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A Concise Review on the Significance of QSAR in Drug Design

Received: 2 December 2019     Accepted: 16 December 2019     Published: 27 December 2019
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Abstract

Drug designing is a crucial step in the exploration of novel drugs which requires potent methodologies. One of such methodologies is Quantitative Structure Activity Relationship (QSAR) which is a widely used statistical tool that correlates the structure of a molecule to a biological activity as a function of molecular descriptors, thereby, playing an essential role in the drug designing. QSAR utilizes Density Functional Theory (DFT) based chemical descriptors for this purpose. The selection of such significant molecular descriptors from various available descriptors is the foremost challenge in a QSAR as structural descriptors are representative of the molecular characteristics accountable for the relevant activity. Recently, new QSAR approaches have been introduced which further enhance the study of the activities. Further, the constructed QSAR models also need to be tested and validated for their efficiency and practical usage. As the QSAR models are structure specific, they may not be universally applicable. However, because of their high precision and efficacy, they have a promising future in the world of drug design. This review briefly summarizes the role of descriptor based QSAR in drug design in conjunction with existing QSAR approaches and also the utility as well as constraints of this approach in drug design.

Published in Chemical and Biomolecular Engineering (Volume 4, Issue 4)
DOI 10.11648/j.cbe.20190404.11
Page(s) 45-51
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

QSAR, Density Functional Theory (DFT), Quantum Chemical Descriptors, Drug Design

References
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  • APA Style

    Hiteshi Tandon, Tanmoy Chakraborty, Vandana Suhag. (2019). A Concise Review on the Significance of QSAR in Drug Design. Chemical and Biomolecular Engineering, 4(4), 45-51. https://doi.org/10.11648/j.cbe.20190404.11

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    Hiteshi Tandon; Tanmoy Chakraborty; Vandana Suhag. A Concise Review on the Significance of QSAR in Drug Design. Chem. Biomol. Eng. 2019, 4(4), 45-51. doi: 10.11648/j.cbe.20190404.11

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    AMA Style

    Hiteshi Tandon, Tanmoy Chakraborty, Vandana Suhag. A Concise Review on the Significance of QSAR in Drug Design. Chem Biomol Eng. 2019;4(4):45-51. doi: 10.11648/j.cbe.20190404.11

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  • @article{10.11648/j.cbe.20190404.11,
      author = {Hiteshi Tandon and Tanmoy Chakraborty and Vandana Suhag},
      title = {A Concise Review on the Significance of QSAR in Drug Design},
      journal = {Chemical and Biomolecular Engineering},
      volume = {4},
      number = {4},
      pages = {45-51},
      doi = {10.11648/j.cbe.20190404.11},
      url = {https://doi.org/10.11648/j.cbe.20190404.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbe.20190404.11},
      abstract = {Drug designing is a crucial step in the exploration of novel drugs which requires potent methodologies. One of such methodologies is Quantitative Structure Activity Relationship (QSAR) which is a widely used statistical tool that correlates the structure of a molecule to a biological activity as a function of molecular descriptors, thereby, playing an essential role in the drug designing. QSAR utilizes Density Functional Theory (DFT) based chemical descriptors for this purpose. The selection of such significant molecular descriptors from various available descriptors is the foremost challenge in a QSAR as structural descriptors are representative of the molecular characteristics accountable for the relevant activity. Recently, new QSAR approaches have been introduced which further enhance the study of the activities. Further, the constructed QSAR models also need to be tested and validated for their efficiency and practical usage. As the QSAR models are structure specific, they may not be universally applicable. However, because of their high precision and efficacy, they have a promising future in the world of drug design. This review briefly summarizes the role of descriptor based QSAR in drug design in conjunction with existing QSAR approaches and also the utility as well as constraints of this approach in drug design.},
     year = {2019}
    }
    

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    AU  - Hiteshi Tandon
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    AU  - Vandana Suhag
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    DO  - 10.11648/j.cbe.20190404.11
    T2  - Chemical and Biomolecular Engineering
    JF  - Chemical and Biomolecular Engineering
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    AB  - Drug designing is a crucial step in the exploration of novel drugs which requires potent methodologies. One of such methodologies is Quantitative Structure Activity Relationship (QSAR) which is a widely used statistical tool that correlates the structure of a molecule to a biological activity as a function of molecular descriptors, thereby, playing an essential role in the drug designing. QSAR utilizes Density Functional Theory (DFT) based chemical descriptors for this purpose. The selection of such significant molecular descriptors from various available descriptors is the foremost challenge in a QSAR as structural descriptors are representative of the molecular characteristics accountable for the relevant activity. Recently, new QSAR approaches have been introduced which further enhance the study of the activities. Further, the constructed QSAR models also need to be tested and validated for their efficiency and practical usage. As the QSAR models are structure specific, they may not be universally applicable. However, because of their high precision and efficacy, they have a promising future in the world of drug design. This review briefly summarizes the role of descriptor based QSAR in drug design in conjunction with existing QSAR approaches and also the utility as well as constraints of this approach in drug design.
    VL  - 4
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Author Information
  • Department of Chemistry, Manipal University Jaipur, Jaipur, India

  • Department of Chemistry, School of Engineering, Presidency University, Bengaluru, India

  • Department of Applied Sciences, BML Munjal University, Gurgaon, India

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