Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review

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Year : July 19, 2024 at 11:05 am | [if 1553 equals=””] Volume :15 [else] Volume :15[/if 1553] | [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] : 02 | Page : 56-63

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Satish kumar Yadav, Manyta Yadav, Mohd. Wasiullah, Piyush Yadav, Priyanshu Upadhyay,

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  1. Associate Professor, Professor, Principal, Academic Head, Research Scholar Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Department of Pharmacy, Prasad Institute of Technology, Jaunpur Uttar Pradesh, Uttar Pradesh, Uttar Pradesh, Uttar Pradesh, Uttar Pradesh India, India, India, India, India
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Abstract

nQuantitative Structure-Activity Relationship (QSAR) stands at the forefront of Computer-Aided Drug Design (CADD), providing a systematic framework for understanding the relationship between the chemical structure of molecules and their biological activity. This review delves into the multifaceted realm of QSAR methodologies within the landscape of drug discovery. Through an exploration of diverse QSAR models, molecular descriptors, validation techniques, and recent advancements, this article aims to elucidate the pivotal role of QSAR in accelerating the development of novel therapeutics. By dissecting the intricacies of QSAR analysis and its application in rational drug design, this review sheds light on the transformative potential of computational modeling in shaping the future of pharmaceutical research. Quantitative Structure-Activity Relationship (QSAR) is a pivotal technique in Computer-Aided Drug Design (CADD) that aids in the rational design of novel drug candidates. This review provides a comprehensive overview of QSAR methodologies, their applications, strengths, limitations, and recent advancements in the field of CADD. By exploring various QSAR models, datasets, molecular descriptors, and statistical techniques, this article aims to shed light on the significance of QSAR in accelerating drug discovery processes.

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Keywords: Receptor, drug designing, biological interaction, molecular docking, modelling, drug discovery, computer aided drug design, docking, multi-target searching, QSAR.

n[if 424 equals=”Regular Issue”][This article belongs to Research & Reviews: A Journal of Pharmaceutical Science(rrjops)]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Research & Reviews: A Journal of Pharmaceutical Science(rrjops)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article: Satish kumar Yadav, Manyta Yadav, Mohd. Wasiullah, Piyush Yadav, Priyanshu Upadhyay. Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review. Research & Reviews: A Journal of Pharmaceutical Science. July 19, 2024; 15(02):56-63.

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How to cite this URL: Satish kumar Yadav, Manyta Yadav, Mohd. Wasiullah, Piyush Yadav, Priyanshu Upadhyay. Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review. Research & Reviews: A Journal of Pharmaceutical Science. July 19, 2024; 15(02):56-63. Available from: https://journals.stmjournals.com/rrjops/article=July 19, 2024/view=0

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References

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Review Article

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Volume 15
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02
Received May 10, 2024
Accepted May 15, 2024
Published July 19, 2024

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