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      Towards a novel peptide vaccine for Middle East respiratory syndrome coronavirus and its possible use against pandemic COVID-19

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          Abstract

          Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging health concern due to its high mortality rate of 35%. At present, no vaccine is available to protect against MERS-CoV infections. Therefore, an in silico search for potential antigenic epitopes in the non-redundant proteome of MERS-CoV was performed herein. First, a subtractive proteome-based approach was employed to look for the surface exposed and host non-homologous proteins. Following, immunoinformatics analysis was performed to predict antigenic B and T cell epitopes that were used in the design of a multi-epitopes peptide. Molecular docking study was carried out to predict vaccine construct affinity of binding to Toll-like receptor 3 (TLR3) and understand its binding conformation to extract ideas about its processing by the host immune system. We identified membrane protein, envelope small membrane protein, non-structural protein ORF3, non-structural protein ORF5, and spike glycoprotein as potential candidates for subunit vaccine designing. The designed multi-epitope peptide then linked to β-defensin adjuvant is showing high antigenicity. Further, the sequence of the designed vaccine construct is optimized for maximum expression in the Escherichia coli expression system. A rich pattern of hydrogen and hydrophobic interactions of the construct was observed with the TLR3 allowing stable binding of the construct at the docked site as predicted by the molecular dynamics simulation and MM-PBSA binding energies. We expect that the panel of subunit vaccine candidates and the designed vaccine construct could be highly effective in immunizing populations from infections caused by MERS-CoV and could possible applied on the current pandemic COVID-19.

          Highlights

          • In silico peptide based multi-epitopes vaccine design for MERS-CoV.

          • Designed vaccine is composed of B, T cell epitopes and adjuvant.

          • Vaccine is antigenic, non-allergic and has favorable physicochemical properties.

          • Dynamically, the vaccine binding mode and interactions are stable to TLR3 receptor.

          • Vaccine revealed robust electrostatic energies in complex with TLR3.

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          Most cited references78

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          CD-HIT: accelerated for clustering the next-generation sequencing data

          Summary: CD-HIT is a widely used program for clustering biological sequences to reduce sequence redundancy and improve the performance of other sequence analyses. In response to the rapid increase in the amount of sequencing data produced by the next-generation sequencing technologies, we have developed a new CD-HIT program accelerated with a novel parallelization strategy and some other techniques to allow efficient clustering of such datasets. Our tests demonstrated very good speedup derived from the parallelization for up to ∼24 cores and a quasi-linear speedup for up to ∼8 cores. The enhanced CD-HIT is capable of handling very large datasets in much shorter time than previous versions. Availability: http://cd-hit.org. Contact: liwz@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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            PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data.

            We describe PTRAJ and its successor CPPTRAJ, two complementary, portable, and freely available computer programs for the analysis and processing of time series of three-dimensional atomic positions (i.e., coordinate trajectories) and the data therein derived. Common tools include the ability to manipulate the data to convert among trajectory formats, process groups of trajectories generated with ensemble methods (e.g., replica exchange molecular dynamics), image with periodic boundary conditions, create average structures, strip subsets of the system, and perform calculations such as RMS fitting, measuring distances, B-factors, radii of gyration, radial distribution functions, and time correlations, among other actions and analyses. Both the PTRAJ and CPPTRAJ programs and source code are freely available under the GNU General Public License version 3 and are currently distributed within the AmberTools 12 suite of support programs that make up part of the Amber package of computer programs (see http://ambermd.org ). This overview describes the general design, features, and history of these two programs, as well as algorithmic improvements and new features available in CPPTRAJ.
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              MMPBSA.py: An Efficient Program for End-State Free Energy Calculations.

              MM-PBSA is a post-processing end-state method to calculate free energies of molecules in solution. MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson-Boltzmann Model, the Generalized Born Model, and the Reference Interaction Site Model. Vibrational frequencies may be calculated using normal mode or quasi-harmonic analysis to approximate the solute entropy. Specific interactions can also be dissected using free energy decomposition or alanine scanning. A parallel implementation significantly speeds up the calculation by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calculations. The source code can be downloaded at http://ambermd.org/ with AmberTools, released under the GNU General Public License.
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                Author and article information

                Journal
                J Mol Liq
                J Mol Liq
                Journal of Molecular Liquids
                Elsevier B.V.
                0167-7322
                1873-3166
                6 November 2020
                6 November 2020
                : 114706
                Affiliations
                [a ]School of Life Sciences, Lanzhou University, Lanzhou, Gansu 73000, PR China
                [b ]School of Integrative Engineering, Chung ANG University, Seoul, South Korea
                [c ]National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan
                [d ]Department of Biological Sciences, National University of Medical Sciences, the Mall, Rawalpindi 46000, Pakistan
                [e ]Department of Microbiology, Quaid-i-Azam University, Islamabad, Pakistan
                Author notes
                [* ]Corresponding authors.
                [1]

                These authors contributed equally to this work.

                Article
                S0167-7322(20)36948-8 114706
                10.1016/j.molliq.2020.114706
                7644433
                33173250
                8ce6601b-8a85-4c1b-b02e-8fdd888df762
                © 2020 Elsevier B.V. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 12 July 2020
                : 5 September 2020
                : 2 November 2020
                Categories
                Article

                middle east respiratory syndrome coronavirus,middle east respiratory syndrome,multi-epitope peptide,toll-like receptor 3

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