IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i10p3644-d361564.html
   My bibliography  Save this article

In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in Staphylococcus saprophyticus

Author

Listed:
  • Farah Shahid

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

  • Usman Ali Ashfaq

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

  • Sania Saeed

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

  • Samman Munir

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

  • Ahmad Almatroudi

    (Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 52571, Saudi Arabia)

  • Mohsin Khurshid

    (Department of Microbiology, Government College University, Faisalabad, Punjab 38000, Pakistan)

Abstract

Staphylococcus saprophyticus is a uropathogenic bacteria responsible for acute urinary tract infections (UTIs) mainly in young female patients. Patients suffering from urinary catheterization, pregnant patients, the elderly as well as those with nosocomial UTIs are at greater risk of the colonizing S. saprophyticus infection. The causative factors include benign prostatic hyperplasia, indwelling catheter, neurogenic bladder, pregnancy, and history of frequent UTIs. Recent findings have exhibited that S. saprophyticus is resistant to several antimicrobial agents. Moreover, there is a global concern regarding the increasing level of antimicrobial resistance, which leads to treatment failure and reduced effectiveness of broad-spectrum antimicrobials. Therefore, a novel approach is being utilized to combat resistant microbes since the past few years. Subtractive proteome analysis has been performed with the entire proteome of S. saprophyticus strain American Type Culture Collection (ATCC) 15305 using several bioinformatics servers and software. The proteins that were non-homologous to humans and bacteria were identified for metabolic pathway analysis. Only four cytoplasmic proteins were found possessing the potential of novel drug target candidates. The development of innovative therapeutic agents by targeting the inhibition of any essential proteins may disrupt the metabolic pathways specific to the pathogen, thus causing destruction as well as eradication of the pathogen from a particular host. The identified targets can facilitate in designing novel and potent drugs against S. saprophyticus strain ATCC 15305.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3644-:d:361564
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/10/3644/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/10/3644/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Roqayah H. Kadi & Khadijah A. Altammar & Mohamed M. Hassan & Abdullah F. Shater & Fayez M. Saleh & Hattan Gattan & Bassam M. Al-ahmadi & Qwait AlGabbani & Zuhair M. Mohammedsaleh, 2022. "Potential Therapeutic Candidates against Chlamydia pneumonia Discovered and Developed In Silico Using Core Proteomics and Molecular Docking and Simulation-Based Approaches," IJERPH, MDPI, vol. 19(12), pages 1-18, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3644-:d:361564. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.