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In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pyogenes

Author

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  • Abdur Rehman

    (Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan
    These authors contributed equally to this study.)

  • Xiukang Wang

    (College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
    These authors contributed equally to this study.)

  • Sajjad Ahmad

    (Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan
    These authors contributed equally to this study.)

  • Farah Shahid

    (Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan)

  • Sidra Aslam

    (Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan)

  • Usman Ali Ashfaq

    (Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan)

  • Faris Alrumaihi

    (Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia)

  • Muhammad Qasim

    (Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan)

  • Abeer Hashem

    (Botany and Microbiology Department, College of Science, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

  • Amal A. Al-Hazzani

    (Botany and Microbiology Department, College of Science, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

  • Elsayed Fathi Abd_Allah

    (Plant Production Department, College Food and Agricultural Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

Abstract

Streptococcus pyogenes is a significant pathogen that causes skin and upper respiratory tract infections and non-suppurative complications, such as acute rheumatic fever and post-strep glomerulonephritis. Multidrug resistance has emerged in S. pyogenes strains, making them more dangerous and pathogenic. Hence, it is necessary to identify and develop therapeutic methods that would present novel approaches to S. pyogenes infections. In the current study, a subtractive proteomics approach was employed to core proteomes of four strains of S. pyogenes using several bioinformatic software tools and servers. The core proteome consists of 1324 proteins, and 302 essential proteins were predicted from them. These essential proteins were analyzed using BLASTp against human proteome, and the number of potential targets was reduced to 145. Based on subcellular localization prediction, 46 proteins with cytoplasmic localization were chosen for metabolic pathway analysis. Only two cytoplasmic proteins, i.e., chromosomal replication initiator protein DnaA and two-component response regulator (TCR), were discovered to have the potential to be novel drug target candidates. Three-dimensional (3D) structure prediction of target proteins was carried out via the Swiss Model server. Molecular docking approach was employed to screen the library of 1000 phytochemicals against the interacting residues of the target proteins through the MOE software. Further, the docking studies were validated by running molecular dynamics simulation and highly popular binding free energy approaches of MM-GBSA and MM-PBSA. The findings revealed a promising candidate as a novel target against S. pyogenes infections.

Suggested Citation

  • Abdur Rehman & Xiukang Wang & Sajjad Ahmad & Farah Shahid & Sidra Aslam & Usman Ali Ashfaq & Faris Alrumaihi & Muhammad Qasim & Abeer Hashem & Amal A. Al-Hazzani & Elsayed Fathi Abd_Allah, 2021. "In Silico Core Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pyogenes," IJERPH, MDPI, vol. 18(21), pages 1-19, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:21:p:11355-:d:667370
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    References listed on IDEAS

    as
    1. Farah Shahid & Usman Ali Ashfaq & Sania Saeed & Samman Munir & Ahmad Almatroudi & Mohsin Khurshid, 2020. "In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in Staphylococcus saprophyticus," IJERPH, MDPI, vol. 17(10), pages 1-10, May.
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    Cited by:

    1. Mohammed S. Almuhayawi & Soad K. Al Jaouni & Samy Selim & Dalal Hussien M. Alkhalifah & Romina Alina Marc & Sidra Aslam & Peter Poczai, 2022. "Integrated Pangenome Analysis and Pharmacophore Modeling Revealed Potential Novel Inhibitors against Enterobacter xiangfangensis," IJERPH, MDPI, vol. 19(22), pages 1-17, November.

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