathogens and is placed in the most critical list of World Health Organization (WHO) for development of novel therapeutics. The pathogens of the genus are associated with high mortality and morbidity. Owing to their strong resistance profile against different classes of antibiotics and nonavailability of a licensed vaccine, urgent efforts are required to develop a novel vaccine candidate that can tackle all pathogenic species of the Klebsiella genus. The present study aims to design a broad-spectrum vaccine against all species of the Klebsiella genus with objectives to identify the core proteome of pathogen species, prioritize potential core vaccine proteins, analyze immunoinformatics of the vaccine proteins, construct a multi-epitopes vaccine, and provide its biophysical analysis. Herein, we investigated all reference species of the genus to reveal their core proteome. The core proteins were then subjected to multiple reverse vaccinology checks that are mandatory for the prioritization of potential vaccine candidates. Two proteins (TonB-dependent siderophore receptor and siderophore enterobactin receptor FepA) were found to fulfill all vaccine parameters. Both these proteins harbor several potent B-cell-derived T-cell epitopes that are antigenic, nonallergic, nontoxic, virulent, water soluble, IFN-γ producer, and efficient binder of DRB*0101 allele. The selected epitopes were modeled into a multi-epitope peptide comprising linkers and Cholera Toxin B adjuvant. For docking with innate immune and MHC receptors and afterward molecular dynamics simulations and binding free energy analysis, the vaccine structure was modeled for tertiary structure and refined for structural errors. To assess the binding affinity and presentation of the designed vaccine construct, binding mode and interactions analysis were performed using molecular docking and molecular dynamics simulation techniques. These biophysical approaches illustrated the vaccine as a good binder to the immune receptors and revealed robust interactions energies. The vaccine sequence was further translated to nucleotide sequence and cloned into an appropriate vector for expressing it at high rate in Escherichia coli K12 strain. In addition, the vaccine was illustrated to generate a good level of primary, secondary, and tertiary immune responses, proving good immunogenicity of the vaccine. Based on the reported results, the vaccine can be a good candidate to be evaluated for effectiveness in wet laboratory validation studies.
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Affiliation(s)
- Khaled S Allemailem
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia
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140
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Lei Y, Li S, Liu Z, Wan F, Tian T, Li S, Zhao D, Zeng J. A deep-learning framework for multi-level peptide-protein interaction prediction. Nat Commun 2021; 12:5465. [PMID: 34526500 PMCID: PMC8443569 DOI: 10.1038/s41467-021-25772-4] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 08/27/2021] [Indexed: 12/12/2022] Open
Abstract
Peptide-protein interactions are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. Recently, a number of computational methods have been developed to predict peptide-protein interactions. However, most of the existing prediction approaches heavily depend on high-resolution structure data. Here, we present a deep learning framework for multi-level peptide-protein interaction prediction, called CAMP, including binary peptide-protein interaction prediction and corresponding peptide binding residue identification. Comprehensive evaluation demonstrated that CAMP can successfully capture the binary interactions between peptides and proteins and identify the binding residues along the peptides involved in the interactions. In addition, CAMP outperformed other state-of-the-art methods on binary peptide-protein interaction prediction. CAMP can serve as a useful tool in peptide-protein interaction prediction and identification of important binding residues in the peptides, which can thus facilitate the peptide drug discovery process.
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Affiliation(s)
- Yipin Lei
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, 100084, China
| | - Shuya Li
- Machine Learning Department, Silexon AI Technology Co., Ltd., Nanjing, China
| | - Ziyi Liu
- Machine Learning Department, Silexon AI Technology Co., Ltd., Nanjing, China
| | - Fangping Wan
- Machine Learning Department, Silexon AI Technology Co., Ltd., Nanjing, China
| | - Tingzhong Tian
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, 100084, China
| | - Shao Li
- Institute of TCM-X, MOE Key Laboratory of Bioinformatics, Bioinformatics Division, BNRist, Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, 100084, China.
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, 100084, China.
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141
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Jibiki K, Kodama TS, Suenaga A, Kawase Y, Shibazaki N, Nomoto S, Nagasawa S, Nagashima M, Shimodan S, Kikuchi R, Okayasu M, Takashita R, Mehmood R, Saitoh N, Yoneda Y, Akagi KI, Yasuhara N. Importin α2 association with chromatin: Direct DNA binding via a novel DNA-binding domain. Genes Cells 2021; 26:945-966. [PMID: 34519142 DOI: 10.1111/gtc.12896] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 09/10/2021] [Accepted: 09/11/2021] [Indexed: 12/18/2022]
Abstract
The nuclear transport of proteins is important for facilitating appropriate nuclear functions. The importin α family proteins play key roles in nuclear transport as transport receptors for copious nuclear proteins. Additionally, these proteins possess other functions, including chromatin association and gene regulation. However, these nontransport functions of importin α are not yet fully understood, especially their molecular-level mechanisms and consequences for functioning with chromatin. Here, we report the novel molecular characteristics of importin α binding to diverse DNA sequences in chromatin. We newly identified and characterized a DNA-binding domain-the Nucleic Acid Associating Trolley pole domain (NAAT domain)-in the N-terminal region of importin α within the conventional importin β binding (IBB) domain that is necessary for nuclear transport of cargo proteins. Furthermore, we found that the DNA binding of importin α synergistically coupled the recruitment of its cargo protein to DNA. This is the first study to delineate the interaction between importin α and chromatin DNA via the NAAT domain, indicating the bifunctionality of the importin α N-terminal region for nuclear transport and chromatin association.
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Affiliation(s)
- Kazuya Jibiki
- Graduate School of Integrated Basic Sciences, Nihon University, Tokyo, Japan
| | - Takashi S Kodama
- National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Osaka, Japan
| | - Atsushi Suenaga
- Graduate School of Integrated Basic Sciences, Nihon University, Tokyo, Japan.,Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Yota Kawase
- Graduate School of Integrated Basic Sciences, Nihon University, Tokyo, Japan
| | - Noriko Shibazaki
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Shin Nomoto
- Graduate School of Integrated Basic Sciences, Nihon University, Tokyo, Japan
| | - Seiya Nagasawa
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Misaki Nagashima
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Shieri Shimodan
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Renan Kikuchi
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Mina Okayasu
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Ruka Takashita
- Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
| | - Rashid Mehmood
- Department of Life Sciences, College of Science and General Studies, Alfaisal University, Riyadh, Saudi Arabia
| | - Noriko Saitoh
- Division of Cancer Biology, The Cancer Institute of JFCR, Tokyo, Japan
| | - Yoshihiro Yoneda
- National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Osaka, Japan
| | - Ken-Ichi Akagi
- National Institutes of Biomedical Innovation, Health and Nutrition (NIBIOHN), Osaka, Japan.,Environmental Metabolic Analysis Research Team, RIKEN Center for Sustainable Resource Science, Yokohama, Japan
| | - Noriko Yasuhara
- Graduate School of Integrated Basic Sciences, Nihon University, Tokyo, Japan.,Department of Biosciences, College of Humanities and Sciences, Nihon University, Tokyo, Japan
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142
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Yang YH, Wang JS, Yuan SS, Liu ML, Su W, Lin H, Zhang ZY. A Survey for Predicting ATP Binding Residues of Proteins Using Machine Learning Methods. Curr Med Chem 2021; 29:789-806. [PMID: 34514982 DOI: 10.2174/0929867328666210910125802] [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: 03/24/2021] [Revised: 06/29/2021] [Accepted: 07/04/2021] [Indexed: 11/22/2022]
Abstract
Protein-ligand interactions are necessary for majority protein functions. Adenosine-5'-triphosphate (ATP) is one such ligand that plays vital role as a coenzyme in providing energy for cellular activities, catalyzing biological reaction and signaling. Knowing ATP binding residues of proteins is helpful for annotation of protein function and drug design. However, due to the huge amounts of protein sequences influx into databases in the post-genome era, experimentally identifying ATP binding residues is cost-ineffective and time-consuming. To address this problem, computational methods have been developed to predict ATP binding residues. In this review, we briefly summarized the application of machine learning methods in detecting ATP binding residues of proteins. We expect this review will be helpful for further research.
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Affiliation(s)
- Yu-He Yang
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
| | - Jia-Shu Wang
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
| | - Shi-Shi Yuan
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
| | - Meng-Lu Liu
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
| | - Wei Su
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
| | - Hao Lin
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
| | - Zhao-Yue Zhang
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054. China
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143
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Soltan MA, Eldeen MA, Elbassiouny N, Mohamed I, El-damasy DA, Fayad E, Abu Ali OA, Raafat N, Eid RA, Al-Karmalawy AA. Proteome Based Approach Defines Candidates for Designing a Multitope Vaccine against the Nipah Virus. Int J Mol Sci 2021; 22:ijms22179330. [PMID: 34502239 PMCID: PMC8431361 DOI: 10.3390/ijms22179330] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 08/24/2021] [Accepted: 08/26/2021] [Indexed: 02/05/2023] Open
Abstract
Nipah virus is one of the most harmful emerging viruses with deadly effects on both humans and animals. Because of the severe outbreaks, in 2018, the World Health Organization focused on the urgent need for the development of effective solutions against the virus. However, up to date, there is no effective vaccine against the Nipah virus in the market. In the current study, the complete proteome of the Nipah virus (nine proteins) was analyzed for the antigenicity score and the virulence role of each protein, where we came up with fusion glycoprotein (F), glycoprotein (G), protein (V), and protein (W) as the candidates for epitope prediction. Following that, the multitope vaccine was designed based on top-ranking CTL, HTL, and BCL epitopes from the selected proteins. We used suitable linkers, adjuvant, and PADRE peptides to finalize the constructed vaccine, which was analyzed for its physicochemical features, antigenicity, toxicity, allergenicity, and solubility. The designed vaccine passed these assessments through computational analysis and, as a final step, we ran a docking analysis between the designed vaccine and TLR-3 and validated the docked complex through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for Nipah virus. Here, we describe the computational approach for design and analysis of this vaccine.
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Affiliation(s)
- Mohamed A. Soltan
- Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai University, Ismailia 41611, Egypt;
| | - Muhammad Alaa Eldeen
- Cell Biology, Histology & Genetics Division, Zoology Department, Faculty of Science, Zagazig University, Zagazig 44519, Egypt;
| | - Nada Elbassiouny
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Sinai University, Ismailia 41611, Egypt;
| | - Ibrahim Mohamed
- Department of Microbiology and Immunology, Faculty of Pharmacy, Suez Canal University, Ismailia 41522, Egypt;
| | - Dalia A. El-damasy
- Department of Microbiology and Immunology, Faculty of Pharmacy, Egyptian Russian University, Cairo 11829, Egypt;
| | - Eman Fayad
- Department of Biotechnology, Faculty of Sciences, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | - Ola A. Abu Ali
- Department of Chemistry, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | - Nermin Raafat
- Department of Medical Biochemistry, Faculty of Medicine, Zagazig University, Zagazig 44519, Egypt;
| | - Refaat A. Eid
- Department of Pathology, College of Medicine, King Khalid University, Abha 12573, Saudi Arabia;
| | - Ahmed A. Al-Karmalawy
- Department of Pharmaceutical Medicinal Chemistry, Faculty of Pharmacy, Horus University-Egypt, New Damietta 34518, Egypt
- Correspondence: ; Tel.: +20-109-214-7330
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144
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Noori Goodarzi N, Bolourchi N, Fereshteh S, Badmasti F. Introduction of novel putative immunogenic targets against Proteus mirabilis using a reverse vaccinology approach. INFECTION GENETICS AND EVOLUTION 2021; 95:105045. [PMID: 34428568 DOI: 10.1016/j.meegid.2021.105045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/04/2021] [Accepted: 08/18/2021] [Indexed: 11/15/2022]
Abstract
Multi-drug resistance of Proteus mirabilis, a frequent cause of catheter-associated urinary tract infections, renders ineffective treatment. Therefore, new advanced strategies are needed to overcome it. In the meantime, vaccination may be the most effective and promising method. In this study antigenicity, allergenicity, subcellular localization, human homology, B-cell epitopes and MHC-II binding sites, conserved domains and protein-protein interactions were predicted using different reverse vaccinology methods and bioinformatics databases to find new putative immunogenic targets against P. mirabilis. Finally, 5 putative immunogenic targets against P. mirabilis were identified. Considering all criteria, QKQ94350.1 (Cell envelope opacity-associated protein A), QKQ94681.1 (Porin), QKQ95001.1 (TonB-dependent hemoglobin/ transferrin/ lactoferrin family receptor), QKQ95221.1 (AsmA) and QKQ94335.1 (N-acetylmuramoyl-L-alanine amidase) are excellent putative immunogenic targets. Finally, a multi-epitope vaccine was designed using the conserved linear epitopes of two OMPs (QKQ94681.1 and QKQ95001.1) and N-acetylmuramoyl-L-alanine amidase (QKQ94335.1), which have promising properties for immunization. These findings can simplify the development of efficient vaccines against P. mirabilis.
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Affiliation(s)
- Narjes Noori Goodarzi
- Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Negin Bolourchi
- Department of Bacteriology, Pasteur Institute of Iran, Tehran, Iran
| | | | - Farzad Badmasti
- Department of Bacteriology, Pasteur Institute of Iran, Tehran, Iran; Microbiology Research Center (MRC), Pasteur Institute of Iran, Tehran, Iran.
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145
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Saba AA, Adiba M, Saha P, Hosen MI, Chakraborty S, Nabi AHMN. An in-depth in silico and immunoinformatics approach for designing a potential multi-epitope construct for the effective development of vaccine to combat against SARS-CoV-2 encompassing variants of concern and interest. Comput Biol Med 2021; 136:104703. [PMID: 34352457 PMCID: PMC8321692 DOI: 10.1016/j.compbiomed.2021.104703] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 07/25/2021] [Accepted: 07/26/2021] [Indexed: 11/03/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the latest of the several viral pathogens that have acted as a threat to human health around the world. Thus, to prevent COVID-19 and control the outbreak, the development of vaccines against SARS-CoV-2 is one of the most important strategies at present. The study aimed to design a multi-epitope vaccine (MEV) against SARS-CoV-2. For the development of a more effective vaccine, 1549 nucleotide sequences were taken into consideration, including the variants of concern (B.1.1.7, B.1.351, P.1 and, B.1.617.2) and variants of interest (B.1.427, B.1.429, B.1.526, B.1.617.1 and P.2). A total of 11 SARS-CoV-2 proteins (S, N, E, M, ORF1ab polyprotein, ORF3a, ORF6, ORF7a, ORF7b, ORF8, ORF10) were targeted for T-cell epitope prediction and S protein was targeted for B-cell epitope prediction. MEV was constructed using linkers and adjuvant beta-defensin. The vaccine construct was verified, based on its antigenicity, physicochemical properties, and its binding potential, with toll-like receptors (TLR2, TLR4), ACE2 receptor and B cell receptor. The selected vaccine construct showed considerable binding with all the receptors and a significant immune response, including elevated antibody titer and B cell population along with augmented activity of TH cells, Tc cells and NK cells. Thus, immunoinformatics and in silico-based approaches were used for constructing MEV which is capable of eliciting both innate and adaptive immunity. In conclusion, the vaccine construct developed in this study has all the potential for the development of a next-generation vaccine which may in turn effectively combat the new variants of SARS-CoV-2 identified so far. However, in vitro and animal studies are warranted to justify our findings for its utility as probable preventive measure.
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Affiliation(s)
- Abdullah Al Saba
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh
| | - Maisha Adiba
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh
| | - Piyal Saha
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh
| | - Md Ismail Hosen
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh
| | - Sajib Chakraborty
- Molecular Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh
| | - A H M Nurun Nabi
- Laboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
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146
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Ismail S, Shahid F, Khan A, Bhatti S, Ahmad S, Naz A, Almatroudi A, Tahir Ul Qamar M. Pan-vaccinomics approach towards a universal vaccine candidate against WHO priority pathogens to address growing global antibiotic resistance. Comput Biol Med 2021; 136:104705. [PMID: 34340127 DOI: 10.1016/j.compbiomed.2021.104705] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 07/06/2021] [Accepted: 07/23/2021] [Indexed: 01/29/2023]
Abstract
Antimicrobial resistance (AMR) in bacterial pathogens is a major global distress. Due to the slow progress of antibiotics development and the fast pace of resistance acquisition, there is an urgent need for effective vaccines against such bacterial pathogens. In-silico approaches including pan-genomics, subtractive proteomics, reverse vaccinology, immunoinformatics, molecular docking, and dynamics simulation studies were applied in the current study to identify a universal potential vaccine candidate against the 18 multi-drug resistance (MDRs) bacterial pathogenic species from a WHO priority list. Ten non-redundant, non-homologous, virulent, and antigenic vaccine candidates were filtered against all targeted species. Nine B-cell-derived T-cell antigen epitopes which show a great affinity to the dominant HLA allele (DRB1*0101) in the human population were screened from selected vaccine candidates using immunoinformatics approaches. Screened epitopes were then used to design a multi-epitope peptide vaccine construct (MEPVC) along with β-defensin adjuvant to improve the immunogenic properties of the proposed vaccine construct. Molecular docking and MD simulation were carried out to study the binding affinity and molecular interaction of MEPVC with human immune receptors (TLR2, TLR3, TLR4, and TLR6). The final MEPVC construct was reverse translated and in-silico cloned in the pET28a(+) vector to ensure its effectiveness. This in silico construct is expected to be helpful for vaccinologists to assess its immune protection effectiveness in vivo and in vitro to counter rising antibiotic resistance worldwide.
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Affiliation(s)
- Saba Ismail
- NUMS Department of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan
| | - Farah Shahid
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan
| | - Abbas Khan
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China
| | - Sadia Bhatti
- Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan.
| | - Anam Naz
- Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore, Lahore, Pakistan
| | - Ahmad Almatroudi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia
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147
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Gautam V, Nimmanpipug P, Zain SM, Rahman NA, Lee VS. Molecular Dynamics Simulations in Designing DARPins as Phosphorylation-Specific Protein Binders of ERK2. Molecules 2021; 26:molecules26154540. [PMID: 34361694 PMCID: PMC8347146 DOI: 10.3390/molecules26154540] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 07/20/2021] [Accepted: 07/23/2021] [Indexed: 11/16/2022] Open
Abstract
Extracellular signal-regulated kinases 1 and 2 (ERK1/2) play key roles in promoting cell survival and proliferation through the phosphorylation of various substrates. Remarkable antitumour activity is found in many inhibitors that act upstream of the ERK pathway. However, drug-resistant tumour cells invariably emerge after their use due to the reactivation of ERK1/2 signalling. ERK1/2 inhibitors have shown clinical efficacy as a therapeutic strategy for the treatment of tumours with mitogen-activated protein kinase (MAPK) upstream target mutations. These inhibitors may be used as a possible strategy to overcome acquired resistance to MAPK inhibitors. Here, we report a class of repeat proteins-designed ankyrin repeat protein (DARPin) macromolecules targeting ERK2 as inhibitors. The structural basis of ERK2-DARPin interactions based on molecular dynamics (MD) simulations was studied. The information was then used to predict stabilizing mutations employing a web-based algorithm, MAESTRO. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations. Two mutations, Ala → Asp and Ser → Leu, were found to perform better than the original sequence (DARPin E40) based on the associated energy and key residues involved in protein-protein interaction. MD simulations and analysis of the data obtained on these mutations supported our predictions.
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Affiliation(s)
- Vertika Gautam
- Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia; (V.G.); (S.M.Z.); (N.A.R.)
| | - Piyarat Nimmanpipug
- Department of Chemistry, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand;
- Center of Excellence for Innovation in Analytical Science and Technology (I-ANALY-S-T), Chiang Mai University, Chiang Mai 50200, Thailand
| | - Sharifuddin Md Zain
- Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia; (V.G.); (S.M.Z.); (N.A.R.)
| | - Noorsaadah Abd Rahman
- Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia; (V.G.); (S.M.Z.); (N.A.R.)
| | - Vannajan Sanghiran Lee
- Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia; (V.G.); (S.M.Z.); (N.A.R.)
- Center of Excellence for Innovation in Analytical Science and Technology (I-ANALY-S-T), Chiang Mai University, Chiang Mai 50200, Thailand
- Correspondence:
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148
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Solanki V, Tiwari M, Tiwari V. Subtractive proteomic analysis of antigenic extracellular proteins and design a multi-epitope vaccine against Staphylococcus aureus. Microbiol Immunol 2021; 65:302-316. [PMID: 33368661 DOI: 10.1111/1348-0421.12870] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 12/08/2020] [Accepted: 12/21/2020] [Indexed: 01/04/2023]
Abstract
Staphylococcus aureus is a versatile Gram's positive bacterium that can reside as an asymptomatic colonizer, which can cause a wide range of skin, soft-tissue, and nosocomial infections. A vaccine against multi-drug resistant S. aureus, therefore, is urgently needed. Subtractive proteomics and reverse vaccinology are newly emerging techniques to design multiepitope-based vaccines. The analysis of 7290 proteomes (sensitive and resistant strains), five potent nonhuman homologous vaccine targets [(UNIPORT ID Q2FZL3 (Staphopain B), Q2G2R8 (Staphopain A), Q2FWP0 (uncharacterized leukocidin-like protein 1), Q2G1S6 (uncharacterized protein), and Q2FWV3 (Staphylokinase, putative)] were selected. These proteins were absent in the gut microbiome, which further enhances the significance of these proteins in vaccine design. These five virulence-associated proteins mainly have a role in the invasion mechanism in the host phagocyte cells. MHC I, MHC II, and B cell epitopes were identified in these five proteins. Finalized epitopes were examined by different online servers to screen suitable epitopes for multi-epitope based vaccine design. Shortlisted antigenic and nonallergenic associated epitopes were joined with linkers to design 30 variants (VSA1-VSA30) of multi-epitope vaccine conjugates. The antigenicity and allergenicity of all the 30 vaccine constructs were identified, and VSA30 was found to have the highest antigenicity and lowest allergenicity, and hence was selected for further study. Accordingly, VSA30 was docked with different HLA allelic variants, and the best-docked complex (VSA30-1SYS) was further analyzed by molecular dynamics simulation (MDS). The MDS result confirms the interaction of VSA30 with MHC (HLA-allelic variant). Thus, the final vaccine construct was in silico cloned in the pET28a vector for suitable expression in a heterologous system. Therefore, the designed vaccine construct VSA-30 can be developed as an appropriate vaccine to target S. aureus infection. VSA-30 still needs experimental validation to assure the antigenic and immunogenic properties.
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Affiliation(s)
- Vandana Solanki
- Department of Biochemistry, Central University of Rajasthan, Ajmer, India
| | - Monalisa Tiwari
- Department of Biochemistry, Central University of Rajasthan, Ajmer, India
| | - Vishvanath Tiwari
- Department of Biochemistry, Central University of Rajasthan, Ajmer, India
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149
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Fostering "Education": Do Extracellular Vesicles Exploit Their Own Delivery Code? Cells 2021; 10:cells10071741. [PMID: 34359911 PMCID: PMC8305232 DOI: 10.3390/cells10071741] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 12/15/2022] Open
Abstract
Extracellular vesicles (EVs), comprising large microvesicles (MVs) and exosomes (EXs), play a key role in intercellular communication, both in physiological and in a wide variety of pathological conditions. However, the education of EV target cells has so far mainly been investigated as a function of EX cargo, while few studies have focused on the characterization of EV surface membrane molecules and the mechanisms that mediate the addressability of specific EVs to different cell types and tissues. Identifying these mechanisms will help fulfill the diagnostic, prognostic, and therapeutic promises fueled by our growing knowledge of EVs. In this review, we first discuss published studies on the presumed EV “delivery code” and on the combinations of the hypothesized EV surface membrane “sender” and “recipient” molecules that may mediate EV targeting in intercellular communication. Then we briefly review the main experimental approaches and techniques, and the bioinformatic tools that can be used to identify and characterize the structure and functional role of EV surface membrane molecules. In the final part, we present innovative techniques and directions for future research that would improve and deepen our understandings of EV-cell targeting.
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150
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Kagami LP, Orlando G, Raimondi D, Ancien F, Dixit B, Gavaldá-García J, Ramasamy P, Roca-Martínez J, Tzavella K, Vranken W. b2bTools: online predictions for protein biophysical features and their conservation. Nucleic Acids Res 2021; 49:W52-W59. [PMID: 34057475 PMCID: PMC8262692 DOI: 10.1093/nar/gkab425] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/21/2021] [Accepted: 05/05/2021] [Indexed: 11/13/2022] Open
Abstract
We provide integrated protein sequence-based predictions via https://bio2byte.be/b2btools/. The aim of our predictions is to identify the biophysical behaviour or features of proteins that are not readily captured by structural biology and/or molecular dynamics approaches. Upload of a FASTA file or text input of a sequence provides integrated predictions from DynaMine backbone and side-chain dynamics, conformational propensities, and derived EFoldMine early folding, DisoMine disorder, and Agmata β-sheet aggregation. These predictions, several of which were previously not available online, capture 'emergent' properties of proteins, i.e. the inherent biophysical propensities encoded in their sequence, rather than context-dependent behaviour (e.g. final folded state). In addition, upload of a multiple sequence alignment (MSA) in a variety of formats enables exploration of the biophysical variation observed in homologous proteins. The associated plots indicate the biophysical limits of functionally relevant protein behaviour, with unusual residues flagged by a Gaussian mixture model analysis. The prediction results are available as JSON or CSV files and directly accessible via an API. Online visualisation is available as interactive plots, with brief explanations and tutorial pages included. The server and API employ an email-free token-based system that can be used to anonymously access previously generated results.
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Affiliation(s)
- Luciano Porto Kagami
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
| | - Gabriele Orlando
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
| | - Daniele Raimondi
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
| | - Francois Ancien
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- 3Bio, Université Libre de Bruxelles, Brussels 1050, Belgium
| | - Bhawna Dixit
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels 1050, Belgium
- VIB Structural Biology Research Centre, Brussels, 1050, Belgium
| | - Jose Gavaldá-García
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels 1050, Belgium
- VIB Structural Biology Research Centre, Brussels, 1050, Belgium
| | - Pathmanaban Ramasamy
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- VIB Structural Biology Research Centre, Brussels, 1050, Belgium
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9000, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent, 9000, Belgium
| | - Joel Roca-Martínez
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels 1050, Belgium
- VIB Structural Biology Research Centre, Brussels, 1050, Belgium
| | - Konstantina Tzavella
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels 1050, Belgium
- VIB Structural Biology Research Centre, Brussels, 1050, Belgium
| | - Wim Vranken
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels 1050, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels 1050, Belgium
- VIB Structural Biology Research Centre, Brussels, 1050, Belgium
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