Author(s):
V. Prema, Meera Sivaramakrishnan, M. Rabiya
Email(s):
premapharmchemistry@gmail.com
DOI:
10.52711/0974-4150.2023.00076 
Address:
V. Prema1*, Meera Sivaramakrishnan2, M. Rabiya2
1Department of Pharmaceutical Chemistry, K. K. College of Pharmacy, Gerugambakkam, Chennai -128, Tamil Nadu, India.
2Department of Pharmacy Practice, K. K. College of Pharmacy, Gerugambakkam, Chennai - 128, Tamil Nadu, India.
*Corresponding Author
Published In:
Volume - 16,
Issue - 6,
Year - 2023
ABSTRACT:
QSAR, Quantitative structure-activity relationship has paved a way for itself into the practice of agrochemistry, pharmaceutical chemistry, toxicology and eventually most faces of chemistry for almost 40 years. Quantitative structure-activity relationships (QSAR) have been applied for decades in the establishment of relationships between physicochemical properties of chemical substances and their biological activities for making prediction regarding the activities of new chemical compounds using reliable statistical model. The fundamental principle underlying the decorum is that the difference in structural properties is responsible for the variations in biological activities of the compounds. However, this approach has only a limited utility for designing a new molecule due to the lack of consideration of the 3D structure of the molecules. Even though the trial-and-error factor which is involved in the development of a new drug cannot be ignored completely, QSAR possibly decreases the number of compounds to be synthesized by facilitating the selection of the most promising lead candidates. Many success stories of QSAR have attracted the medicinal chemists to investigate the relationships of structural properties with biological activity.1 Conscientious analysis and modification of independent variables has led to an expansion in development of molecular and atom-based descriptors, as well as descriptors derived from quantum chemical calculations and spectroscopy. The improvement in high-through-put screening procedures also contributes for rapid screening of large number of compounds under similar test conditions and thus minimizes the risk of combining variable test data from different sources. The overall goals of QSAR are to retain their original essence and remain focused on the predictive ability of the approach and its receptiveness to mechanistic interpretation.
Cite this article:
V. Prema, Meera Sivaramakrishnan, M. Rabiya. A Concise Review on role of QSAR in Drug Design. Asian Journal of Research in Chemistry. 2023; 16(6):459-6. doi: 10.52711/0974-4150.2023.00076
Cite(Electronic):
V. Prema, Meera Sivaramakrishnan, M. Rabiya. A Concise Review on role of QSAR in Drug Design. Asian Journal of Research in Chemistry. 2023; 16(6):459-6. doi: 10.52711/0974-4150.2023.00076 Available on: https://ajrconline.org/AbstractView.aspx?PID=2023-16-6-12
REFERENCES:
1. Jitender Verma, Vijay M Khedkar, Evans C Coutinho. 3D-QSAR In Drug Design: A review. Volume 10. Bentham Science Publishers; 2010.
2. Sapkale GN, Khandare DD, Patil SM, Ulhas S Surwase. Drug Design: An Emerging Era of Modern Pharmaceutical Medicines. Asian J. Research Chem. 2010; 3(2): 261-264.
3. Graham L. Patrick. An introduction to Medicinal Chemistry. Fifth Edition. Oxford university press, New York; 1995. Pg. No: 383-406.
4. A K Debnath. Quantitative structure- activity relationship (QSAR) Paradigm-Hansch era to new millennium. Mini review in Medicinal Chemistry; 01 Jul 2001.
5. Ewelina Rutkowska, Karolina Pajak, Krzyszt of Jozwiak. Lipophilicity- Methods of determination and its role in Medicinal Chemistry: Acta Poloniae Pharmaceutica; Jan-Feb 2013.
6. Bharat Jhanwar, Vandana Sharma, Rajeev K Singla, Birendra Shrivastava. QSAR- Hansch Analysis and Related Approaches in Drug Design, pharmacology online 1:306-344. 2011.
7. Donald J Abraham, Burger’s Medicinal Chemistry and Drug Discovery. Sixth Edition. Vol.1. Pg. No: 1-42.
8. Hugo Kubinyi., QSAR and 3D QSAR in drug design Part 2: applications and problems. Vol 2, Issue 12. Dec 1997.
9. Miki Akamatsu. Current state and perspectives of 3D-QSAR. 2(12): 1381-94. Dec 2002.
10. Navin Sainy, Nidhi Dubey, Rajesh Sharma, Nitin Dubey, Jitendra Sainy. 3D QSAR Analysis of Flavones as Antidiabetic agents. Research Journal of Pharmacy and Technology. 2022; 15(4): 1689-5. doi: 10.52711/0974-360X.2022.00283
11. Layla Abdel-Ilah, Elma Veljovic, Lejla Gurbeta, Almir Badnjevic. Applications of QSAR study in Drug Design: International Journal of Engineering Research and Technology (IJERT). 2017; 6(6): 582-587.
12. Jitendar k Malik, Himesh Soni, Singhai A K and Harish Pandey. QSAR- Application in Drug Design: International Journal of Pharmaceutical Research and Allied Sciences. 2013; 2(1).
13. Bruno J Neves, Rodolpho C. Braga, Cleber C. Melo-Filho, Jose Teofilo Moreira- Filho, Eugene N. Muratov and Carolina Horta Andrade. Frontier Pharmacology: QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery. 13 November 2018.
14. Azizeh Abdolmaleki, Jahan B Ghasemi, Fatemeh Ghasemi. Computer Aided Drug Design for Multi-Target Drug Design: SAR/QSAR, Molecular Docking and Pharmacophore Methods. Bentham Science. 2017; 18(5): 556-575.
15. Eslam Pourbasheer, Siavish Riahi, Mohammad Reza Ganguli and Parviz Norouzi. Quantitative Structure Activity Relationship (QSAR) study of interleukin-1 receptor associated kinase-4 (IRAK-4) inhibitor activity by the genetic algorithm and multiple linear regression method: Journal of Enzyme Inhibition and Medicinal Chemistry. 2010; 25(6): 844-853.
16. R. S. Kalkotwar, R. B. Saudagar. Design, Synthesis and anti-microbial, anti-inflammatory, Antitubercular activities of some 2,4,5-trisubstituted imidazole derivatives. Asian J. Pharm. Res. 2013; 3(4): 159-165.
17. Abdellah Oussa, Bouhya Elidrissi, Mounir Ghamali, Samir Chatata, Adnane Aouidate, Mohammed Bouachrine and Tahar Lakhlifi. Research Article on QSAR study of (5- Nitro heteroaryl- 1,3,4- Thiadiazole-2-yl) Piperazinyl Derivatives to predict new similar compounds as Antileishmanial Agents. 2018.
18. Croft S.L, Seifert. K and Yardley. V. Current scenario of drug development for leishmaniasis: Indian Journal of Medical Research. 2006; 123(3): 399–410.
19. Giuseppina Gini. QSAR: What Else? Springer Link. 23 June 2018.
20. Funatsu K, Miyao T, Arakawa M. Systemic generation of chemical structures for rational drug design based on QSAR models. 2011 ; 7(1): 1-9.
21. Hiteshi Tandon, Tanmoy Chakraborty, Vandana Suhag. A Concise Review on the Significance of QSAR in Drug Design: Chemical and Biomolecular Engineering. 2019; 4(4): 45-51.
22. Kubinyi H, Mannhold R, Kroogsgard-Larsen P, Timmerman H, Eds.; Wiley-VCH: Weinheim, 1993, QSAR: Hansch Analysis and Related Approaches: In Methods and Principles in Medicinal Chemistry. 1993; 1: 240.
23. Maryam Hamzeh-Mivehroud, Babak Sokouti, Siavoush Dastmalchi. An introduction to the basic concepts in QSAR-aided drug design. 2017.
24. Pathan S, Ali SM, Shrivastava M. Quantitative structure activity relationship and drug design: A Review. Int. J. Res. Biosciences. 2017; 5(4): 1-5.
25. Patnala Ganga Raju Achary. Applications of Quantitative Structure-Activity Relationships (QSAR) based Virtual Screening in Drug Design. 2020; 20(14).
26. Roger Perkins, Hong Fang, Weida Tong, William J Welsh. Quantitative structure- activity relationship methods: perspectives on drug discovery and toxicology. Environmental Toxicology and chemistry: An International Journal. 2003; 22 (8).
27. Sandhya Kortagere, Markus Lill, John Kerrigan. Role of Computational Methods in Pharmaceutical Sciences. 22 August 2012.
28. Sapna Jain Dabade, Dheeraj Mandloi, Amritlal V Bajaj, Harsha Are. Molecular Docking and QSAR Studies for Modelling Antifungal Activity of Triazine Analogues against Therapeutic Target NMT of Candida Albicans. International Journal of Pharmaceutical Sciences and Drug Research. 2021: 13(2): 141-146.
29. Selassie, C.D, Mekapati, S.B. Verma R.P. QSAR: Then and Now, Volume 9. Current Topics in Medicinal Chemistry. pp. 1357-1379. 2002.
30. Stephani Joy Y Macalino, Vijayakumar Gosu, Sunhye Hong, Sun Choi. Role of computer aided drug design in modern drug discovery. Archives of Pharmaceutical Research. 2015; 38: 1686-1701.
31. Sunyoung Kwon, Ho Bae, Jeonghee Jo and Sungroh Yoon. Comprehensive assemble in QSAR Prediction for Drug Discovery. BMC Bioinformatics. Article Number: 521. 2019.
32. Thirumurthy Madhavan. A Review of 3D-QSAR in Drug Design. Journal of the Chosun Natural Science. 2012; 5(1): 1-5.
33. Vanessa Aguiar-Pulido, Marcos Gestal, Maykel Cruz-Monteagudo, Juan R Rabunal, Julian Dorado, Cristian R Munteanu. Evolutionary Computation and QSAR Research. Current Computer aided Drug Design. 2013; 9(2): 206-225.
34. Verma J, Khedkar VM, Coutinho EC. 3D-QSAR in Drug Design: A Review- Current Topics in Medicinal Chemistry, Current Topics in Medicinal Chemistry. 2010; 10: 95-115.
35. Tao Wang, Mian- Bin Wu, Jian-Ping Lin, Li-Rong Yang. Quantitative Structure- activity relationship: promising advances in drug discovery platforms. Expert Opinion on Drug Discovery. 2015.
36. Niranjan D, Gill S, Shrivastava D, Jain A, Agrawal OP. Quantitative structure activity relationships in computer aided drug design: a review. Journal of Drug Delivery and Therapeutics. 2019; 9(3): 645-9.
37. Tandon H, Chakraborty T, Suhag V. A concise review on the significance of QSAR in drug design. Chemical and Biomolecular Engineering. 2019; 4(4): 45-51.
38. Puzyn T, Leszczynski J, Cronin MT, editors. Recent advances in QSAR studies: methods and applications.
39. Achary PG. Applications of quantitative structure-Activity relationships (QSAR) based virtual screening in drug design: a review. Mini Reviews in Medicinal Chemistry. 2020; 20(14):1375-88.
40. Kellogg GE, Semus SF. 3D QSAR in modern drug design. Modern Methods of Drug Discovery. 2003: 223-41.
41. Patel HM, Noolvi MN, Sharma P, Jaiswal V, Bansal S, Lohan S, Kumar SS, Abbot V, Dhiman S, Bhardwaj V. Quantitative structure–activity relationship (QSAR) studies as strategic approach in drug discovery. Medicinal Chemistry Research. 2014; 23(12): 4991-5007.
42. Hopfinger AJ. Computer-assisted drug design. Journal of Medicinal Chemistry. 1985; 28(9): 1133-9.
43. Dunn III WJ. Quantitative structure—activity relationships (QSAR). Chemometrics and Intelligent Laboratory Systems. 1989; 6(3): 181-90.
44. Sharma OP, Saini NK, Gupta V, Sachdeva K, Arya H. Evolutionary history of QSAR: a review. J. Natur. Cons. 2011; 1(4): 266-72.
45. Topliss JG, Fukunaga JY. Quantitative structure-activity relationships in drug design. Annual Reports in Medicinal Chemistry. 1978; 13: 292-303.
46. Mahalakshmi PS, Sree Mahalakshmi P, Jahnavi Y. A review on QSAR studies. Int J Adv Pharm Biotechnol. 2020; 6:19-23.
47. Bajot F. The use of QSAR and computational methods in drug design. In Recent advances in QSAR studies 2010 (pp. 261-282). Springer, Dordrecht.
48. Shivam Gupts, M. Yamuna. Physiochemical Properties of Medicines - Using Graph Eccentricity and Multiple Regression. Research J. Pharm and Tech. 2018; 11(9): 4112-4112. doi; 10.5958/0974- 360X.2018.00756.4.
49. Nachiket S. Dighe, Pankaj Shinde, Harshali Anap, Sanjay Bhawar, Deepak S. Musmade. QSAR Study and Synthesis of some new 2, 5-disubstituted 1,3,4-oxadiazole derivatives as Anti-microbial and Anti-inflammatory agents. Asian J. Pharm. Res. 2014; 4(4): 174-179.
50. Satyajit Dutta, Sagar Banik, Sovan Sutradhar, Sangya Dubey, Ira Sharma. 4D-QSAR: New Perspectives in Drug Design. Asian J. Research Chem. 2011; 4(6): 857-862.
51. Venkatesh Kamath, Aravinda Pai. Application of Molecular Descriptors in Modern Computational Drug Design –An Overview. Research J. Pharm. and Tech. 2017; 10(9): 3237-3241. doi: 10.5958/0974-360X.2017.00574.1
52. Sonal Dubey, Sakshi Bhardwaj, Prabitha Parbhakaran, Ekta Singh. In silico Prediction of Pyrazoline Derivatives as Antimalarial agents. Asian Journal of Pharmaceutical Research. 2022; 12(2): 119-4. doi: 10.52711/2231-5691.2022.00018.
53. Arun kashid, Sashikant Dhawale. 3D-QSAR analysis of some HIV Reserve transcriptase Inhibitors. Asian J. Research Chem. 2011; 4(9): 1385-1387.
54. Yogesh Vaishnav, Alok Singh Thakur, Chanchal Deep Kaur, Shekhar Verma, Achal Mishra, Sanmati Kumar Jain, Piyush Ghode. QSAR Analysis of some N, N-diphenyl urea derivatives as CCR5 Receptor Antagonist. Research J. Pharm. and Tech. 2018; 11(9): 3802-3810. doi: 10.5958/0974- 360X.2018.00697.2