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Current Drug Therapy

Editor-in-Chief

ISSN (Print): 1574-8855
ISSN (Online): 2212-3903

Research Article

QSAR Studies on Thienopyrimidines as Potential Antimicrobial Agents

Author(s): Pranali A. Jadhav* and Pratiksha Jadhav

Volume 19, Issue 6, 2024

Published on: 10 November, 2023

Page: [748 - 755] Pages: 8

DOI: 10.2174/0115748855266001231026063520

Price: $65

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Abstract

Background: Recent research has revealed promising antibacterial action for thienopyrimidines. To comprehend the underlying molecular features underlying their antibacterial potency, a thorough quantitative structure-activity relationship (QSAR) investigation is required.

Objectives: In order to clarify the structural parameters for effective antibacterial activity, we conducted QSAR analyses on a variety of thienopyrimidines in this work.

Methods: Through the analysis of physicochemical properties and molecular descriptors, we aimed to develop predictive models that can guide the design of novel thienopyrimidine derivatives with enhanced antimicrobial potential.

Results: It was discovered through the descriptor importance analysis that specific physicochemical characteristics, including lipophilicity, electronic distribution, and steric effects, significantly influenced the antibacterial efficacy of these drugs.

Conclusion: The identified molecular characteristics and descriptors can be used to guide the development of new thienopyrimidine derivatives with higher antibacterial activity.

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[1]
Neves BJ, Braga RC, Melo-Filho CC, Moreira-Filho JT, Muratov EN, Andrade CH. QSAR-based virtual screening: Advances and applications in drug discovery. Front Pharmacol 2018; 9: 1275.
[http://dx.doi.org/10.3389/fphar.2018.01275] [PMID: 30524275]
[2]
Roy K, Das R. A review on principles, theory and practices of 2D-QSAR. Curr Drug Metab 2014; 15(4): 346-79.
[http://dx.doi.org/10.2174/1389200215666140908102230] [PMID: 25204823]
[3]
Golbraikh A, Tropsha A. QSAR modeling using chirality descriptors derived from molecular topology. J Chem Inf Comput Sci 2003; 43(1): 144-54.
[http://dx.doi.org/10.1021/ci025516b] [PMID: 12546547]
[4]
Subramani AK, Sivaperuman A, Natarajan R, Bhandare RR, Shaik AB. QSAR and molecular docking studies of pyrimidine-coumarin-triazole conjugates as prospective anti-breast cancer agents. Molecules 2022; 27(6): 1845.
[http://dx.doi.org/10.3390/molecules27061845] [PMID: 35335208]
[5]
Kwon S, Bae H, Jo J, Yoon S. Comprehensive ensemble in QSAR prediction for drug discovery. BMC Bioinformatics 2019; 20(1): 521.
[http://dx.doi.org/10.1186/s12859-019-3135-4] [PMID: 31655545]
[6]
Lambrinidis G, Tsantili-Kakoulidou A. Challenges with multi-objective QSAR in drug discovery. Expert Opin Drug Discov 2018; 13(9): 851-9.
[http://dx.doi.org/10.1080/17460441.2018.1496079] [PMID: 29996683]
[7]
Mao J, Akhtar J, Zhang X, et al. Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models. iScience 2021; 24(9): 103052.
[http://dx.doi.org/10.1016/j.isci.2021.103052] [PMID: 34553136]
[8]
Keyvanpour MR, Shirzad MB. An analysis of QSAR research based on machine learning concepts. Curr Drug Discov Technol 2021; 18(1): 17-30.
[http://dx.doi.org/10.2174/1570163817666200316104404] [PMID: 32178612]
[9]
Achary PGR. Applications of Quantitative Structure-Activity Relationships (QSAR) based virtual screening in drug design: A review. Mini Rev Med Chem 2020; 20(14): 1375-88.
[http://dx.doi.org/10.2174/1389557520666200429102334] [PMID: 32348219]
[10]
Hussain W, Rasool N, Khan YD. Insights into machine learning-based approaches for virtual screening in drug discovery: Existing strategies and streamlining through FP-CADD. Curr Drug Discov Technol 2021; 18(4): 463-72.
[http://dx.doi.org/10.2174/1570163817666200806165934] [PMID: 32767944]
[11]
Wang T, Wu MB, Lin JP, Yang LR. Quantitative structure–activity relationship: Promising advances in drug discovery platforms. Expert Opin Drug Discov 2015; 10(12): 1283-300.
[http://dx.doi.org/10.1517/17460441.2015.1083006] [PMID: 26358617]
[12]
Abdel Hamid AM, Shehta W. Synthesis of some novel furan-tagged thienopyrimidine derivatives as antibacterial agents. J Heterocycl Chem 2019; 56(2): 485-92.
[http://dx.doi.org/10.1002/jhet.3423]
[13]
Mulla JA, Palkar MB, Maddi VS, Khazi IA. Rational design of antibacterial thienopyrimidines by 2D-QSAR study. J Drug Deliv Ther 2012; 2(2)
[http://dx.doi.org/10.22270/jddt.v2i2.118]
[14]
Mabkhot Y, Kheder N, Farag A. Synthesis and antimicrobial activity of some new thieno[2,3-b]thiophene derivatives. Molecules 2013; 18(4): 4669-78.
[http://dx.doi.org/10.3390/molecules18044669] [PMID: 23603949]
[15]
Wang T, Yuan X, Wu MB, Lin JP, Yang LR. The advancement of multidimensional QSAR for novel drug discovery - where are we headed? Expert Opin Drug Discov 2017; 12(8): 1-16.
[http://dx.doi.org/10.1080/17460441.2017.1336157] [PMID: 28562095]
[16]
Pavase LS, Mane DV. Synthesis and anticancer activities of novel (tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidine-4-yl)-pyrolidine-2-carboxylic acid derivatives. Med Chem Res 2016; 25(10): 2380-91.
[http://dx.doi.org/10.1007/s00044-016-1692-x]
[17]
Rami C, Patel L, Patel C, Parmar J. Synthesis, antifungal activity, and QSAR studies of 1,6-dihydropyrimidine derivatives. J Pharm Bioallied Sci 2013; 5(4): 277-89.
[http://dx.doi.org/10.4103/0975-7406.120078] [PMID: 24302836]
[18]
Lagardère P, Fersing C, Masurier N, Lisowski V. Thienopyrimidine: A promising scaffold to access anti-infective agents. Pharmaceuticals 2021; 15(1): 35.
[http://dx.doi.org/10.3390/ph15010035] [PMID: 35056092]
[19]
Islam F, Quadery TM. Therapeutic potential, synthesis, patent evaluation and SAR studies of thieno[3,2-d]pyrimidine derivatives: Recent updates. Curr Drug Targets 2021; 22(17): 1944-63.
[http://dx.doi.org/10.2174/1389450122666210526094047] [PMID: 34042033]
[20]
Ali EMH, Abdel-Maksoud MS, Oh CH. Thieno[2,3-d]pyrimidine as a promising scaffold in medicinal chemistry: Recent advances. Bioorg Med Chem 2019; 27(7): 1159-94.
[http://dx.doi.org/10.1016/j.bmc.2019.02.044] [PMID: 30826188]
[21]
Kerru N, Maddila SN, Maddila S, Sobhanapuram S, Jonnalagadda SB. Synthesis and antimicrobial activity of novel thienopyrimidine linked rhodanine derivatives. Can J Chem 2019; 97(2): 94-9.
[http://dx.doi.org/10.1139/cjc-2018-0220]
[22]
Shaaban OG, Issa DAE, El-Tombary AA, Abd El Wahab SM, Abdel Wahab AE, Abdelwahab IA. Synthesis and molecular docking study of some 3,4-dihydrothieno[2,3-d]pyrimidine derivatives as potential antimicrobial agents. Bioorg Chem 2019; 88: 102934.
[http://dx.doi.org/10.1016/j.bioorg.2019.102934] [PMID: 31026720]
[23]
Veerasamy R, Rajak H. QSAR studies on neuraminidase inhibitors as anti-influenza agents. Turk J Pharmaceut Sci 2021; 18(2): 151-6.
[http://dx.doi.org/10.4274/tjps.galenos.2020.45556] [PMID: 33900700]
[24]
Bhatia N, Mahadik K, Bhatia M. QSAR analysis of 1,3-diaryl-2-propen-1-ones and their indole analogs for designing potent antibacterial agents. Chem Pap 2009; 63(4): 456-63.
[http://dx.doi.org/10.2478/s11696-009-0026-6]
[25]
Mullani A, Disouza JI. Synthesis and QSAR study of N-substituted [5-(1 H -1, 2, 4-Triazol-5yl)pyridine-2-YL]methanimine Derivatives as potential antibacterial. Asian J Res Chem 2015; 8(9): 561-5.
[http://dx.doi.org/10.5958/0974-4150.2015.00089.9]
[26]
Hafez HN, El-Gazzar ARBA, Zaki MEA. Simple approach to thieno[3,2-d]pyrimidines as new scaffolds of antimicrobial activities. Acta Pharm 2016; 66(3): 331-51.
[http://dx.doi.org/10.1515/acph-2016-0029] [PMID: 27383884]
[27]
Giri T, Sailaja G, Laxminarayana E, Thirumala Chary M, Ramesh M. Synthesis and antibacterial activity of novel 4-4-(methylamino)thieno[3,2-d]pyrimidin-2-yl-benzohydrazide derivatives. Russ J Gen Chem 2017; 87(6): 1275-80.
[http://dx.doi.org/10.1134/S1070363217060238]

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