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<records>

  <record>
    <language>eng</language>
          <publisher>Oriental Scientific Publishing Company</publisher>
        <journalTitle>Biosciences Biotechnology Research Asia</journalTitle>
          <issn>0973-1245</issn>
            <publicationDate>2015-12-25</publicationDate>
    
        <volume>12</volume>
        <issue>3</issue>

 
    <startPage>2173</startPage>
    <endPage>2186</endPage>

	 
      <doi>10.13005/bbra/1889</doi>
        <publisherRecordId>2454</publisherRecordId>
    <documentType>article</documentType>
    <title language="eng">In-Silico Prediction of Riboswitches and Design of their Potent Inhibitors for H1N1, H2N2 and H3N2 Strains of Influenza Virus</title>

    <authors>
	 


      <author>
       <name>Priya Pradhan</name>

 
		
	<affiliationId>1</affiliationId>
      </author>
    

	 


      <author>
       <name>Nishant K. Soni</name>


		
	<affiliationId>1</affiliationId>

      </author>
    

	 


      <author>
       <name>Lalitesh Chaudhary</name>

		
	<affiliationId>1</affiliationId>
      </author>
    

	 


      <author>
       <name>Somdutt Mujwar</name>

		
	<affiliationId>1</affiliationId>
      </author>
    


	 


      <author>
       <name>K. R. Pardasani</name>

		
	<affiliationId>1</affiliationId>
      </author>
    


	
    </authors>
    
	    <affiliationsList>
	    
		
		<affiliationName affiliationId="1">Department of Bioinformatics, Maulana Azad National Institute of Technology Bhopal 462 051 (INDIA)</affiliationName>
    

		
		
		
		
		
	  </affiliationsList>






    <abstract language="eng">Almost every age group is at higher risk for serious flu complications. The major problem arising these days regarding the control of influenza disease is the development of resistance among the influenza viruses against the existing anti-viral drugs that are being recommended. Also, these antiviral drugs have a number of side effects. The main objective of the present paper is to explore riboswitches as a novel target for design of drugs for influenza virus in order to address the issues of resistance and side effects of present drugs.

Riboswitches are present in the non-coding region of mRNA that sense changes in the cellular environment and directly mediate appropriate gene control responses. These riboswitches are primarily found in the 5’ untranslated regions of messenger RNAs. In the present paper <em>in-silico</em> approach is proposed for the prediction of riboswitches for the strains of influenza virus, their binding sites and design of their inhibitors. Two riboswitches have been predicted for the three strains of influenza virus and five inhibitors have been identified for each of the two riboswitches by virtual screening. These inhibitors are found to be free from the side effects of antiviral agents and have remote chances of being resistant.</abstract>

    <fullTextUrl format="html">https://www.biotech-asia.org/vol12no3/in-silico-prediction-of-riboswitches-and-design-of-their-potent-inhibitors-for-h1n1-h2n2-and-h3n2-strains-of-influenza-virus/</fullTextUrl>



      <keywords language="eng">
        <keyword>Riboswitches; Influenza; Inhibitors; Auto dock; Drug; Virtual Screening</keyword>
      </keywords>

  </record>
</records>